motivated learning: balancing between autonomy and structure

A problem which is often mentioned by teachers is that students are notmotivated. Also, research indicates that students’ motivation declines overtime. Teachers are a crucial factor in motivating students, both in terms oftheir behavior in the classroom and in designing digital learning tasks.

This dissertation is concerned with how appropriate teacher behavior anddigital learning tasks can be motivating and how teachers can be trainedin learning this behavior and designing these tasks. In general, striking theright balance between autonomy support and structure support isessential to promote students’ motivation.

As a result of the findings of this dissertation, the body of knowledge inthe field of student motivation will be expanded. This thesis offers someguiding insights and principles that teachers need to fit into their dailypractice in order to motivate students in their classes.

Motivated Learning: Balancing BetweenAutonomy and Structure

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Motivated Learning: Balancing BetweenAutonomy and StructureAnne-Marieke van Loon

Motivated learning omslag:Opmaak 1 27-03-2013 10:18 Pagina 1

Motivated Learning:Balancing BetweenAutonomy and Structure

Anne-Marieke van LoonOpen University, The Netherlands

© 2013 Anne-Marieke van LoonISBN 978-94-90014-00-1

Productie: Franssen & Van Iersel

Alle rechten voorbehouden.Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand en/of openbaar gemaakt in enige vorm of op enige wijze, hetzij elektronisch,mechanisch, door fotokopieën,opnamen of op enige andere manier zonder voorafgaande schriftelijke toestemming van de uitgever.

Motivated Learning:Balancing BetweenAutonomy and Structure

PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Open Universiteitop gezag van de rector magnificus prof. mr. A. Oskamp ten overstaan van een door het College voor promoties ingestelde commissie in het openbaar te verdedigen op vrijdag 19 april 2013 te Heerlen om 16:00 uur

door

MARIA JOHANNA ANTONIA PAULINA VAN LOON

geboren op 29 december 1980 te Roosendaal

PROMOTORProf. dr. R.L. Martens, Open Universiteit

COPROMOTORDr. A.A. Ros, Fontys Hogescholen

OVERIGE LEDEN BEOORDELINGSCOMMISSIEProf. dr. J.J.H. van den Akker, Universiteit TwenteProf. dr. A.E.M.G. Minnaert, Rijksuniversiteit GroningenProf. dr. Th.J. Bastiaens, Open UniversiteitProf. dr. F.L.J.M. Brand-Gruwel, Open Universiteit

Table of Contents

Chapter 1 | Introduction1.1 Challenges in Education1.2 Theoretical Framework 1.3 Research Questions and Relevance of the Study1.4 Nature of the Research1.5 Structure of the StudyReferences

Chapter 2 | Motivated Learning with Digital Learning Tasks: What About Autonomy and Structure?

2.1 Introduction2.1.1 The Self-Determination Theory and Basic

Psychological Needs2.1.2 The Roles of Autonomy Support and Structure Support2.1.3 The Present Study and Hypotheses

2.2 Methodology2.2.1 Design2.2.2 Participants2.2.3 Digital Learning Task, Design Features and Cognitive Tools2.2.4 Four Experimental Conditions2.2.5 Procedure2.2.6. Measures

2.2.6.1 Perceived autonomy, perceived competence, and intrinsic motivation

2.2.6.2 Learning outcomes2.3 Results

2.3.1 Effects of Digital Learning Conditions with Autonomy Support on Perceived Autonomy (Hypothesis 1a)

2.3.2 Effects of Digital Learning Conditions with Structure Support on Perceived Competence (Hypothesis 1b)

2.3.3 Effects of Digital Learning Conditions on Intrinsic Motivation (Hypothesis 2)

2.3.4 Effects of Digital Learning Conditions on Learning Outcomes (Hypothesis 3)

2.3.5 Perceived Autonomy and Perceived Competence Increase Intrinsic Motivation and Learning Outcomes

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2.4 Discussion2.4.1 Limitations and Future Research2.4.2 Conclusion

References

Chapter 3 | Designing Digital Problem Based Learning Tasks that Motivate Students

3.1 Introduction3.1.1 The Importance of Autonomy Support and

Structure Support3.1.2 Training Teachers3.1.3 The Present Study and Hypotheses

3.2 Methodology3.2.1 Design3.2.2 Participants3.2.3 Training3.2.4 Procedure3.2.5 Measures

3.2.5.1 Perceived autonomy, perceived competence, and intrinsic motivation

3.2.5.2 Teacher report: autonomy support and structure support

3.2.5.3 Teacher report: skill in creating digital PBL tasks

3.2.6 Data Analyses3.3 Results

3.3.1 Teachers’ Perceptions (Hypothesis 1)3.3.2 Students’ Perceived Autonomy and Perceived

Competence (Hypothesis 2)3.3.2.1 Perceived autonomy

3.3.2.1.1 Difference between primary- and secondary school students

3.3.2.2 Perceived competence3.3.2.2.1 Difference between primary- and

secondary school students 3.3.3 Students’ Intrinsic Motivation (Hypothesis 3)

3.3.3.1 Difference between primary- and secondary school students

3.4 DiscussionReferences

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Chapter 4 | Training Teacher’s Autonomy-supportive and Structure-supportive Behavior

4.1 Introduction4.1.1 Autonomy Support and Structure Support4.1.2 Training Teachers4.1.3 The Present Study and Hypotheses

4.2 Methodology4.2.1 Design4.2.2 Participants4.2.3 Training4.2.4 Procedure4.2.5 Measures

4.2.5.1 Teacher report: autonomy support and structure support

4.2.5.2 Student perceptions of autonomy support and structure support

4.2.5.3 Student motivation4.2.5.4 Observations of autonomy-supportive and

structure-supportive behavior4.2.6 Data Analyses

4.3 Results4.3.1 Autonomy-supportive and Structure-supportive

Behavior of Teachers 4.3.2 Perceived Autonomy Support, Perceived Structure

Support and Motivation of Students4.3.3 Effects of Perceived Autonomy Support and

Perceived Structure Support on Motivation 4.4 Discussion

4.4.1 ConclusionReferences

Chapter 5 | Characteristics of an Effective Teacher Professional Development Program on Students’ Motivation

5.1 Introduction5.1.1 Autonomy Support and Structure Support5.1.2 Teacher Professional Development5.1.3 The Present Study and Research Questions


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5.2 Methodology5.2.1 Design5.2.2 Participants5.2.3 Intervention5.2.4 Procedure5.2.5 Measures

5.2.5.1 Measuring design principles5.2.5.2 Measuring teachers’ differences

5.2.6 Data Analyses5.3 Results

5.3.1 Which Design Principles have Contributed Most to Teachers’ Professional Development According to Teachers? 5.3.2.1 Are there differences between teachers’

evaluation based on initial skills?5.3.2.2 Are there differences between teachers’

evaluation based on the increase of skills?5.4 Discussion

References

Chapter 6 | Discussion6.1 Recapitulation of the Results of the Present Thesis6.2 From Results to Main Conclusions6.3 Discussion6.4 Limitations and Directions for Future Research6.5 Theoretical and Practical Implications6.6 Concluding Remarks

References

Summary (in Dutch)

Curriculum Vitae

List of publications

Acknowledgements (in Dutch)


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Chapter 1Introduction

This dissertation attempts to solve the challenges of motivation currently fa-cing education. Motivation is defined as the process that initiates, guides andmaintains goal-oriented behaviors. Motivation is essential to education be-cause it provides the energy and direction that students need to be successfulin school. A large body of research shows that high classroom motivation pre-dicts good classroom performance (e.g. Pintrich & Schrauben, 1992; Ryan &Deci, 2000; Skinner & Belmont, 1993). Low classroom motivation has negativeconsequences, such as student dropout (Vallerand, Fortier, & Guay, 1997). De-spite the importance of motivation, it seems that it generally decreases duringschool years (Gottfried, Flemming, & Gottfried, 2001; Stoel, Peetsma, & Roele-veld, 2001), leaving teachers wondering how they can motivate students. Onething that schools can do to motivate students is to use information and com-munication technology (ICT) in the classroom (Liu & Bera, 2005; Liu, Horton,Olmanson, & Toprac, 2011; Mayer, 2011). Although digital applications offermany opportunities to motivate pupils, teachers often do not know how toapply them to this end.

This research will answer the question of how teachers can motivate stu-dents in the classroom both with and without ICT. Teachers are a crucial factorin motivating students and can sometimes struggle with this often difficulttask. Therefore, the influence not only of the learning environment on stu-dents’ motivation but also that of teacher professionalization concerning theirmotivating skills is the object of this research.

The goal of this dissertation is to expand the body of knowledge in thefield of student motivation and teacher professionalization. It also aims to con-tribute to educational practice. We want to help teachers to motivate studentsin their daily teaching practice. Because we consider teachers as professionals,we offer no handy recipes for motivating pupils, but guiding insights and prin-ciples that teachers need to accommodate in their daily practice.

The motive for this research is elaborated in four challenges, derived fromour experiences and dialogues with teachers and other professionals in educa-tional practice, and grounded on literature results. These challenges are descri-bed in the next paragraph.

1.1 Challenges in EducationMotivational challengeAn important challenge for schools is to motivate students. Teachers fre-quently complain that students are not motivated. Also, research shows thatstudents’ motivation declines over time; students find school boring, and theydo not enjoy learning (Skinner, Furrer, Marchand, & Kindermann, 2008). If stu-dents are motivated they are generally more extrinsically oriented than intrinsi-


Chapter 1 | Introduction

cally motivated, and especially in secondary education students often workunder external pressure rather than experiencing the inherent joy an activitygives (Van Nuland, 2011).

Motivation refers largely to the will of children and young people to learn(Vansteenkiste, Sierens, Soenens, & Lens, 2007). It is an inner process that incitesa person's particular behavior, gives direction to this behavior and ensures thatthis behavior is maintained (Woolfolk, Hughes, & Walkup, 2008). Student motiva-tion is crucial because when students are motivated, they tend to approach chal-lenging tasks with greater eagerness, persevere in difficult situations, and takepleasure in their achievements (Stipek, 1993). If students are motivated to learn,they often perform better (Eccles, Wigfield, & Schiefele, 1998).

An explanation for the motivation problem among pupils is an inadequate“fit” between the school and the personal needs and interests of students(Minnaert, Boekaerts, & De Brabander, 2007; Vansteenkiste et al., 2007). Ifschools fail to satisfy the latter, and do not accommodate the desired learningstyles of their pupils, then, and certainly in the longer term, the motivation ofstudents for school decreases. Additional consequences are under-utilizationof talents and risk of premature school dropout (Hardre & Reeve, 2003).

Many teachers struggle with this daily challenge and ask themselves whatthey can do to promote the motivation of students. Although teachers recog-nize that they have a supporting role, as part of the learning environment tomotivate students (Urdan & Schoenfelder, 2006; Vedder, Boekaerts, & Seegers,2005), little research has been performed on the role of teachers in promotingmotivation in the classroom; certainly primary education is a relatively unexplo-red area (Thoonen, Sleegers, Peetsma, & Oort, 2011).

Motivational challenge in a digital learning environmentMany believe that one opportunity for schools to motivate students is offeredby the use of ICT in the classroom (Liu & Bera, 2005; Liu et al., 2011; Mayer,2011). In the last decades there has been a large increase in the ICT and digitalapplications used in schools (OECD, 2001). According to Martens (2007) multi-media learning is beginning to flourish. The nonlinear, associative, and interac-tive capabilities of multimedia can allow students to access informationaccording to their own learning needs and present multiple related problemsin one environment (Hoffman & Richie, 1997).

The expectation is that, with the increase of the digital possibilities in theclassroom, teachers themselves will also design more digital learning tasks forstudents supported by problem-based learning (PBL). PBL is an instructionalapproach that exemplifies authentic learning to motivate students (Liu & Bera,2005; Liu et al., 2011; Mayer, 2011). In digital learning tasks featuring PBL, the



emphasis is on acquiring conceptual knowledge by solving complex problemsin rich contexts (Barrows, 1996; Dunlap, 2005). In this process a student com-pares new information from different sources and relates this information toexisting knowledge and new insights (Barrows, 1996; Dunlap, 2005). The aimof digital learning tasks designed to be used in this more constructivist way isnot to ensure that children give a single “right answer”; rather, the goal is hel-ping them to develop increasingly complex and thorough knowledge (Nieder-hauser & Stoddart, 2001). This is in contrast to tasks that encourage studentsto improve skills by using drill and practice methods.

Despite the potential of digital PBL tasks, teachers sometimes find that di-gital tasks are not automatically motivating. Just creating a task based on PBLand letting students work on the computer will not automatically lead to moti-vated students and effective education. The media type is not the decisive fac-tor (Brand-Gruwel, 2012). It is the quality of the digital task that determinessuccess. Unfortunately, research shows that the quality of digital learning taskscreated by teachers is often of a low level. Tasks are often unclear as regardstheir learning goals and the requirements for students' performance. More -over, these digital learning tasks give insufficient guidelines for a structuredand result-oriented learning process (Inspection of education, 2006). Digital learning tasks in the class are often ill-structured, so students find it difficult tochoose a path to solve the problem (Toprac, 2011). As a consequence, manylearners do not make effective choices and sometimes experience informationoverload (Azevedo & Witherspoon, 2009; Liu & Bera, 2005; Liu et al., 2011;Mayer, 2011; Narciss & Körndle, 1998).

So, the challenge for teachers who design and use digital learning tasksbased on PBL in the classroom is to take advantage not only of the appealingappearance or novelty of the technology but also the didactic and educationalsubstance of digital tasks that improve motivation and promote learning.

Professionalization challengeTeachers involved in the design of effective digital learning tasks that enhancemotivation and learning should be intensively professionalized (Higgins, 2003).Creating a learning environment that motivates students demands new know-ledge and skills of teachers. Merely installing computers and software in theclassroom will not change the didactic methods of teachers (Bastiaens, 2007;Coonen, 2005; Stoddart & Niederhauser, 1993; Van Dusen & Worthen, 1992,1995). The question is how teachers can be professionalized most effectively.Although the success of a new teaching approach largely depends on the qua-lity of the teacher (Hattie, 2009), educational research shows that changing theeducational behavior of teachers is a very complex matter (Fullan, 1991).



The term "professionalism" covers both the behavior and the attitude ofthe teacher. Attitude and behavior influence each other and focus on attitudeis particularly important when change is required. Attitude involves the deeperbeliefs, values and motivation that lead to changes in behavior (Bergenhene-gouwen & Mooijman, 2010). Similarly to motivating students, professionaliza-tion of teachers depends closely on their intrinsic motivation. According toMartens (2009) teachers often do not support their own professional needsand consequently fail to meet the conditions for their own motivation.

The challenge for schools is how teachers can be professionalized so a realbehavioral change occurs and students are more motivated in the classroom.

Research challengeThree challenges concerning the improvement of student motivation havebeen described so far. The fourth is described below. Research can help toequip teachers with knowledge and insights to meet these challenges. Conse-quently, it is important that the research is relevant to teaching practice andleads to practical conclusions. The role of researchers is marginalized, however.There is a gap between educational practice and educational research and theimpact of scientific research on educational practice is disappointing (Broek-kamp & van Hout-Wolters, 2006; Martens, 2010; Onderwijsraad, 2011). Oftenthe complexity of the educational interventions is not taken into account ineducational research, and as a consequence the results are not useful for thefield (Martens & Diepstraten, 2011; Reeves, 2006). Most educational researchexperiments are conducted in laboratory settings focused on a single depen-dent variable and researchers try to control other variables. But in fact the dailypractice of teachers does not comprise one variable but multiple dependentvariables with their own limitations, complexities, and dynamics (Collins, Jo-seph, & Bielaczyc, 2004).

The challenge for educational research is to contribute to solving the dailychallenges of teachers. Therefore, it is important to tackle complex problemsin real educational contexts and to use existing and new insights together withteachers (Reeves, 2006). Not only should research address questions of ge-nuine interest to educators but the findings should also be presented in a waythat is useful to practitioners (Reeves, 2000). Research results that consider therole of social context have better potential for influencing educational practice(Barab & Squire, 2004).

Central research questionIn summary, there are many challenges that education has to deal with. This re-search will attempt to solve the four mentioned challenges concerning motivation



and try to address the following general question: how can teachers promote (digital) motivated learning in students and how can they be trained to do so?

To answer this question we make use of starting-points in previous researchincluding insights from the Self-Determination Theory (SDT). In the next para-graph we will further elaborate on the theoretical framework that is the basisof the research and relates to the first three challenges. After this we will focuson the sub-questions of the research and the specific research approach tosolve the fourth challenge concerning the nature of the research.

1.2 Theoretical Framework Promoting motivation with autonomy support and structure supportInsights from the Self-Determination Theory (SDT) have been used in attemptsto offer some solutions to the motivational challenge. Among the many theo-retical perspectives on motivation (see Boekaerts, Van Nuland, & Martens,2010 for an overview), SDT has become a very influential one. SDT has, in itssearch for answers to motivational problems, received substantial empiricalsupport (Deci & Ryan, 2008; Ryan & Deci, 2000). SDT indicates that the sourceof motivation is internal to the student, and when the learning environment ful-fills the student's basic psychological needs, motivation will flourish, since it isan innate propensity (Deci & Ryan, 2000). Psychological needs are the needsfor autonomy, competence, and relatedness (Deci & Ryan, 2000). A fundamen-tal principle of SDT is that this theory is universal in nature and applies to every -one regardless of their cultural context.

Literature on motivation in recent decades has increasingly shown a shiftfrom a more behavioristic approach to motivation, that considers extrinsic fac-tors such as reward and punishment as important motivators, to an approachthat intrinsic motivation preconceives (Martens & Boekaerts, 2007; Van Nuland,Dusseldorp, Martens, & Boekaerts, 2010), such as SDT (Deci & Ryan, 2000; Ryan& Deci, 2000). SDT emphasizes the importance of creating a favorable learningenvironment that elicits intrinsic motivation. Intrinsic motivation is the naturaltendency to engage in activities for the inherent joy an activity gives. This is incontrast to extrinsic motivation, where behavior relies on external rewards and isconsidered to be inferior to intrinsic motivation (Ryan & Deci, 2000).

In line with SDT, teachers can enhance or decrease student motivation bymeeting basic psychological needs (i.e. autonomy, competence, and related-ness; Deci & Ryan, 2000). The need for autonomy involves being self-organizedand having a sense of choice about one’s behavior. The need for competenceinvolves the experience of efficacy while completing a (learning) task (Ryan &Deci, 2000). Relatedness is defined as “the desire to feel connected to others-to love and care, and to be loved and cared for” (Deci & Ryan, 2000, p. 231).



In this research we concentrate on autonomy and competence because theseprinciples are especially applicable in digital learning. If teachers want to in -crease the motivation of students, their own behavior has to change to moreneed-supporting behavior. According to research on SDT (Ryan & Deci, 2000), ateacher has to be autonomy-supportive to meet the need for autonomy (Reeve,Ryan, Deci, & Jang, 2007) and provide structure to meet the need for compe-tence (Grolnick & Ryan, 1989; Skinner & Belmont, 1993; Tucker et al., 2002).

Autonomy support is about a variety of teacher behaviors aimed at ac-knowledging students’ perspective and thus enhancing students’ feelings ofvolition (Reeve, Nix, & Hamm, 2003). Teachers can be autonomy-supportive byproviding students with a degree of choice (Katz & Assor, 2007). The fact thatstudents can choose from several options makes them feel more in control oftheir behavior (Reeve et al., 2003). Another aspect of an autonomy-supportiveteaching style includes providing a rationale for a task. If students receive ameaningful explanation of why it is useful for them to do a certain learningtask, the probability increases that they will internalize the personal relevanceof the learning task and, therefore, be motivated to learn (Deci, Eghrari, Pa-trick, & Leone, 1994; Reeve, Jang, Hardre, & Omura, 2002). Furthermore, re-search shows that it is important that teachers acknowledge students’ feelingsby trying to empathize with them and respecting their perspective (Reeve &Jang, 2006), and also by avoiding the use of controlling language (Reeve, Deci,& Ryan, 2004).

There is a risk, however, that autonomy-supportive environments createtoo many associative distractions and overwhelm students with too many choi-ces; as a result students do not make effective choices and may even expe-rience information overload (Azevedo & Witherspoon, 2009). This reasoning isin line with the findings based on cognitive load theory (Sweller, 2004), whichposits that imposing too much extraneous load hinder students from under-standing the course content (Morrison & Anglin, 2005). Thus, besides auto-nomy support, structure support also plays a key role in a teaching style topromote students’ motivation (Connell, 1990; Guay, Ratelle, & Chanal, 2008;Skinner & Belmont, 1993; Skinner et al., 2008). Providing structure supportmeans that teachers make their goals and expectations clear and explicitlydescribe the consequences of achieving or not achieving the goals (Connell,1990; Connell & Wellborn, 1991; Reeve et al., 2004; Skinner & Belmont, 1993).In addition, teachers can provide structure support by offering help and sup-port, by adjusting teaching strategies to the level of the student and by provi-ding clear procedures so students better know how to accomplish goals(Reeve et al., 2004; Skinner & Belmont, 1993).

In practice, teachers often only meet the need for autonomy or compe-



tence, but not both (Reeve & Jang, 2006; Reeve, Jang, Carrell, Jeon, & Barch,2004). Generally, teachers tend to think that autonomy support and structuresupport are two opposing principles. Especially in schools that operate accor-ding to constructivist principles, students often experience much autonomybut less structure. Constructivism means that students are given the opportu-nity to discover knowledge through their own active exploration (Slavin, 1994).In this way, they activate their own prior conceptions and relate them to newknowledge (Järvelä & Niemivirta, 1999). This does not mean, however, thatstudents decide for themselves what they want to learn and only get auto-nomy support (Ros, 2007). It seems that teachers have difficulties striking a ba-lance between autonomy and structure (Gerrits, 2012) in daily practice. Thesupposed contradiction between autonomy and structure is often the sourceof lengthy debates in and about education.

Motivation in digital learning environmentsFulfilling students' needs applies not only to the behavior of teachers in theclassroom; this approach is important for the whole learning environment in theclass, and for the digital learning environment of students. Through the use ofdigital learning tasks students have access to different information resources (i.e.texts, images, and video sequences) in a nonlinear way (Hoffman & Richie, 1997).

Despite the significance of motivation for learning consequences (Eccles etal., 1998), it has not received commensurate attention in digital learning (Jones& Issroff, 2005; Miltiadou & Savenye, 2003) particularly, studies aiming to vali-date SDT in digital learning contexts are rarely found (Chen & Jang, 2010).There are a few exceptions such as Xie, Debacker, and Ferguson (2006), whoapplied SDT to examine online discussion, Roca and Gagné (2008), who exami-ned e-learning continuance intention in the workplace, and Chen and Jang(2010), who investigated SDT in an online program with adult learners. Thecombined effect of autonomy support and structure support on learning andmotivation has not yet been empirically examined in the context of digital learn ing tasks with young students in primary and secondary education.

Professionalization of teachersTeachers need to be professionalized to apply autonomy support and structuresupport in their educational setting. Often such professional development ischaracterized as ineffective (Borko, Jacobs, & Koellner, 2010; Hanushek, 2005;Martens, 2010). A key reason why teachers' professional development hasbeen so disappointing is that this is a complex process (Clarke & Collins, 2007;Collins & Clarke, 2008). To change teachers' behavior, changes in teachers’ be-liefs and practices must occur (Clarke & Hollingsworth, 2002; Opfer & Pedder,



2011). Therefore, teacher learning must be conceptualized as a complex sys-tem rather than as an event (Clarke & Collins, 2007; Collins & Clarke, 2008).

One way of dealing with the complex nature of teacher development is tofocus on professional development approaches that are more closely alignedwith constructivist and situative theories grounded in classroom practice andinvolving the formation of professional learning communities instead of work-shops or courses outside the school (Borko et al., 2010). Teachers' professionaldevelopment is increasingly conceptualized as a learning process that is em-bedded within the context of the school and takes place in the workplace (e.g.Putnam & Borko, 2000; Smylie & Hart, 1999).

Thanks to previous research on successful professional development, diffe-rent principles or features of high-quality professionalization can be distinguis-hed that increase teachers’ learning and change their practice, and ultimatelyimprove students’ learning (Desimone, 2009; Desimone, Porter, Garet, Yoon, &Birman, 2002; Garet, Porter, Desimone, Birman, & Yoon, 2001). For instance,research shows that change of teacher behavior requires professional develop-ment activities to be of sufficient duration, including both the time over whichthe activity is spread and the number of hours spent on the activity (Cohen &Hill, 2001; Fullan, 1993; Guskey, 1994). Professional development is far moreeffective in changing teachers’ classroom practice when it enjoys the collectiveparticipation of teachers from the same school, department, or grade (Desi-mone et al., 2002; Garet et al., 2001; Wayne, Yoon, Zhu, Cronen, & Garet,2008), when it is closely connected with their work in the classroom (Hargrea-ves & Fullan, 1992; Wilcox, 1998) and when it engages them in active learning(Garet et al., 2001; Loucks-Horsley, Hewson, Love, & Stiles, 1998).

1.3 Research Questions and Relevance of the StudyThe theoretical considerations above lead to a set of research questions thatare presented below.

Research questionsOn the basis of existing theories this research attempts to answer the generalquestion: how can teachers promote (digital) motivated learning in studentsand how can they be trained to do so? To answer this question, this disserta-tion addresses four specific research questions (RQs):

1. What should good digital learning environments contain to stimulate andmotivate students to learn? What is the combined and relative effect of au-tonomy support and structure support on motivation and learning out -comes in digital environments?



2. Can teachers be trained in applying autonomy support and structure sup-port in their digital learning tasks so students experience more autonomy,competence and motivation in these tasks?

3. Can teachers be trained to adopt an autonomy-supportive and structure-supportive teaching style during a school year, so students experience moreautonomy support and structure support and their motivation increases?

4. Which design principle does teachers recognize as contributing to theirprofessional development in autonomy-supportive and structure-suppor-tive behavior?

Relevance There is still little knowledge about how teachers can meet the need for bothautonomy and competence so students are more motivated and learn better.Research on the proper balance between autonomy support and structure sup-port is particularly relevant for learning in both face-to-face and digital learningenvironments.

Theoretical relevanceResearch on the impact of autonomy support and structure support on motiva-tion and learning is generally scarce and has not been previously studied in thecontext of digital learning (Chen & Jang, 2010). This research will contribute tothe further substantiation and operationalization of SDT in educational settings.It will also build on knowledge about professional development of teachers todetermine which training principles are effective in changing teachers’ behavior.

Practical relevance This research gives insights into the importance of autonomy support andstructure support for motivation and performance of students and how thesetwo relate to each other. It will help teachers to understand how to influencetheir students’ motivation through their behavior in the class and through thedigital learning tasks that they design. This research will try to provide specificguidelines on how to design digital learning tasks and which design principlesteachers can be used to train teachers in this context.

1.4 Nature of the ResearchPractice-based scientific researchBecause this research aims to contribute to educational practice as well as offertheoretical insights, a practice-based scientific research approach is chosen. The



primary purpose of practice-based scientific research is to solve practical pro-blems and contribute to education improvement in a scientific way. Becausethis research has to deal with complex processes (behavior of teachers) and va-riables with long-term effects, an oversimplification of reality should be avoided(Martens, 2010; Martens, Kessels, de Laat, & Ros, 2012; Ros, Timmermans, vander Hoeven, & Vermeulen, 2009; Ros & Vermeulen, 2010).

For practice-based scientific research the dialogue between theory and prac-tice is paramount (Stenhouse, 1983). Through a holistic and complex view ofclassroom practice we reach a better understanding of that complex reality. Be-cause it is scientific research, an important goal is to deliver generic knowledge(Stenhouse, 1983). In a number of areas practice-based research is similar to de-sign-based research (DBR). DBR is grounded in both theory and the real-worldcontext (Wang & Hannafin, 2005) and is pragmatic because its goals are solvingcurrent real-world problems by designing and enacting interventions and exten-ding theories (Van den Akker, Gravemeijer, McKenney, & Nieveen, 2006). By vir-tue of being conducted in a real-world context in collaboration with practitionersand based on theory, research is much more likely to lead to effective applica-tion and be relevant for teachers (Van den Akker et al., 2006).

Martens et al. (2012) cite a number of specific characteristics of practice-based scientific research. In practice-based scientific research new phenomenaare often investigated. Another feature is that the research object often con-cerns (learning) processes and, in order to obtain good visibility, it is necessaryto follow these processes for an extended period of time. Interrelatedness isalso an important consideration because research is done within schools andamong teachers who can affect each other, more intensive forms of data col-lection with multiple viewpoints (triangulation) are needed. A final feature ofpractice-based scientific research is working with small samples.

Practice-based scientific research delivers holistic knowledge. To offer a solution to problems in education, this type of research examines the new ap -proach in its totality, with great attention to the context. Solutions are practi -cable for schools.

CriteriaTwo kinds of quality criteria for practice-based scientific research can be distin-guished, according to Verschuren (2009) (cf. Martens et al., 2012; Ros & Ver-meulen, 2010). There are basic criteria, which, in principle, apply to all research(science internal requirements) and usability criteria more specific to practice-based scientific research (science external requirements). In this research, theaim is to meet all of the criteria. It is evident that we meet the basic criteria (in-ternal validity, external validity, controllability, cumulativity and ethical aspects).



We briefly describe below how we want to comply with the usability criteria. Usability criteria 1. Understandability of research results

The results will be understandable and accessible to the educational field.Multiple ways of dissemination will be employed, including online tools ta-king into account.

2. Acceptance and experienced legitimacy The educational field will experience the results as true, relevant and legiti-mate. This will be achieved by relating the problems that teachers expe-rience with student motivation and by checking the solutions together withteachers in terms of their attainability in daily practice.

3. Learning opportunities The research will also produce knowledge to improve teaching practice.The intention is that the instruments which are developed for data collec-tion can also be used as a reflective tool that teachers use in daily practice,independently of the research.

1.5 Structure of the StudyIn the forthcoming chapters, four empirical studies will address the researchquestions.

Chapter 2: Motivated Learning with Digital Learning Tasks: What About Auto-nomy and Structure?In Chapter 2, we will look more closely at SDT and explore the influence of thedimensions of autonomy support and structure support on motivation and learn -ing outcomes in digital environments. This chapter asks: what should good digital learning environments contain to stimulate and motivate students tolearn? What is the combined and relative effect of autonomy support andstructure support on motivation and learning outcomes in digital environ-ments? (RQ 1).

To answer this question the principles of SDT will be operationalized anddigital learning tasks will be developed. The research will be experimental innature and based on a 2 (with or without autonomy support) x 2 (with or with -out structure support) design. Participants are 320 fifth- and sixth-grade stu-dents from eight elementary schools throughout the Netherlands.The findings of Chapter 2 are the basis for the other chapters in which the prin-ciples of autonomy support and structure support will be further examined.

Chapter 3: Designing Digital Problem-Based Learning Tasks that Motivate Students



Chapter 3 will focus on the question of whether teachers can be trained in ap-plying autonomy support and structure support in their digital learning tasksso that primary and secondary school students experience more autonomy,competence and motivation in these tasks (RQ 2).

Participants are 184 fifth-, sixth-, seventh- and eighth- grade students and20 teachers. The research is based on a one-group pre-test post-test design.Questionnaires will be filled in by teachers and students to measure the pro-gress of digital learning tasks in fulfilling the need for autonomy, competenceand motivation. Because the data have a two-level hierarchical structure (stu-dents are nested in classes), hierarchical linear modeling will be used.

Chapter 4: Training Teachers Autonomy-supportive and Structure-supportiveBehavior In contrast to the previous two chapters, Chapter 4 is about the behavior of teachers in the classroom. Now that we know from Chapters 2 and 3 what aspects of SDT are important for motivating students in a digital learning environment; according to SDT these principles also apply to teacher behavior.Chapter 4 asks how teachers can be trained to adopt an autonomy-supportiveand structure-supportive teaching style during a school year so students expe-rience more autonomy support and structure support and their motivation in -creases (RQ 3).

The data for this research will be collected from a sample of 23 elemen-tary teachers and 164 students from grades three, four, five, and six at a primary school in the Netherlands. The research is based on a one-grouppre-test post-test design. Questionnaires will be used to measure the per -ceived teaching style of the teachers' and students’ perceptions of their teachers’ teaching style. Classroom observations will also be used to analyzethe teaching style.

Chapter 5: Characteristics of an Effective Teachers’ Professional DevelopmentProgram on Students’ MotivationChapter 5 will elaborate on the aspects of the training program described inChapter 4 in which teachers change their behavior to an autonomy-supportiveand structure-supportive teaching style. It will be important to examine whichdesign principle does teachers recognize as contributing to their professionaldevelopment (RQ 4). We can learn from this example of effective teacher pro-fessional development and apply it in future programs.

The analyses of Chapter 5 are based on the same sets of data as in Chap-ter 4. Questionnaires will be used to define which design principle has contri-buted to teachers' professional development.



Chapter 6: Conclusions and DiscussionIn Chapter 6 conclusions and recommendations for follow-up research will bepresented. It will start by answering the research questions. Then, a generalconclusion on the basis of the findings will follow. The discussion specifieswhat this means for the four challenges mentioned earlier. We will elaborateon the strengths and limitations of the research and possibilities for further research. Lastly, recommendations for the educational field will be given.

The four chapters in this dissertation are written as separate articles in such a waythat they can be read independently. Consequently, some sections of the chap-ters have inevitable overlap. Though each chapter highlights a different set of hy-potheses, the analyses in Chapters 4 and 5 are based on the same sets of data.



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1 This chapter is published as: Van Loon, A.-M., Ros, A., & Martens, R. (2012). Motivated learningwith digital learning tasks: what about autonomy and structure? Educational Technology Researchand Development, 60(6), 1015-1032.

This chapter is presented as: Van Loon, A.-M. (2010, November). Effective Digital Learning Tasks.Their Impact on Learning and Motivation at European Association for Practitioner Research on Improving Learning Conference, Lisbon, Portugal.

Chapter 2Motivated Learning with DigitalLearning Tasks: What About Autonomy and Structure?1

AbstractIn the present study, the ways in which digital learning tasks contribute to stu-dents’ intrinsic motivation and learning outcomes were examined. In particular,this study explored the relative contributions of autonomy support and theprovision of structure in digital learning tasks. Participants were 320 fifth- andsixth-grade students from eight elementary schools throughout the Nether-lands. The results show that a digital learning task that combined autonomysupport and structure support had a positive effect on both intrinsic motivationand learning outcomes in students. A digital learning task that only providedstructure support also had a positive effect on learning outcomes, but a digitallearning task with only autonomy support did not yield a similar effect.

Keywords: Digital learning task; Self-determination theory; Structure sup-port; Autonomy support; Intrinsic motivation.

2.1 IntroductionWhen students are motivated, they tend to approach challenging tasks withgreater eagerness, persevere in difficult situations, and take pleasure in theirachievements (Stipek, 1993). If students are motivated to learn, they oftenperform better (Ryan & Deci, 2000a). Computer-supported learning environ-ments offer features that may promote motivation (Liu, Horton, Olmanson, &Toprac, 2011; Mayer, 2011). A digital problem-based learning (PBL) environ-ment is an example of a computer-supported learning environment thattakes an instructional approach to motivate students (Liu & Bera, 2005; Liu et al., 2011; Mayer, 2011). In this type of environment, the emphasis is on sol -ving complex problems in rich contexts to facilitate the development ofhigher-order thinking skills in students (Savery & Duffy, 1995). Students haveopportunities to apply their content knowledge and skills while working oncontextualized problems (Dunlap, 2005). Important aspects of PBL are thatlearning activities are student-centered, problems are the starting-point andstimulus for learning and new information is acquired through self-directedlearning (Barrows, 1996).

Making use of a hypermedia environment could enhance PBL, because hy-permedia could provide richer information resources using different media (i.e.texts, images, and video sequences) in a more efficient way (Liu & Bera, 2005;Narciss, Proske, & Körndle, 2007). The nonlinear, associative, and interactivecapabilities of hypermedia can allow students to access information accordingto their own learning needs, and present multiple related problems in one en-vironment (Hoffman & Richie, 1997).

Certain researchers, however, have noted the increased demands on learn-ers, as indicated by relatively high dropout rates and a diminished ability tofocus during learning (Clark, Yates, Early, & Mouton, 2010; Mayer, 2011). Al-though PBL hypermedia environments provide rich and realistic contexts thatallow learners to explore multiple options, the extensive amount of availableinformation may cause them to become distracted from their learning objec-tives, lose their way in cyberspace, focus too much on irrelevant information,or absorb important information only cursorily (Salomon & Almog, 1998).

A PBL hypermedia environment entails an increased degree of freedomthat can discomfort students (Hoffman & Richie, 1997). In these environments,students are often presented with a complex, ill-structured problem that theyare expected to resolve and are able to choose whichever path they desire tosolve the problem (Toprac, 2011). Many learners do not make effective choicesand may experience information overload (Azevedo & Witherspoon, 2009; Liu & Bera, 2005; Narciss & Körndle, 1998). This reasoning is in line with thefindings based on cognitive load theory (Sweller, 2004), which posits that digital



tasks imposing too much extraneous load hinder students from understandingthe course content (Morrison & Anglin, 2005).

An important question that emerges from this discussion is this: whatshould good digital learning environments contain to stimulate and motivatestudents to learn? This study is based on a digital problem-based learning taskin a hypermedia environment in which students’ learning is initiated in theprocess of solving a complex problem. The challenge for teachers who designand use digital learning tasks in the classroom is to take advantage not only ofthe appealing appearance or novelty of the technology but also the didacticand educational substance of digital tasks that might improve motivation andpromote learning.

This study builds upon the Self-Determination Theory (SDT), which is an in-fluential theory regarding motivation. By specifying the contextual environ-ments that foster optimal learning, SDT is a relevant framework for the studyof favorable conditions for digital PBL that enhance motivation and learningperformance. First, we will look more closely at the design principles that canbe derived from SDT.

2.1.1 The Self-Determination Theory and Basic Psychological NeedsSDT is a motivational theory that focuses on intrinsic motivation. The theory as-sumes that all individuals, regardless of background, have an intrinsic urge toexplore, organize, understand, and assimilate with their environment (Deci,Ryan, & Williams, 1996). Because SDT assumes that everyone is naturally moti-vated, the theory’s focus is on the conditions that facilitate or hinder intrinsicmotivation (Ryan, Kuhl, & Deci, 1997). Research reveals that to function opti-mally, an individual needs to satisfy three universal, innate, and essential psy-chological needs: the need for competence (White, 1959), the need forautonomy (DeCharms, 1968; Deci, 1975), and the need for relatedness(Baumeister & Leary, 1995). The need for competence is concerned with theexperience of efficacy after completing a (learning) task (Ryan & Deci, 2000a).The need for autonomy refers to the initiative and freedom that a person ex-periences when engaged in an activity in the absence of outside pressure withrespect to his or her personal goals (Ryan & Deci, 2000b). Finally, the need forrelatedness concerns the feeling of connectedness to significant others, includ-ing teachers (Deci & Ryan, 2000).

Students who are intrinsically motivated to learn often perform better inschool (Ryan & Deci, 2000a). Intrinsic motivation has been associated with highcognitive performance, in-depth learning, and better recall of the acquiredknowledge (Grolnick & Ryan, 1987; Vansteenkiste, Simons, Lens, Sheldon, &Deci, 2004). Intrinsically motivated students tend to be more curious (Kuhl,



2000; Lewalter & Krapp, 2004), exhibit greater exploratory behavior (Martens,Gulikers, & Bastiaens, 2004), and focus more on understanding rather thansimply memorizing (Deci & Ryan, 2008).

If a digital learning environment motivates and encourages learners tolearn with greater depth, students should experience both autonomy and competence. Both of these needs may be fulfilled by the provision of auto -nomy support and structure support in the digital learning environment.

2.1.2 The Roles of Autonomy Support and Structure SupportAn environment with autonomy support is an environment in which externalpressure is minimal, the personal goals of students are recognized (Deci &Ryan, 2000, 2008), and choices are offered (Zuckerman, Porac, Lathin, Smith, &Deci, 1978). Being able to choose from among several options makes studentsfeel more in control of their actions (Reeve, Nix, & Hamm, 2003). Research byCordova and Lepper (1996) shows that when students work on a meaningfuldigital learning task that presents options, their intrinsic motivation levels arehigher. Students are more engaged in the task, employ more deep-level learn-ing, and learn more in a shorter amount of time. In addition to offeringchoices, providing a rationale for a task can also promote a sense of autonomy.If students receive a meaningful explanation of the purpose behind a certainlearning task, they are likely to be more personally engaged in the learningtask and, therefore, to be more motivated to learn (Deci, Eghrari, Patrick, &Leone, 1994). Autonomy-supportive language in learning tasks is characterizedby non-directive language that encourages students to take the initiative (Deciet al., 1996). Research shows that environments that are autonomy-supportivehelp to fulfill the need for autonomy (Reeve, Ryan, Deci, & Jang, 2007) andfoster greater intrinsic motivation in students (Reeve & Jang, 2006). Such envi-ronments stimulate students’ curiosity and encourage them to confront chal-lenges (Flink, Boggiano, & Barrett, 1990; Ryan & Grolnick, 1986).

There is a risk, however, that autonomy-supportive environments create toomuch associative distraction and overwhelm students with too many choices. Re-search by Martens et al. (2004) shows that students with high intrinsic motivationengage in greater exploratory behavior during digital learning tasks. Exploratorybehavior, however, increases the likelihood of “getting lost” and following inef-fective online learning paths. The risk is that, given the nonlinear and associativevisual appeal of the digital task, the learner will wander from one item to an-other. As a consequence learners will only construct shallow associative cognitivenetworks which have no intellectual merit (Okan, 2003; Salomon & Almog,1998). Thus, in addition to autonomy support, structure support also plays a keyrole in an optimal digital learning environment (Guay, Ratelle, & Chanal, 2008).



Providing structure makes the learning environment less chaotic and moreconsistent and predictable for students. Moreover, from a motivational point ofview, structure support enables students to feel more competent (Grolnick &Ryan, 1989; Skinner & Belmont, 1993; Tucker et al., 2002). According to SDT,structure support is of secondary importance compared with autonomy sup-port in an optimal learning environment (Guay et al., 2008). Providing structuremeans providing clear goals and expectations for students and explicitly de-scribing the consequences of achieving (or not achieving) those goals (Connell,1990). Providing structure also means providing help, support, appropriatestrategies, and guidance for students to carry out a task successfully (Connell,1990; Skinner & Belmont, 1993). Finally, structure support requires providingstudents with clear procedures to follow (Reeve, Deci, & Ryan, 2004). Structuresupport is associated not only with positive learning outcomes but also withgreater learner engagement (Skinner & Belmont, 1993; Tucker et al., 2002),lower passivity with regard to learning, and less school-avoidant behavior(Patrick, Turner, Meyer, & Midgley, 2003).

Providing structure for students is not the opposite of providing autonomysupport, however (Ryan, 1993). According to Reeve et al. (2004), autonomysupport and structure support are separate dimensions of a teaching style thatmotivates students. In fact, the opposite of an autonomy-supportive environ-ment is a controlling environment (Black & Deci, 2000; Koestner, Ryan,Bernieri, & Holt, 1984). A controlling environment is characterized by extrinsicincentives and pressuring language that tend to interfere with student motiva-tion (Reeve, Jang, Carrell, Jeon, & Barch, 2004).

The combined influence of autonomy and structure on learning and moti-vation has not yet been empirically examined in the context of digital tasks butonly in physical learning environments. Research studies on learning in theclassroom show that offering choices and providing structure together pro-duce positive effects on student motivation and the extent of self-regulatedlearning (Jang, Reeve, & Deci, 2010; Sierens, Vansteenkiste, Goossens, Soe-nens, & Dochy, 2009). In an empirical study among 526 eleventh- to twelfth-grade students, Sierens et al. (2009) found that structure support wasassociated with more self-regulated learning only under conditions of moder-ate and high autonomy support. Therefore, teachers who want their studentsto be more self-regulated in their learning should provide help, goals, and ex-pectations in ways that support autonomy. Jang et al. (2010) studied the effectof autonomy support and structure support in a sample of 133 teachers and2,523 students. The authors concluded that the elements of structure support(e.g. clear expectations and goals) had to be offered in an autonomy-support-ive way to enhance student engagement.



2.1.3 The Present Study and HypothesesResearch on the proper balance between autonomy support and structure sup-port is particularly relevant to problem-based learning (PBL) in a hypermediaenvironment. Digital PBL tasks in the classroom often offer a large amount ofinformation without structure support, thereby increasing the risk of informa-tion overload and superficial information processing (Narciss & Körndle, 1998).The challenge is to create a digital learning task that provides students withchoices and guidance. This study was based on the assumption that digital PBLtasks should provide both autonomy support and structure support and thatboth dimensions positively influence students’ intrinsic motivation and learningoutcomes. Currently, however, there is a lack of scientific research on auto -nomy support and structure support in a hypermedia learning environment.Particularly with the emergence of digital PBL tasks in education it is importantto examine whether there is evidence to support this type of task design.

This study aims to answer the following question: “In what ways can digitaltasks based on PBL in a hypermedia environment contribute to the motivationand learning outcomes of students?”

In summary, we examine the combined and relative influence of autonomysupport and structure support on learning in digital PBL hypermedia environ-ments.

To answer the research question, this study explores three hypotheses. Thefirst hypothesis (1A) is that in an autonomy-supportive digital learning task inwhich external pressure is minimal and choices are offered, students experi-ence a greater sense of autonomy, and (1B) providing structure support in adigital learning task makes the task predictable and offers enough guidancefor students to experience a greater sense of competence.

Because the nature of the digital learning task also affects intrinsic mo-tivation and learning outcomes, the second hypothesis (2) is that an autonomy-supportive digital learning task with structure support contributes to a higherdegree of intrinsic motivation.

The third hypothesis (3) is that an autonomy-supportive digital learningtask with structure support yields better learning outcomes.

2.2 Methodology2.2.1 DesignIn this research, we examined the effects of autonomy support and the provi-sion of structure support on motivation and learning outcomes in a digitallearning environment. The research was experimental in nature and based on a2 (with or without autonomy support) by 2 (with or without structure support)design. Students from all the appropriate classrooms within a school were ran-



domly selected and assigned to one of the four experimental conditions. Be-cause students within a school were randomly selected and assigned to one ofthe four experimental conditions, the effect of the school as a factor on themotivation and learning outcomes of students was minimized. We designed adigital learning task that was used in each of the four experimental conditions.The conditions differed in their degrees of autonomy support and structuresupport. Learning condition 1 involved a digital task with autonomy supportand structure support. Learning condition 2 involved a digital task with struc-ture support but without autonomy support. Learning condition 3 involved adigital task with autonomy support but without structure support. Learningcondition 4 involved a digital task with neither autonomy support nor structuresupport. Table 2.1 presents the factorial design with sample sizes by learningcondition.

Table 2.1

Factorial design with sample sizes by learning condition

Autonomy support

Structure support + Autonomy support - Autonomy support

+ Structure support Learning condition 1 Learning condition 2

n = 80 n = 80

- Structure support Learning condition 3 Learning condition 4

n = 80 n = 80

2.2.2 ParticipantsThe study took place in the Netherlands. Participants were 320 fifth- and sixth-grade students from eight elementary schools across the country. The meanage of the students at the outset of the study was 11.7 years (SD = 0.63, range= 10.0 - 13.6 years). A total of 160 boys and 160 girls from twelve differentclassrooms participated. On the basis of reports issued by the National Boardof Education, we assumed that the learning outcomes of the students from theparticipating schools would be representative of the level achieved by theirpeers at other schools throughout the country. We selected the participatingschools according to two criteria: (1) the students in these schools were accus-tomed to work independently, and (2) these schools integrated working withcomputers into the curriculum.

The task was incorporated into the regular curriculum in the classroom.Students received no reward or extra credit for their participation.

In every participating class, students were randomly assigned to one offour conditions. In total, we randomly assigned 80 students (38 boys, 42 girls)



to condition 1 with autonomy support and structure support, 80 students (41boys, 39 girls), to condition 2 with structure support but without autonomysupport, 80 students (46 boys, 34 girls) to condition 3 with autonomy supportbut without structure support, and 80 students (35 boys, 45 girls) to condition4 with neither autonomy support nor structure support (Table 2.1). No studentdropped out of the experiment.

2.2.3 Digital Learning Task, Design Features and Cognitive ToolsThe digital PBL task in this study incorporates design features that are sup-ported by problem-based learning and hypermedia learning.

Problem-based learning (PBL) is an instructional approach that exemplifiesauthentic learning and emphasizes solving problems in rich contexts (Dunlap,2005). Compared with the main characteristics of PBL (Barrows, 1996) the digi-tal PBL task in this study was a structured PBL- like activity. It contained mostaspects of PBL, namely:• Learning is student-centered as students assume a major responsibility for

their own learning; in the task in this study students themselves had to solvea problem about advertising with their own arguments and findings.

• Teachers are facilitators or guides; in this task there was electronic guidance.For example students could use a roadmap to understand and manage theproblem better.

• Problems form the organizing focus and stimulus for learning; in this task stu-dents had to solve a problem about the need to convey a clear message inadvertising.

• Problems, similar to those one would face in future professions, are a vehiclefor the development of problem-solving skills; students were asked to play therole of an advertising creator who had to encourage people to buy a product.

• New information is acquired through self-directed learning; students had ac-cess to cognitive tools that facilitated the learning process. For example, stu-dents could use an information database to learn from their own study andresearch and acquire new information.

The task in this study was more of a structured PBL-like activity because onetenet of PBL, that learning does occur in small groups, was not met. In thisstudy students learned individually.

The task consisted of a hypermedia electronic learning environment wherestudents could navigate freely. The task was composed of hypertext with im-ages, graphics and video. The content of the task related to the need to con-vey a clear message in advertising. In all conditions, the introduction of thetask began by presenting a problem situation that was situated in a rich con-text with different hypermedia formats (i.e. text, graphics, video) so that stu-



dents could see the complexity of the problem from multiple perspectives.Specifically, students were asked to play the role of an advertising creator whohad to insure good advertising to encourage people to buy a product. All thestudents read instructions for the task so that they knew what was expected ofthem. The instructions were as follows: “In this task, you are a creator of adver-tisements. You are going to decide what good advertising is and identify thetricks used in advertisements to ensure that customers really do buy more.”Also, the task provided a digital information database with advertisements andonline sources with hyperlinks so students could navigate freely on the internetto facilitate knowledge acquisition and to solve the problem. In addition in allconditions they had access to computer-based cognitive tools that facilitatedthe learning process (Lajoie, 1993).

Cognitive tools are computer-based instruments that assist learners in ac-complishing complex cognitive tasks. (Lajoie, 1993). Lajoie categorizes cogni-tive tools as follows: (1) tools that share the cognitive load, (2) tools thatsupport cognitive processes, (3) tools that support cognitive activities thatwould be out of reach otherwise, and (4) tools that allow hypothesis genera-tion and testing. Tools in this study could be grouped into categories 1 and 2.Tools that share cognitive overload existed of the problem presentation stu-dents received, and an information database with online sources and examplesof advertisements so students could navigate to acquire information about ad-vertising and to solve the problem. Tools supporting cognitive processes werea digital roadmap of the stages required to complete the task successfully anda template to interpret and organize information and present methods forsolving the problem (a Word or PowerPoint document). See Figure 2.1 for a visual presentation of the start screen of the task.

The assignment and the basic features of the task (as described above)were the same for each student in all conditions. The only differences betweenthe conditions were associated with autonomy support and structure support.



Figure 2.1. Visual presentation of the start screen of the task in condition 1

2.2.4 Four Experimental ConditionsThe digital learning task in condition 1 (with autonomy support and structuresupport) provided options and structural guidance (Figure 2.1). In terms of au-tonomy support, students had control over the content (i.e. the student couldselect an advertisement for him/herself), online sources (i.e. the student couldsearch for information on websites of their own choice), and computer pro-gram (i.e. the student could choose to complete the task in Word or Power-Point). An explanation was given about the relevance of the task to theirlearning. The autonomy-supportive task was also characterized by languagethat was non-directive and encouraged initiative (i.e. “You can make use of…,”and “You can do this task.”). In terms of structure support, students were giveninformation to support their achievement of the learning goals, such as aroadmap of the stages required to complete the task successfully. Additionally,there was clarity regarding the way in which the finished product would be as-sessed. Lastly, the task with structure support also provided clear proceduresso that the students knew how long they were allowed to work on the task andwhat they could do when they had finished their work.

The digital learning task in condition 2 (without autonomy support butwith structure support) offered no choices and only structural guidance. Students were instructed to use a particular advertisement, to use only a setof recommended online sources, and to complete the task in either Word orPowerPoint. The relevance of the task was not explained. The language wasdirective (i.e. “You should do this task,” and “You are expected to performthe task properly.”). In terms of structure support, information was given to



support students’ achievement of the learning goals, such as a roadmap of the stages required to complete the task successfully. Clear proceduresand information regarding the way in which the finished product would be assessed were available.

The digital learning task in condition 3 (with autonomy support but withoutstructure support) offered choices and no structural guidance. Students wereallowed to choose their own content, online sources, and program to presenttheir findings. An explanation was given about the relevance of the task. Theautonomy-supportive task was characterized by language that was non-direc-tive and encouraged initiative. In terms of structure support, no informationwas given to insure achievement of the learning goals; students were not givena roadmap of the stages required to complete the task successfully. Studentswere not told how the finished product would be assessed, nor did they receive a description of the procedures. Thus, they did not know how longthey were allowed to work on the task and what they could do when they hadfinished their work.

The digital learning task in condition 4 (without structure support and without autonomy support) offered no choices and no structural guidance. Students were required to use a particular advertisement, to use the recom-mended online sources, and to complete the task either in Word or Power-Point. There was no explanation of the relevance of the task. The languagewas directive. In terms of structure support, no information (e.g. a roadmap)was provided to support students’ achievement of the learning goals. Studentswere not given a description of the procedures nor were they told how the finished product would be assessed.

2.2.5 ProcedureThe intervention was conducted in separate rooms at the different schools. Anumber of the schools had special computer rooms available for the task,which meant that all the students were able to work on the task at the sametime. In other schools, the students had to work during different sessions. Theintervention was conducted during a single session and took approximately 1.5hours for each learner. An experimenter explained the task at the beginning ofthe session. The teacher was present but played no active role. The studentscompleted the task independently and were not allowed to work together.Students were allowed to ask questions but were only given minimal help.Teachers were not allowed to give instructions. At the end of the task, eachstudent filled out a questionnaire concerning the extent to which he or she hadbeen motivated to complete the task and the degree of autonomy and com-petence that he or she had experienced.



2.2.6. Measures2.2.6.1 Perceived autonomy, perceived competence,

and intrinsic motivationTo measure the intrinsic motivation of students, we used the Intrinsic Motiva-tion Inventory (IMI), which was originally developed by Ryan (1982). The IMI isa structured written questionnaire proven by McAuley, Duncan, and Tammen(1987) to be reliable and valid. The subscale “interest / enjoyment” from theIMI contains seven items that measure intrinsic motivation (e.g. “I enjoyeddoing this activity very much” and “This activity was fun to do.”). The per-ceived degrees of competence and autonomy were measured by questionsbased on the IMI subscales of “perceived competence” that consisted of sixitems (e.g. “I am satisfied with my performance in this task” and “I was prettyskilled at this task”) and “perceived freedom of choice” that consisted of sevenitems (e.g.“I believe I had some choice about doing this activity” and “I feltlike it was not my own choice to do this task,” which was reverse coded). Eachitem is presented in the form of a statement about which the respondent indi-cates his or her degree of agreement or disagreement on a seven-point Likertscale (with a score of one indicating “totally disagree” and a score of seven in-dicating “totally agree”). In this sample, the reliability was high for all threescales: intrinsic motivation (α = .95), perceived autonomy (α = .95), and per-ceived competence (α = .93). No significant correlation was observed betweenperceived autonomy and perceived competence, which suggested that thesevariables were independent. To detect the possible issue of multicollinearity ofperceived autonomy and perceived competence, we examined the impact onthe precision of estimation of the regressors, with the result being reflected inthe variance inflation index (VIF). If the largest VIF is greater than 10, there iscause for concern (Bowerman & O’Connell, 1990). In this study, none of the VIFvalues was greater than 10 (maximum VIF = 1.00). A tolerance below 0.2 alsoindicates a potential problem (Menard, 1995), but this result was not found inour data (minimum tolerance = 0.99). Thus, multicollinearity was not detected,making it possible to interpret the effects of perceived autonomy and per-ceived competence in a reliable manner.

2.2.6.2 Learning outcomesThe learning outcomes were measured by assessing the learning presentations(Word or PowerPoint document) created by the students. The students had totake the role of an advertising creator and produce a Word or PowerPoint docu-ment about effective advertising based on their research on the Internet. Thequality of the learning products was assessed by a standard scoring form basedon the learning goals of the task. The scoring form consisted of four areas in



which students could earn points: the number of techniques that advertisers useto make customers buy more (maximum three points), the strengths of the ad-vertisement (maximum two points), suggestions for how to improve the advertis-ing message (maximum two points), and the readability of the report (maximumone point). Students could earn a maximum of eight points. Two independentreviewers scored all of the products. There was a high inter-rater reliability be-tween the ratings of the two reviewers (r = .95, p < .001).

2.3 Results2.3.1 Effects of Digital Learning Conditions with Autonomy

Support on Perceived Autonomy (Hypothesis 1a)First, we explored the effect of the digital learning conditions with autonomysupport on perceived autonomy. A general linear model univariate analysis ofvariance indicated that the main effect of autonomy support on perceived au-tonomy was significant (F(1, 316) = 610.27, p < .001, partial η² = .66). There wasno significant interaction between the provision of structure support and auto -nomy support on perceived autonomy (F(1, 316) = 0.86, p = .356, partial η² =.00). The perceived autonomy scores in the conditions with autonomy support (1and 3) (M = 5.79, SD = 1.07) were higher than the scores in the conditions with-out autonomy support (2 and 4) (M = 2.71, SD = 1.16). Thus, students experi-enced a greater sense of autonomy in the autonomy-supportive conditions.

2.3.2 Effects of Digital Learning Conditions with Structure Support on Perceived Competence (Hypothesis 1b)

Second, we explored the impact of the digital learning conditions with structuresupport on perceived competence. A general linear model univariate analysis ofvariance showed that the main effect of structure support on perceived compe-tence was significant (F(1, 316) = 217.65, p < .001, partial η² = .41). There was nosignificant interaction between the provision of structure support and autonomysupport on perceived competence (F(1, 316) = 2.49, p = .116, partial η² = .01).Students under conditions with structure support (1 and 2) (M = 5.55, SD = 1.10)scored higher on perceived competence than students under conditions withoutstructure support (3 and 4) (M = 3.65, SD = 1.21). Thus, providing structure sup-port in the learning environment resulted in a greater sense of competence.

2.3.3 Effects of Digital Learning Conditions on Intrinsic Motivation (Hypothesis 2)

We analyzed the relationship between digital learning conditions and intrinsicmotivation. A general linear model univariate analysis of variance was con-ducted with intrinsic motivation as the dependent variable and autonomy sup-





port (with or without) and provision of structure support (with or without) asthe independent variables. The main effect of autonomy support on intrinsicmotivation was significant (F(1, 316) = 69.86, p < .001, partial η² = .18). Themain effect of structure support on intrinsic motivation was also significant (F(1, 316) = 70.29, p < .001, partial η² = .18), as was the interaction betweenautonomy support and structure support (F(1, 316) = 14.60, p < .001, partial η²= .04). These results meant that the effect of structure support on intrinsic mo-tivation was different in conditions with autonomy support from that in conditions without autonomy support. Simple effects analysis showed signifi-cant differences in the mean intrinsic motivation between providing structuresupport together with autonomy support (p < .005) and providing structuresupport in the absence of autonomy support (p < .001). As shown in Table 2.2,the intrinsic motivation of students was highest in the condition with both autonomy support and structure support (condition 1) (M = 5.83, SD = 1.11),and lowest in the condition with neither autonomy support nor structure sup-port (condition 4) (M = 3.51, SD = 1.42). These findings showed that the exis-tence of an autonomy-supportive condition with structure support had apositive influence on intrinsic motivation. When both autonomy support andstructure support were absent, low intrinsic motivation was evident.

2.3.4 Effects of Digital Learning Conditions on Learning Outcomes (Hypothesis 3)

Next, we analyzed the effects of the digital learning conditions on learningoutcomes. A general linear model univariate analysis of variance was con-ducted with learning outcomes as the dependent variable and autonomy sup-port (with or without) and structure support (with or without) as theindependent variables. The main effect of structure support on learning out-comes was significant (F(1, 316) = 191.06, p < .001, partial η² = .38). The maineffect of autonomy support on learning outcomes was not significant (F(1, 316)= 1.25, p = .264, partial η² = .00). The interaction between autonomy supportand structure support on learning outcomes was significant (F(1, 316) = 16.05,p < .001, partial η² = .05), which meant that the effect of structure support onlearning outcomes was different in conditions with autonomy support fromthat in conditions without autonomy support. Simple effects analysis showedsignificant differences in the mean learning outcome between providing struc-ture support when there was autonomy support (p < .001) and providing struc-ture support in the absence of autonomy support (p < .001). Table 2.2 showsthat the condition with both autonomy support and structure support (condi-tion 1) produced the best learning outcomes (M = 5.59, SD = 1.35). Studentsscored slightly lower when they were provided with structure support but no



autonomy support (condition 2) (M = 4.70, SD = 1.52.). In the condition withneither autonomy support nor structure support (condition 4), even lowerscores were found (M = 3.00, SD = 1.66). The lowest learning outcomes wereachieved in the condition in which autonomy support was given without struc-ture support (condition 3) (M = 2.50, SD = 1.64).

Table 2.2

Mean Scores (and Standard Deviations) for all Measures as a Function of

Digital Learning Condition

Learning Learning Learning Learning condition 1 condition 2 condition 3 condition 4

+ autonomy - autonomy + autonomy - autonomysupport support support support

+ structure + structure - structure - structuresupport support support support

Perceived autonomy 5.78 (1.10) 2.82 (1.25) 5.79 (1.04) 2.60 (1.05)

Perceived competence 5.50 (1.14) 5.59 (1.06) 3.81 (1.19) 3.49 (1.21)

Intrinsic motivation 5.83 (1.11) 5.20 (1.26) 5.20 (1.14) 3.51 (1.42)

Learning outcomes 5.59 (1.35) 4.70 (1.52) 2.50 (1.64) 3.00 (1.66)

2.3.5 Perceived Autonomy and Perceived Competence Increase Intrinsic Motivation and Learning Outcomes

The relative effects of perceived autonomy and perceived competence on in-trinsic motivation and learning outcomes were examined by hierarchical re-gression analyses using the enter method. The results are displayed in Table2.3, which shows that perceived competence was the strongest predictor oflearning outcomes (β =.48) and intrinsic motivation (β =.50). In addition, per-ceived autonomy had a significant effect on intrinsic motivation (b =.44) butnot on learning outcomes (β =.02).

In addition, the effect of intrinsic motivation on learning outcomes was ex-amined by regression analyses using the enter method. Results show that in-trinsic motivation was a good predictor of learning outcomes (t(318) = 5.80, p< .001, β =.31). Because intrinsic motivation significantly predicted learningoutcomes and structure support was significantly related to both enhanced intrinsic motivation and learning outcomes, an additional mediation analysiswas performed that treated the relationship between structure support andlearning outcomes mediated by intrinsic motivation. This was done by theSobel Test (1982) that assessed whether a mediation effect of intrinsic motiva-



tion is significant. This showed that the indirect path was significant and thatintrinsic motivation was a significant mediator between structure support andlearning outcomes (β < .05). There was partial mediation; intrinsic motivationaccounts for some, but not all, of the relationship between structure supportand learning outcomes. The standardized regression coefficient between struc-ture support and learning outcomes (β =.60, p < .001) decreased when wecontrolled for intrinsic motivation (β =.55, p < .001).

Table 2.3

Results of Hierarchical Regression Analyses Predicting Intrinsic Motivation and Learning

Outcomes by Perceived Competence and Perceived Autonomy

Intrinsic motivation Learning outcomes

β SE B t β SE B t

Step 1

Perceived competence .54*** .05 11.40 .48*** .07 9.74

ΔR² .29*** .23***

Step 2

Perceived competence .50*** .04 12.38 .48*** .07 9.66

Perceived autonomy .44*** .03 10.69 .02 .05 .46

ΔR² .19*** .00

Note. ***p < .001.

2.4 DiscussionThe aim of the study was to explore the ways in which digital learning tasksfeaturing problem-based learning (PBL) in a hypermedia environment con-tribute to the level of intrinsic motivation and learning outcomes in students.Although digital PBL tasks are used in classroom teaching with increasing fre-quency, there is a lack of research informing the optimization of structure sup-port and autonomy support in such tasks.

The first hypothesis was confirmed in its entirety. Specifically, students pro-vided with autonomy support experienced a greater sense of autonomy, andstudents provided with structure support experienced a greater sense of compe-tence. Results suggest that perceived autonomy increases when a digital learn-ing task supports autonomy by offering choices, a rationale for a task, andnon-directive language. Further, an autonomy-supportive digital learning taskhelps to fulfill the need for autonomy because students can experience freedomin the activity (Reeve et al., 2007). A digital learning task that provides structuresupport through clear expectations, guidance, and procedures contributes togreater perceived competence. This finding is consistent with previous findings



that the provision of structure support makes a learning task consistent and pre-dictable and, in turn, helps students to feel more competent (Connell, 1990;Grolnick & Ryan, 1989; Skinner & Belmont, 1993; Tucker et al., 2002).

The second hypothesis was that a digital learning task characterized byboth autonomy support and structure support would have a positive effect onintrinsic motivation. This hypothesis was also supported by the results, thoughthe occurrence of both dimensions was not necessary for promoting intrinsicmotivation. The results showed that even a single dimension (autonomy sup-port or structure support) was sufficient to foster intrinsic motivation. The posi-tive interaction suggests, however, that when both autonomy support andstructure support are present they are mutually supportive and result in highmotivation. If both are absent, however, low intrinsic motivation results. Thisfinding concurs with previous research suggesting that environments that in-hibit the fulfillment of these needs yield fewer optimal forms of motivation(Deci & Ryan, 2008).

The third hypothesis was that a digital learning task characterized by bothautonomy support and structure support would have a positive effect on learn-ing outcomes. This hypothesis was also confirmed. The positive interaction in-dicated that the combination of autonomy support and structure support leadsto better learning outcomes. Specifically, structure support was associated withbetter learning outcomes in conditions that also provided autonomy support.A main effect of structure support on learning outcomes was also found, butthere was no main effect of autonomy support on learning outcomes. In otherwords, providing autonomy support had no impact on learning outcomes. Itwas only when it was combined with structure support that autonomy supportresulted in positive outcomes.

A possible explanation for this finding is that when students work on a dig-ital learning task with autonomy support, but not structure support, they maybe too easily distracted from the purpose of the assignment. Students couldbe confused by the options offered when there is no corresponding guidanceon the different steps they should take to reach a solution. Such confusioncould lead students to lose sight of their objectives and become less focusedon the goals of the task, which, in turn, could negatively affect their learningoutcomes. These results suggest that structure support facilitates metacogni-tive skills or self-regulated learning. Metacognitive skills comprise the control,monitoring, time-management, and self-regulation required by learning activi-ties and problem-solving (Brown, 1978).

In accordance with the research on metacognition, structure support canbe seen as a supportive tool that students use when they think through theirplanning and strategy to complete the task. Bannert (2004) shows that stu-

dents with this type of metacognitive support tend to achieve better learningoutcomes. Even adult users of web-based contexts indicate that they benefitfrom guided tools, such as a checklist, a help function, or an overview ofphases and steps (Stoof, Martens, & van Merriënboer, 2007).

In this study, we can see that perceived autonomy and perceived compe-tence in digital learning are good predictors of intrinsic motivation. This find-ing is in accordance with the research on SDT, which shows that perceivedautonomy and perceived competence increase intrinsic motivation (Deci &Ryan, 2000, 2008). In contrast, learning outcomes appear to be affected onlyby perceived competence. Perceived autonomy by itself appears to have noadditional effect on learning outcomes. The observation that perceived com-petence strongly predicted learning outcomes is in agreement with previousresearch that showed how classroom achievement is affected by students’ be-liefs about themselves and their academic competence (Deci, Vallerand, Pel-letier, & Ryan, 1991; Pintrich & Schunk, 2002). In addition, the direct effect ofintrinsic motivation on learning outcome suggests that improved motivationenhances learning outcomes. The finding that student learning and educationbenefits from increased intrinsic motivation is in line with previous researchbased on the SDT (Ryan & Deci, 2000a; Vansteenkiste et al., 2004).

2.4.1 Limitations and Future ResearchThe present study, using an experimental design, shows significant evidencethat the hypotheses were almost entirely confirmed. Nonetheless, several limi-tations of the study should be acknowledged.

The research consisted of a relatively short task that students completed inapproximately an hour and a half. In future research, the effects of autonomysupport and structure support on student motivation and learning perform-ance should be examined in digital tasks of varied duration that require stu-dents to spend more time completing them.

Because the student presentations could only be scored with eight pointsacross four different criteria, there was limited variation in the learning out-come measure. Despite the limited variation, however, the effects of autonomysupport and structure support on learning performance were still significant.

Another limitation was that no pre- and post- measurements were adminis-tered. Instead, to overcome the fact that students were unlikely to have thesame levels of prior knowledge and motivation, a large and representativesample was used. To control for possible interactions of the schools and theconditions on motivational and learning outcomes, students from all the appropriate classrooms within a school were randomly selected and assignedto one of the four experimental conditions. In follow-up work, pre- and post-



measurements should be included to control for the different levels of priorknowledge and motivation of students.

In addition, whereas the impact of autonomy support and structure sup-port was examined, the impact of specific aspects of autonomy support andstructure support (e.g. providing a rationale for a task that explains task rele-vance or using a roadmap) on motivation and learning performance has notbeen studied. Follow-up work should investigate the contributions of specificaspects of autonomy support and structure support to clarify the mechanismsunderlying the relationships found in this study. This is also the case formetacognitive skills and self-regulated learning. In particular, the results sug-gest that structure support facilitates self-regulated learning. Students underthe structured conditions were told the time limit for the task but those underthe non-structured conditions were not. It is possible that the metacognitiveskills used in this task related mainly to time management and that time man-agement explained the effect to a greater extent than other metacognitiveskills. Unfortunately, the investigation of this possibility fell beyond the scopeof this study because it would have entailed the use of more than four experi-mental conditions. Thus, future research should take into account the effect ofspecific aspects of metacognitive skills under the structured condition to clarifythe exact ways in which metacognitive skills have an effect on the motivationand learning performance of students.

The ultimate aim of the research was to examine the factors that increasethe intrinsic motivation of students. Extrinsic motivation was excluded by giv-ing students a task that was part of their regular curriculum and resulted in noassociated score, grade, or reward upon completion. Despite these efforts, theexistence of extrinsic motivation cannot be ruled out entirely. In follow-up re-search, a subscale should be included to measure extrinsic motivation to en-able comparison of the levels of extrinsic motivation and intrinsic motivationthat students experience.

It would also be interesting to investigate the ways in which the teachercan contribute to a more autonomy-supportive and structured digital learningenvironment. In a follow-up study, we intend to take into consideration therole of the teacher as a designer of digital learning tasks.

2.4.2 ConclusionIn summary, the results of the present study show that when autonomy supportand structure support are present, digital learning tasks featuring problem-based learning in a hypermedia environment lead to a positive effect on intrin-sic motivation and learning outcomes of students. Because structure supportensures that the digital learning task is consistent and clear, students are better



able to make appropriate choices. Although providing structure support has apositive effect on both intrinsic motivation and learning achievement, this effect was not observed for autonomy support. In the study, autonomy supportwithout structure support produced the least effective learning outcomes. Thefact that structure support matters in a digital learning task is not surprising.Because structure support encourages metacognitive reflection and leads tomore effective learning performance (Bannert, 2004) it can be seen as a toolthat students leverage in their learning process.

The combined impact of autonomy support and structure support has notbeen previously studied in the context of digital learning. In this study, wefound that both dimensions affected student motivation and learning out-comes, similarly to previous findings on learning in the classroom (Jang et al.,2010; Sierens et al., 2009). The findings of this study will not only help teachersto use digital learning tasks more effectively to improve the learning processbut will also contribute to the discussion on SDT.

With regard to the implications of the present findings for educationalpractice, we believe that teachers will be able to use the results of this study todesign better digital PBL tasks in a hypermedia environment. Digital learningtasks in the classroom often offer a lot of information but the lack of structuresupport tends to increase the risk of information overload and cause studentsto lose sight of task objectives. This study suggests that the combination of autonomy support and structure support contributes to the increased motiva-tion and learning performance of students in the process of digital learning.



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2 This chapter is submitted for publication as: Van Loon, A.-M., Ros, A., & Martens, R. (2013).Designing digital problem based learning tasks that motivate students.

This chapter is presented as: Van Loon, A.-M. (2012, November). Designing Digital Problem BasedLearning Tasks that Motivate Students at European Association for Practitioner Research on Improving Learning Conference, Jyväskylä, Finland.

Chapter 3Designing Digital ProblemBased Learning Tasks that Motivate Students2

AbstractThis study examines whether teachers are able to apply the principles of auto -nomy support and structure support in designing digital problem based learning(PBL) tasks. We examine whether these tasks are more autonomy- and structure-supportive and whether primary and secondary school students experiencegreater autonomy, competence, and motivation in these tasks. Participants were184 fifth-, sixth-, seventh- and eighth- grade students and 20 teachers. The resultsshowed that teachers indicated that their digital PBL tasks were more autonomy-and structure-supportive after completing the training. Furthermore, students’perceived autonomy, perceived competence, and intrinsic motivation in the digitalPBL tasks were higher after teachers completed the training. In addition, there wasan interaction effect between training and school type on perceived autonomy,perceived competence, and intrinsic motivation. Compared to primary school students, secondary school students evidenced a greater increase in perceived autonomy, perceived competence, and intrinsic motivation on the PBL tasks.

Keywords: Digital problem based learning task; Self-determination theory;Structure support; Autonomy support; Intrinsic motivation.

3.1 IntroductionComputer use in primary and secondary education has primarily involved drillsand practice for reading and mathematics skill development and basic wordprocessing (Becker, 1991; Maddux, Johnson, & Willis, 1992). The use of in-structional computer-supported learning environments based on constructivistprinciples in a hypermedia environment is less common in the classroom(Niederhauser & Stoddart, 2001). Computer-supported learning environmentsbased on an instructional constructivist approach provide students with accessto a variety of open-ended applications that help them construct more com-plex understandings (Savery & Duffy, 1995). An example of such environmentis a digital problem based learning (PBL) task (Liu & Bera, 2005). In these tasks,students have opportunities to apply their content knowledge and skills whileworking on contextualized problems (Dunlap, 2005). The learner acts as an ac-tive seeker of information who revises and updates his or her knowledgethrough the process of gathering new information rather than providing thesingle correct answer to a question (Niederhauser & Stoddart, 2001). Becausehypermedia provide rich information resources through various forms of media(e.g., texts, images, and video sequences), multiple related problems can bepresented in one environment (Hoffman & Richie, 1997). Digital PBL tasks offerstudents autonomy and have a positive effect on students’ motivation andlearning outcomes (Liu, Horton, Olmanson, & Toprac, 2011; Mayer, 2011).

However, it seems that many teachers do not have the expertise to con-struct effective PBL tasks. Digital PBL tasks in the classroom often provide sucha large amount of information and autonomy that students experience infor-mation overload, do not make effective choices and become lost due to the in-formation that they receive (Azevedo & Witherspoon, 2009). PBL tasks areoften ill-structured, which places increased demands on learners, as indicatedby superficial information processing (Liu & Bera, 2005; Narciss & Körndle,1998), relatively high dropout rates and a diminished ability to focus duringlearning (Clark, Yates, Early, & Mouton, 2010; Mayer, 2011).

To avoid excessive associative distraction, digital PBL tasks must containnot only autonomy support but also structure support (Van Loon, Ros, &Martens, 2012). The previous research of Van Loon et al. (2012) shows that adigital PBL task that combined autonomy support and structure support had apositive effect on students’ intrinsic motivation and learning outcomes.

Autonomy support ensures that students feel control over their actions(Reeve, Nix, & Hamm, 2003) and structure support makes the learning environ-ment less chaotic and more consistent and predictable for students (Guay,Ratelle, & Chanal, 2008). These two principles are derived from the Self-Deter-mination Theory (SDT), which is an influential theory regarding motivation



(Deci & Ryan, 2000; 2008). By specifying the contextual environments that fos-ter optimal learning, SDT is a relevant framework for the study of favourableconditions for digital learning. According to SDT, intrinsic motivation and deeplearning occur when a learning environment facilitates a student’s perceivedautonomy, perceived competence, and perceived relatedness (Deci & Ryan,2008). A digital PBL task can facilitate perceived autonomy and perceivedcompetence through autonomy support by encouraging students to makechoices and follow their own learning path and through the necessary structuresupport by providing the guidance that they need. Research studies on lear n -ing in the classroom show that offering autonomy support and structure sup-port together positively affects student motivation (Jang, Reeve, & Deci,2010), including in digital learning with PBL tasks (Van Loon et al., 2012).

To realize motivated students and a good learning result, both autonomyand structure support are important in digital PBL tasks (Van Loon et al., 2012).However, the question is whether teachers can bring these principles into prac-tice when they are designing digital PBL tasks. This is not simple becauseteachers often believe that autonomy support and structure support are twoopposite principles. According to Reeve, Deci, and Ryan (2004a), autonomysupport and structure support are separate dimensions of a learning environ-ment that motivates students. In fact, the opposite of an autonomy-supportiveenvironment is a controlling environment (Black & Deci, 2000; Koestner, Ryan,Bernieri, & Holt, 1984). A controlling environment is characterized by extrinsicincentives and pressuring language, which tend to interfere with student moti-vation (Reeve, Jang, Carrell, Jeon, & Barch, 2004b).

The current study builds on Van Loon et al. (2012) finding that when auto -nomy support and structure support are present, digital PBL tasks in a hyper-media environment have a positive effect on students’ intrinsic motivation andlearning outcomes. The present study examines whether teachers can betrained to apply the principles of autonomy support and structure support intheir digital PBL tasks and whether students in primary and secondary educa-tion experience greater autonomy, competence, and motivation while workingon these tasks. First, we will discuss the SDT-derived design principles of au-tonomy support and structure support.

3.1.1 The Importance of Autonomy Support and Structure SupportIn a digital PBL task with autonomy support, external pressure is minimal (Deci& Ryan, 2000; 2008) and choices are offered (Zuckerman, Porac, Lathin, Smith,& Deci, 1978). The ability to choose among several options makes studentsfeel greater control over their actions (Cordova & Lepper, 1996; Reeve et al.,2003). Another aspect of autonomy support is the provision of the rationale for



a task. If students receive a meaningful explanation of why a specific learningtask is useful, they are more likely to internalize the personal relevance of thelearning task and become motivated to learn (Deci, Eghrari, Patrick, & Leone,1994; Reeve, Jang, Hardre, & Omura, 2002). Further, it is important that thelanguage in the learning tasks is characterized by non-directive language thatencourages students to take initiative rather than controlling language (Deci,Ryan, & Williams, 1996; Reeve et al., 2004a).

Research shows that environments that are autonomy-supportive help tofulfill the need for autonomy (Reeve, Ryan, Deci, & Jang, 2007) and fostergreater intrinsic motivation in students (Reeve & Jang, 2006). Such environ-ments stimulate students’ curiosity and encourage them to confront challenges(Flink, Boggiano, & Barrett, 1990; Ryan & Grolnick, 1986). However, PBL taskswith only autonomy support may create associative distraction and overwhelmstudents with an excessive number of choices. As a consequence, learners onlyconstruct shallow associative cognitive networks that have no intellectual merit(Okan, 2003; Salomon & Almog, 1998). Thus, in addition to autonomy support,structure support plays a key role in an optimal digital PBL task (Guay et al.,2008). Structure makes the learning environment less chaotic and more consis-tent and predictable for students. Moreover, from a motivational point of view,structure increases students’ perceived competence (Grolnick & Ryan, 1989;Skinner & Belmont, 1993; Tucker et al., 2002).

Structure support in digital PBL tasks involves providing students with cleargoals and expectations and explicitly describing the consequences of achieving(or not achieving) these goals (Connell, 1990; Connell & Wellborn, 1991; Reeveet al., 2004a; Skinner & Belmont, 1993). Structure also involves providing stu-dents with help, support, and guidance to successfully carry out a task (Connell,1990; Reeve et al., 2004a; Skinner & Belmont, 1993). Finally, structure requiresproviding students with clear procedures to follow (Reeve et al., 2004a).

Structure is associated with positive learning outcomes as well as greaterlearner engagement (Skinner & Belmont, 1993; Tucker et al., 2002), lower passivity toward learning, and less school-avoidant behavior (Patrick, Turner,Meyer, & Midgley, 2003).

3.1.2 Training TeachersAlthough research shows that both autonomy support and structure support indigital PBL tasks are important for motivating students, it is questionablewhether teachers are able to apply these principles in digital PBL tasks. This application requires didactic teacher skills. Research shows that simply installing computers in schools and the presence of computers in the class-room do not change the didactic teaching methods of teachers (Stoddart &



Niederhauser, 1993; Van Dusen & Worthen, 1992; 1995). Therefore, teachersshould be trained in designing digital PBL tasks with the principles of auto -nomy support and structure support. Shashaani’s (1997) research demonstratethat training can positively impact teachers’ computer skills.

In addition, it is difficult to change teacher behavior through training. Muchof the research on teachers’ professional learning activities is often character-ized as ineffective (Hanushek, 2005). Teacher professional development hasbeen disappointing because sustainable training effects and educational im-provement require changes in teachers’ beliefs and practices (Clarke &Hollingsworth, 2002; Opfer & Pedder, 2011). Therefore, teacher learning mustbe conceptualized as a complex system rather than as an event (Clarke &Collins, 2007; Collins & Clarke, 2008).

Research on the professional development of teachers shows that tochange teachers’ behavior, certain principles should be taken into account.Firstly, teachers require time to develop, absorb, discuss, and practice newknowledge (Garet, Porter, Desimone, Birman, & Yoon, 2001). Thus, profes-sional development that involves a significant number of contact hours over along period of time is typically associated with effectiveness (Guskey, 2000).Secondly, teachers’ learning should be situated and focused on authentic activ-ities in the classroom (Garet et al., 2001). Research shows that teachers learnmost effectively when the training is school-based and integrated into theirdaily work (Garet et al., 2001; Hawley & Valli, 1999). And thirdly, professionaldevelopment has been shown to be more effective when teachers from thesame school or year level participate collectively (Desimone, Porter, Garet,Yoon, & Birman, 2002; Garet et al., 2001).

3.1.3 The Present Study and HypothesesThis study examines whether teachers can be trained to apply the principles ofautonomy support and structure support in their digital PBL tasks. The challengeis training teachers such that they indicate increased skill in creating digital PBLtasks and that their tasks are more autonomy- and structure-supportive. An addi-tional goal is to increase primary and secondary education students’ autonomy,competence, and motivation in these tasks. We specifically examine both primaryand secondary education students (in particular, middle school students) to deter-mine whether the teacher training has the same effect on students of secondaryeducation as students of primary education. Students’ motivation declines duringtheir school career, beginning in primary education and continuing until theycomplete high school, with notable losses during the transition to middle school(Wigfield, Eccles, Schiefele, Roeser, & Davis-Kean, 2006). Thus, it is especially important for secondary school teachers to construct motivating learning tasks.



This leads to the following hypotheses: The first hypothesis is that after thecompletion of training, teachers will indicate that they are more skilled in cre-ating digital PBL tasks and that their digital PBL tasks are more autonomy-sup-portive and structure-supportive than those prior to training.

The second hypothesis is that primary and secondary school studentswill experience greater autonomy and competence in digital PBL tasks that aredesigned by teachers after training than prior to training. In addition, we inves-tigate potential differences between primary education students and second-ary education students.

The third hypothesis is that primary and secondary school students will experience greater intrinsic motivation in digital PBL tasks that are designedby teachers after training than prior to training. In addition, we investigate potential differences between students of primary education and students ofsecondary education.

3.2 Methodology3.2.1 DesignThe research is based on a one-group pre-test–post-test design. To test hypo -thesis 1, teachers were asked to rate their skills in creating digital PBL tasks withautonomy support and structure support before and after the training. In addi-tion, teachers were asked to assess the degree of autonomy support and struc-ture support in digital PBL tasks that they had designed before and after thetraining.

To test hypotheses 2 and 3, students were asked to complete a question-naire about their perceived autonomy, competence, and motivation in a digitalPBL task that their teacher had created before and after the training.

3.2.2 ParticipantsThe study was conducted in the Netherlands. Participants were 184 fifth-,sixth-, seventh- and eighth- grade students of 20 classrooms. There were 121fifth- and sixth- grade students from four primary schools (10 classrooms) and63 seventh- and eighth- grade students from one secondary school (middleschool, 10 classrooms). The mean age of the students at the outset of thestudy was 12.6 years (SD = 1.11, range = 10.6 - 16.3 years). A total of 86 boysand 98 girls participated. The schools were typical schools that did not deviatefrom other schools in size, population or learning outcomes. The averagelearning outcomes of the students from the participating schools were at thesame level as those of their peers at other schools throughout the country(Dutch Inspectorate of education, 2011). The teacher sample contained 20teachers (10 primary and 10 secondary school teachers). A total of 11 female



and 9 male teachers participated. We selected the teachers at the participat-ing schools based on the following two criteria: 1) the teachers had affinitywith creating digital PBL tasks and 2) they taught fifth-, sixth-, seventh- andeighth- grade students. Participation was on a voluntary basis.

3.2.3 TrainingTo train teachers in applying the principles of autonomy support and structuresupport in their digital PBL tasks, an experienced external trainer was em-ployed. The training was based on the three principles described in the intro-duction to this article. The first principle, i.e., teachers require time to developand practice new knowledge, was met by the significant number of contacthours involved in the training. The training lasted two months and consisted ofthree team meetings.

During the first training meeting, the trainer gave a presentation that ex-plained the two concepts of autonomy support and structure support in digitalPBL tasks. The empirical support for the assertion that students benefit when adigital PBL task supports their needs for autonomy and competence was shownto the teachers. After this introduction, more detailed information and examplesof autonomy support and structure support in digital tasks were provided.

Following this meeting, teachers were required to create a plan for imple-menting autonomy support and structure support in their digital PBL tasks. Inthe second and third meetings, which occurred two weeks and six weeks afterthe first meeting, respectively, teachers implemented both autonomy supportand structure support in their digital PBL tasks. These tasks were relevant tothe lessons in the classroom and could be used in the lessons. Thus, the sec-ond principle, i.e., teachers’ learning is situated and focuses on authentic activ-ities in the classroom, was met.

During each meeting, teachers were not only coached on strengths andareas for improvement in their digital PBL tasks, but were also provided techni-cal support in designing the tasks. After the last meeting, they completed theirnew digital PBL task and offered it to the students in their class. Becauseteachers from one school learned together, the third principle, i.e., teachersfrom the same school participate collectively, was also realized.

3.2.4 ProcedureAt two moments, before the training and after the training, teachers wereasked to complete a questionnaire regarding the extent to which their digitalPBL tasks consisted of autonomy support and structure support. In addition,they were asked to complete a questionnaire regarding their skill in designingdigital PBL tasks with autonomy support and structure support.



Students were asked to complete a questionnaire regarding their per-ceived autonomy, perceived competence, and intrinsic motivation at two timepoints. The first time point coincided with a digital PBL task that their teachersdesigned before the training, and the second time point coincided with theirteachers’ post-training digital PBL task.

3.2.5 Measures3.2.5.1 Perceived autonomy, perceived competence, and

intrinsic motivationTo measure students’ intrinsic motivation, we used the Intrinsic Motivation Inventory (IMI), which was originally developed by Ryan (1982). The IMI is astructured written questionnaire, and its reliability and validity have been con-firmed by McAuley, Duncan, and Tammen (1987). The subscale “interest / en-joyment” of the IMI contains seven items that measure intrinsic motivation(e.g., “I enjoyed doing this task very much” and “This task was fun to do”). Theperceived degrees of competence and autonomy were measured by questionsbased on the IMI subscales of “perceived competence”, which consists of sixitems (e.g., “I am satisfied with my performance on this task” and “I was prettyskilled at this task”), and “perceived freedom of choice”, which consists ofseven items (e.g., “I believe I had some choice about doing this task” and “Ifelt like it was not my own choice to do this task”, which was reverse coded).Each item is presented in the form of a statement and the respondent indi-cates his or her degree of agreement or disagreement on a 7-point Likert scale(with a score of 1 indicating “totally disagree” and a score of 7 indicating “totally agree”). In the current sample, the reliability was high for all threescales, intrinsic motivation (α = .91), perceived autonomy (α = .82), and perceived competence (α = .83).

3.2.5.2 Teacher report: autonomy support and structure supportTeachers were asked to assess their digital PBL task with respect to the two dimensions of autonomy support and structure support using a rating sheet. Therating sheet features two clusters of items to assess autonomy support and structure support. Each item is scored using a 3-point Likert scale (with a score of 0indicating “not present” and a score of 2 indicating “totally present”). The itemswere taken and slightly modified from an existing questionnaire, the Teacher asSocial Context Questionnaire (Belmont, Skinner, Wellborn & Connell, 1988).

The teachers scored the following three autonomy-supportive aspects intheir digital PBL task: offering choices, providing a rationale and avoiding theuse of controlling language. Offering choices in the digital PBL task includeschoice about the content of the task, choice about the online sources that the



student could search for information, and choice about information processing.Providing a rationale involves an explanation about the relevance of the task.In the digital PBL task, non-directive language was used (e.g., “You can makeuse of…,” and “You can do this task”). The reliability of the autonomy supportscale was sufficient (α = .76).

Teachers scored the following three structure-supportive aspects in theirdigital PBL task: providing clear expectations for students, guidance for stu-dents to successfully carry out a task, and clear procedures to follow. Providingclear expectations in the digital PBL task includes clarity regarding the way inwhich the completed product would be assessed. Guidance for students tosuccessfully carry out a task involves providing students with a roadmap of thestages required to successfully complete the task. Finally, clear procedures in-cludes how long the students were allowed to work on the task and what theycould do when they completed their work. The reliability was sufficient for thestructure support scale (α= .79).

3.2.5.3 Teacher report: skill in creating digital PBL tasksTeachers were asked to assess their skills in creating digital PBL tasks using awritten questionnaire. Three items of this questionnaire measure skills in creatingdigital PBL tasks (e.g., “I think I’m skilled in designing digital PBL tasks”). Eachitem is presented in the form of a statement and the respondent indicates his orher degree of agreement or disagreement on a 5-point Likert scale (with a scoreof 1 indicating “totally disagree” and a score of 5 indicating “totally agree”). Inthe current sample, the reliability was sufficient for this scale (α = .75).

3.2.6 Data AnalysesThe first hypothesis, i.e., teachers will indicate that they are more skilled in creating digital PBL tasks and that their digital PBL tasks are more autonomy- and structure-supportive after completing the training, was tested by depend-ent t -tests.

To test hypotheses 2 and 3, i.e., students will experience greater autonomy,competence, and intrinsic motivation in digital PBL tasks that are designed byteachers after the training than before the training, three sets of multilevel linearmodels were constructed. Because the data have a two level- hierarchical struc-ture (students at level 1 and students nested in classes at level 2), we used hierarchical linear modeling [HLM]. This method is necessary because using atraditional single- level statistical method for multilevel data can lead to prob-lems such as violations of assumptions of independence, aggregation bias, heterogeneity of regression and spurious significant results (Hox, 2002).

Three sets of multilevel regression analyses were conducted to predict



students’ perceived autonomy, perceived competence, and motivation. Thefirst model was the base model with no predictors. This model examinedwhether the classes (second level) contributed to the variance of the depen -dent variable. In the second model, we added the predictor training as afixed effect. In the third model, we allowed the effect of the predictor training as a fixed effect and as a random effect (to examine whether the effect of training varied by class). To examine the difference between primaryand secondary school students, in the fourth model, the predictors training,school type and the interaction between training and school type wereadded as fixed effects.

3.3 Results3.3.1 Teachers’ Perceptions (Hypothesis 1)It was expected that teachers would report increased skill in creating digitalPBL tasks after completing the training in applying autonomy support andstructure support in digital PBL tasks. Furthermore, we expected teachers toindicate that their digital PBL tasks were more autonomy- and structure-sup-portive after the training than before the training (1). Table 3.1 reports the descriptive statistics, means and standard deviations of teachers’ reported skillin creating digital PBL tasks and degree of autonomy support and structuresupport in digital PBL tasks before and after the training.

Table 3.1

Descriptive Statistics for Teachers’ Perceived Skills, Perceived Autonomy Support and

Perceived Structure Support in Digital PBL Tasks Before and After Completing the Training

Before training After training

M SD M SD

Perceived Skill 2.92 0.85 3.86 0.65

Perceived Autonomy Support 1.70 1.22 4.05 0.89

Perceived Structure Support 2.75 1.37 4.10 0.97

The first part of the first hypothesis, i.e., teachers will indicate that they aremore skilled in creating digital PBL tasks after completing the training, was ex-amined by a paired samples t-test with the questionnaire results regardingteachers’ perceived skill in creating digital PBL tasks. The results showed thatteachers indicated that they were more skilled in creating digital PBL tasksafter completing the training than before the training (t(19) = 3.41, p < .05).

The second part of the first hypothesis, i.e., teachers will indicate that theirdigital PBL tasks are more autonomy- and structure-supportive after complet-



ing the training than before the training, was examined by two paired samplest-tests with the questionnaire results regarding teachers’ perceived autonomysupport and structure support in tasks before and after the training. The teach-ers indicated that their tasks were more autonomy-supportive (t(19) = 8.29, p < .001) and structure-supportive after the training than before the training(t(19) = 5.31, p < .001).

In conclusion, the results showed that the training significantly affected thedegree of autonomy support and structure support in digital PBL tasks, accord-ing to teachers. Teachers assessed the degree of structure support within digitalPBL tasks as higher than the degree of autonomy support. Teachers reported in-creased skill in creating digital PBL tasks after completing the training.

3.3.2 Students’ Perceived Autonomy and Perceived Competence (Hypothesis 2)

It was expected that students would experience greater autonomy and com-petence in digital PBL tasks that were designed by teachers after the trainingthan before the training. Potential differences between students of primary education and students of secondary education were examined (2). Table 3.2reports the descriptive statistics, means and standard deviations of students’perceived autonomy and perceived competence in digital PBL tasks that weredesigned by teachers before and after the training for all students, primaryschool students (fifth- and sixth- grade), and secondary school students (seventh- and eighth- grade).

Table 3.2

Descriptive Statistics for Students’ Perceived Autonomy and Competence in Digital PBL

Tasks Before and After Teachers Completed the Training

Perceived Autonomy Perceived Competence

Before Training After Training Before Training After Training

M SD M SD M SD M SD

All

students 4.73 0.95 5.23 1.07 5.09 0.88 5.54 1.02

Primary school

students 5.06 0.83 5.29 0.98 5.25 0.81 5.47 1.08

Secondary school

students 4.09 0.81 5.11 1.24 4.77 0.93 5.70 0.90

To test hypothesis 2, two sets of multilevel linear models were constructedwith the students’ perceived autonomy and perceived competence as the



dependent variables and the effect of teacher training as the independent variable. Because the data has a two level- hierarchical structure (students atlevel 1 and students nested in classes at level 2), we employed hierarchical linear modeling [HLM].

3.3.2.1 Perceived autonomyTable 3.3 shows the estimates for the models of the predictors of perceivedautonomy. The first model was the base model with no predictors. It examinedwhether the classes (second level) contributed to the variance of the depend-ent variable perceived autonomy. The class significantly predicted the per-ceived autonomy of students. Interclass correlation coefficients indicated thatbetween-class differences accounted for 11% of the total variance in students’perceived autonomy. Thus, the specific class and specific teacher who de-signed the task predicted the perceived autonomy of students.

In the second model, we added the predictor training as a fixed effect. Theresults showed that the training significantly affected the perceived autonomyof students (F(1, 347.84) = 25.18, p < .001). The class also significantly pre-dicted students’ perceived autonomy.

In the third model, we allowed the effect of the predictor training as afixed effect and as a random effect (to examine whether the effect of trainingvaried by class). The results showed that the training significantly affected theperceived autonomy of students (F(1, 14.70) = 22.97, p < .001). The class alsosignificantly predicted students’ perceived autonomy. In addition, the slopedid not vary across students, and the slope and intercept did not significantlycovary. Thus, the relationship between training and autonomy did not vary between classes.

The change of the -2 Log Likelihood from model 1 to model 2 was signifi-cant (p < .01). The change of the -2 Log Likelihood from model 2 to model 3was not significant. Thus, model 2 provided the best fit to the data.

3.3.2.1.1 Difference between primary- and secondary school students To examine the potential difference between primary school students (fifth-and sixth- grade) and secondary school students (seventh- and eighth- grade),in the fourth model, the predictors training, school type and the interactionbetween training and school type were added as fixed effects. Training andclass were also added as random effects.

There was a significant interaction effect of training and school type on theperceived autonomy of students (F(1, 803.22) = 12.18, p < .01). This interac-tion was further investigated by conducting separate multilevel models on pri-mary school students and secondary school students. The models specified



were the same as model 4 but excluded the main effect and interaction terminvolving school type. These analyses showed that for primary school students,training significantly predicted the perceived autonomy (t(396.51) = 2.06, p < .05). Training also significantly predicted the perceived autonomy of secondary school students (t(5.12) = 5.15, p < .01). The increase in perceivedautonomy from the PBL tasks that were designed by teachers before the training to the PBL tasks after the training was greater for secondary schoolstudents than for primary school students. See Figure 3.1 for this interactioneffect.

Table 3.3

Multilevel Model Estimates for Models of the Predictors of Perceived Autonomy

Model 1 Model 2 Model 3 Model 4

Estimate SE Estimate SE Estimate SE Estimate SE

Fixed effects

Intercept 4.93*** 0.09 4.68*** 0.10 4.66*** 0.12 5.08*** 0.12

Training 0.50*** 0.10 0.53*** 0.11 ns

School type 0.99*** 0.19

Training x School type 0.77*** 0.22

Random effects

Intercept (Class) 0.12* 0.06 0.12* 0.06 0.19* 0.09 ns

Training ns ns

Covariance ns ns

-2*log likelihood 1055.090 1030.779 1029.010 1008.869

Note. *p < .05. **p < .01. ***p < .001.



Figure 3.1. Perceived autonomy in digital PBL tasks of primary school students (n = 121) and

secondary school students (n = 63) before and after teachers completed the training

3.3.2.2 Perceived competenceTable 3.4 shows the estimates for the models of the predictors of perceivedcompetence. The first model was the base model with no predictors. It examined whether the classes (second level) contributed to the variance ofthe dependent variable perceived competence. The class did not predict the perceived competence of students. Interclass correlation coefficients indicated that between-class differences accounted for 0.04% of the totalvariance in students’ perceived competence. Thus, the specific class and specific teacher who designed the task did not predict the perceived competence of students.

In the second model, we added the predictor training as a fixed effect. Theresults showed that the training significantly affected the perceived compe-tence of students (F(1, 348.73) = 22.66, p < .001).

In the third model, we allowed the effect of the predictor training as afixed effect and as a random effect (to examine whether the effect of trainingvaried by class). The results showed that the training significantly affected theperceived competence of students (F(1, 444.86) = 22.56, p < .001).

In addition, the relationship between training and students’ perceivedcompe tence showed no significant variance in intercepts across students, theslopes did not vary across students, and the slopes and intercepts did notsignificantly covary.



5,75

5,50

5,25

5,00

4,75

4,50

4,25

4,00

before training after training

School TypePrimary school studentsSecondary school students

Time

Per

ceiv

ed A

uto

nom

y

The change of the -2 Log Likelihood from model 1 to model 2 was signifi-cant (p < .01). The change of the -2 Log Likelihood from model 2 to model 3was not significant. Thus, model 2 provided the best fit to the data.

3.3.2.2.1 Difference between primary- and secondary school students To examine the potential difference between primary school students (fifth-and sixth- grade) and secondary school students (seventh- and eighth- grade),in the fourth model, the predictors training, school type and the interactionbetween training and school type were added as fixed effects. Training andclass were also added as random effects.

There was a significant interaction effect of training and school type on theperceived competence of students (F(1, 436.99) = 12.19, p < .01). This interac-tion was further investigated by conducting separate multilevel models on pri-mary school students and secondary school students. The models specifiedwere the same as model 4 but excluded the main effect and interaction terminvolving school type. These analyses showed that for primary school students,training did not significantly predict the perceived competence. For secondaryschool students, training significantly predicted the perceived competence(t(192.23) = 5.91, p < .001). The increase in perceived competence from thePBL tasks that were designed by teachers before the training to the PBL tasksafter the training was greater for secondary school students than for primaryschool students. See Figure 3.2 for this interaction effect.

Table 3.4

Multilevel Model Estimates for Models of the Predictors of Perceived Competence



Fixed effects

Intercept 5.31*** 0.07 5.08*** 0.08 5.06*** 0.10 5.25*** 0.10

Training 0.46*** 0.10 0.47*** 0.10 ns

School type 0.47* 0.17

Training x School type 0.72** 0.21

Random effects

Intercept (Class) 0.04 0.03 0.04 0.03 ns ns

Training ns ns

Covariance ns ns

-2*log likelihood 1025.178 1003.225 1003.449 992.651

Note. *p < .05. **p < .01. ***p < .001.



Figure 3.2. Perceived competence in digital PBL tasks of primary school students (n = 121)

and secondary school students (n = 63) before and after teachers completed the training

In conclusion, the results showed that the training significantly affected theperceived autonomy and perceived competence of students. The perceivedautonomy and perceived competence scores on the PBL tasks after the train-ing were higher than those before the training. The class significantly pre-dicted students’ perceived autonomy. Thus, the specific teacher who designedthe task predicted the perceived autonomy of students. This was not the casefor perceived competence.

The significant interaction effect between training and school type on students’ perceived autonomy and perceived competence indicated that theincrease in perceived autonomy and perceived competence for the PBL tasksthat were designed by teachers before and after the training was greater forsecondary school students than for primary school students.

3.3.3 Students’ Intrinsic Motivation (Hypothesis 3)It was expected that students would experience greater intrinsic motivation indigital PBL tasks that were designed by teachers after the training than beforethe training. Potential differences between students of primary education andstudents of secondary education were also examined (3). Table 3.5 reports thedescriptive statistics, means and standard deviations of intrinsic motivation ofstudents in digital PBL tasks that were designed by teachers before and after



5,75

5,50

5,25

5,00

4,75

4,50



Time

Per

ceiv

ed C

om

pet

ence

the training for all students, primary school students (fifth- and sixth- grade),and secondary school students (seventh- and eighth- grade).

Table 3.5

Descriptive Statistics for Students’ Perceived Intrinsic Motivation in Digital PBL Tasks Before

and After Teachers Completed the Training

Intrinsic motivation

Before Training After Training

M SD M SD

All students 4.95 1.30 5.48 1.27

Primary school students 5.41 1.14 5.66 1.20

Secondary school students 4.09 1.18 5.15 1.34

To test hypothesis 3, a set of multilevel linear models were constructed withthe perception of the students’ intrinsic motivation as the dependent variableand the effect of teacher training as the independent variable. Because thedata has a two level- hierarchical structure (students at level 1 and studentsnested in classes at level 2), we employed hierarchical linear modeling [HLM].

Table 3.6 shows the estimates for the models of the predictors of per-ceived intrinsic motivation. The first model was the base model with no predic-tors. It examined whether the classes (second level) contributed to thevariance of the dependent variable perceived intrinsic motivation. The classsignificantly predicted the perceived intrinsic motivation of students. Interclasscorrelation coefficients indicated that between-class differences accounted for16% of the total variance in students’ perceived intrinsic motivation. Thus, thespecific class and specific teacher who designed the task predicted the per-ceived intrinsic motivation of students.

In the second model, we added the predictor training as a fixed effect. Theresults showed that the training significantly affected the perceived intrinsicmotivation of students (F(1, 348.17) = 18.49, p < .001). The class also signifi-cantly predicted students’ perceived intrinsic motivation.

In the third model, we allowed the effect of the predictor training as afixed effect and as a random effect (to examine whether the effect of trainingvaried by class). The results showed that the training significantly affectedthe perceived intrinsic motivation of students (F(1, 530.87) = 18.53, p <.001). The class also significantly predicted the perceived intrinsic motivationof students. In addition, the slope did not vary across students and the slopeand intercept did not significantly covary. Thus, the relationship betweentraining and intrinsic motivation did not vary between classes.



The change of the -2 Log Likelihood from model 1 to model 2 was signifi-cant (p < .01). The change of the -2 Log Likelihood from model 2 to model 3was also significant (p < .05). Thus, model 3 provided the best fit to the data.

3.3.3.1 Difference between primary- and secondary school students To examine the difference between primary school students (fifth- and sixth-grade) and secondary school students (seventh- and eighth- grade), in thefourth model, the predictors training, school type and the interaction betweentraining and school type were added as fixed effects. Training and class werealso added as random effects.

There was a significant interaction effect of training and school type on theperceived intrinsic motivation of students (F(1, 380.47) = 9.86, p < .01). This in-teraction was further investigated by conducting separate multilevel models onprimary school students and secondary school students. The models specifiedwere the same as model 4 but excluded the main effect and interaction term in-volving school type. These analyses showed that for primary school students,training did not significantly predict the perceived intrinsic motivation. For sec-ondary school students, training significantly predicted the perceived intrinsicmotivation (t(122.66) = 4.92, p < .001). The increase in perceived intrinsic moti-vation from the PBL tasks that were designed by teachers before the training tothe PBL tasks after the training was greater for secondary school students thanfor primary school students. See Figure 3.3 for this interaction effect.

Table 3.6

Multilevel Model Estimates for Models of the Predictors of Perceived Motivation



Fixed effects

Intercept 5.12*** 0.14 4.85*** 0.15 4.82*** 0.18 5.41*** 0.16

Training 0.53*** 0.12 0.58*** 0.14 ns

School type 1.31* 0.24

Training x School type 0.81** 0.26

Random effects

Intercept (Class) 0.27* 0.12 0.28* 0.12 0.51* 0.23 ns

Training ns ns

Covariance ns ns

-2*log likelihood 1214.732 1196.718 1190.571 1171.286

Note. *p < .05. **p < .01. ***p < .001.



Figure 3.3. Intrinsic motivation in digital PBL tasks of primary school students (n = 121) and

secondary school students (n = 63) before and after teachers completed the training

In conclusion, the results showed that the training significantly affected the in-trinsic motivation of students. The intrinsic motivation scores on the PBL tasksafter the training were higher than those before the training. The class also sig-nificantly predicted the intrinsic motivation of students. The significant interac-tion effect between training and school type on students’ intrinsic motivationindicated that the increase in intrinsic motivation for the PBL tasks was greaterfor secondary school students than for primary school students.

3.4 DiscussionThis study examines whether teachers are able to apply the principles of auto -nomy support and structure support in designing digital PBL tasks. Previous research shows that digital PBL tasks with both autonomy support and struc-ture support have a positive effect on students’ intrinsic motivation and learn -ing outcomes (Van Loon et al., 2012). Teachers experience difficulties inincorporating these principles into PBL tasks because they often believe thatautonomy support and structure support are two opposite principles. How-ever, autonomy support and structure support are two separate dimensions ofa learning environment that motivates students (Jang et al., 2010; Reeve et al.,2004a). The current study is the first to examine teachers’ ability to design di -gi tal PBL tasks with a combination of autonomy support and structure support.



5,25

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4,25

4,00



Time

Intr

insi

c M

oti

vati

on

5,75

5,50

The study investigated whether training in the application of the combinationof these two principles in digital PBL tasks can increase teachers’ perceivedskill in creating digital PBL tasks and the autonomy- and structure-supportivenature of the tasks. More importantly, we examined whether primary and sec-ondary school students experience greater autonomy, competence, and moti-vation in these tasks.

The first part of the first hypothesis, i.e., teachers will indicate that they aremore skilled in creating digital PBL tasks after completing the training, wasconfirmed. The results showed that teachers indicated that they were moreskilled in creating digital PBL tasks after completing the training than beforethe training. In addition, the second part of the first hypothesis, i.e., teacherswill indicate that their digital PBL tasks are more autonomy- and structure-sup-portive after completing the training, was confirmed. Teachers assessed thedegree of structure support within digital PBL tasks as higher than the degreeof autonomy support. Based on the low scores on autonomy support andstructure support before training and the increase of these scores after train-ing, training on these two principles is effective.

The second hypothesis, i.e., primary and secondary school students will ex-perience greater autonomy and competence in digital PBL tasks that are de-signed by teachers after training than before the training, was confirmed. Theresults showed that students’ perceived autonomy and perceived competencescores on the digital PBL tasks after teachers completed the training werehigher than those before teachers completed the training. An examination ofthe difference between primary and secondary school students demonstratedthat primary school students scored higher on perceived autonomy and per-ceived competence in digital PBL tasks before and after the training than didsecondary school students. There was also an interaction effect between train-ing and school type on perceived autonomy and perceived competence. Theincrease in perceived autonomy and perceived competence from PBL tasksthat were designed by teachers before they completed the training to the PBLtasks after the training was greater for secondary school students than for pri-mary school students.

The third hypothesis, i.e., primary and secondary school students will expe-rience greater intrinsic motivation in digital PBL tasks that are designed byteachers after the training than before the training, was also confirmed. The in-trinsic motivation of students on the digital PBL tasks after the teachers com-pleted the training was higher than that before teachers completed thetraining. An examination of the difference between primary and secondaryschool students indicated that primary school students scored higher on intrin-sic motivation in digital PBL tasks before and after the training than did sec-



ondary school students. Additionally, there was an interaction effect; com-pared to primary school students, secondary school students evidenced agreater increase in intrinsic motivation from the tasks before the training to thetasks after the training.

Previous research shows that students in secondary education are less mo-tivated than primary school students (Wigfield et al., 2006). It is possible thatthese students’ lower motivation scores are due to the lower levels of auto -nomy support and structure support provided by teachers in secondary educa-tion. In the current study, the baseline scores of autonomy, competence, andmotivation of secondary education students were indeed lower. However, arelatively short teacher training on autonomy- and structure-supportive skillswas associated with great improvement on these aspects among secondaryeducation students.

Although the hypotheses were confirmed, some limitations must be con-sidered. First, because the students were nested within different classes andtaught by different teachers, the factor “class” was included in the analyses.Although the number of students was large (184), the number of teachers inthis study was relatively small (20); therefore, the results should be interpretedwith caution (Kreft & Deleeuw, 1998). In future studies, a greater number ofteachers should be included. Second, the data on the teachers and studentscould not be compared with a group of untrained teachers. In this study, thislimitation was partially overcome by the use of multiple methods of data col-lection (triangulation) (Campbell & Fiske, 1959). The variables of autonomysupport and structure support in digital PBL tasks were operationalized basedon multiple perspectives, namely, teachers’ perceptions of autonomy- andstructure support in the PBL tasks and students’ perceptions of the PBL tasks.

This study provides important guidelines for teachers who are designing digital PBL tasks based on instructional constructivist learning in the class. Toavoid information overload and ensure motivation, which is an important predic-tor of learning performance (Grolnick & Ryan, 1987; Vansteenkiste, Simons,Lens, Sheldon, & Deci, 2004), digital PBL tasks must contain a combination ofautonomy support and structure support. Autonomy support provides choices, arationale for a task, and avoids the use of controlling language. It ensures thatstudents feel control over their actions (Reeve et al., 2003). Structure supportprovides clear goals and expectations for students and explicitly describes theconsequences of achieving (or not achieving) these goals, provides help andguidance for students to successfully carry out a task, and provides students withclear procedures to follow. Structure support makes the learning environmentless chaotic and more consistent and predictable for students (Guay et al., 2008).

This study shows that teachers can be trained to apply autonomy support



and structure support in their digital PBL tasks. Teachers indicated that thetasks were more autonomy- and structure-supportive after they completed thetraining and students experienced more autonomy, competence, and motiva-tion in these tasks. We believe that this success is due to the combination ofthe following design principles: teachers require time to develop, absorb, dis-cuss, and practice new knowledge (Garet et al., 2001), teachers’ learningshould be situated and focused on authentic activities in the classroom (Garetet al., 2001; Hawley & Valli, 1999) and teachers from the same school or yearlevel should participate collectively (Desimone et al., 2002; Garet et al., 2001).More research is needed to examine whether the effect of the training can beattributed to a particular principle or a combination of principles.



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3 This chapter is submitted for publication as: Van Loon, A.-M., Ros, A., & Martens, R. (2013). Training teacher’s autonomy-supportive and structure-supportive behavior.

This chapter is presented as: Van Loon, A.-M. (2011, June). Autonomieondersteunend en structu -rerend leerkrachtgedrag [Autonomy-supportive and structure-supportive teacher behavior] at Onderwijs Research Dagen, Maastricht, the Netherlands.

Chapter 4Training Teacher’s Autonomy-supportive and Structure-supportive Behavior3

AbstractThe aim of the present study is to advance our understanding of how teachers,through their teaching style, can motivate students, and whether teachers canbe trained in this. The data for this study were collected based on a sample of23 elementary teachers who were trained during one year, and 164 studentsfrom grades three, four, five, and six at a primary school in The Netherlands.This study shows that teachers can be trained in a combined teaching stylethat includes autonomy-supportive and structure-supportive behaviors to moti-vate students. Students’ motivation and perceived structure support increasedsignificantly during school year.

Keywords: Self-determination theory; Autonomy support; Structure support; Motivation; Teachers’ training.

4.1 IntroductionEvery teacher dreams of motivated students who want to learn. If children aremotivated, they are enthusiastic, interested, involved, and curious; they activelycope with challenges and setbacks (Skinner & Belmont, 1993). In practice, this isoften not the case. Student engagement declines over time; students findschool to be boring, and they do not enjoy learning (Skinner, Furrer, Marchand,& Kindermann, 2008). Teachers wonder what they can do to motivate children.Assuming that teacher behavior can appeal to students’ motivation (Deemer,2004), this study is based on the Self-Determination Theory (SDT), a motiva-tional theory that has received substantial empirical support (Ryan & Deci,2002). SDT assumes that all individuals, regardless of background, have an intrinsic urge to explore, organize, understand, and assimilate their environment(Deci, Ryan, & Williams, 1996). In contrast, motivation theories in the past weremore extrinsic, emphasizing reward and punishment to get something done.Research shows a recent and clear shift towards intrinsic motivation theoriessuch as SDT (Boekaerts, Van Nuland, & Martens, 2010). SDT indicates that thesource of motivation is internal to the student, and when the teacher providesfor students’ basic psychological needs, motivation will flourish (Deci & Ryan,2000). These psychological needs comprise the need for competence (White,1959), autonomy (DeCharms, 1968; Deci, 1975) and relatedness (Baumeister &Leary, 1995). Teachers, by their behavior in the classroom, enhance or decreasestudent motivation by fulfilling these basic needs.

In an educational setting, the need for competence involves the experi-ence of efficacy while completing a (learning) task (Ryan & Deci, 2000a). Feel-ings of competence affect intrinsic motivation, particularly if there is autonomy.Autonomy refers to the initiative and freedom that a person experiences in anactivity without outside pressure with respect to his or her personal goals (Ryan& Deci, 2000b). Autonomy involves being self-organized and having a sense ofchoice about one’s behavior. Finally, there is the need for relatedness to signifi-cant others, such as teachers and classmates. Relatedness is defined as ”thedesire to feel connected to others- to love and care, and to be loved andcared for” (Deci & Ryan, 2000, p. 231).

This study is concerned with what is required of teachers to meet two ofthese basic needs, focusing on teachers’ behavior and how they can fulfill students’ needs for autonomy and competence. Research has shown thatteacher–student interaction is the critical factor in fostering a sense of compe-tence and autonomy (Deci & Ryan, 2000; Seifert, 2004). However, there is stilllittle known about how teacher behavior can meet the need for autonomy andcompetence. Often, research focuses only on meeting the need for one or theother–autonomy or competence–but not both (Reeve & Jang, 2006; Reeve,



Jang, Carrell, Jeon, & Barch, 2004a). The aim of the present study is to ad-vance our understanding of how teachers, via their teaching style, can fulfillboth of these needs. In addition, it remains to be discovered whether teacherscan be trained in their teaching style to fulfill these needs.

4.1.1 Autonomy Support and Structure SupportTeachers can fulfill the need for autonomy with an autonomy-supportive teach-ing style (Reeve, Nix, & Hamm, 2003; Reeve, Ryan, Deci, & Jang, 2007). To satisfactorily promote the competence need, a teacher must demonstrate astructure-supportive teaching style (Connell & Wellborn, 1991; Skinner & Belmont, 1993). Research has shown that fulfilling these needs in the classroomleads to higher intrinsic motivation (e.g., Reeve & Jang, 2006). If students areintrinsically motivated to learn, they often perform better in school (Ryan &Deci, 2000a). Intrinsic motivation is associated with greater exploratory beha -vior (Martens, Gulikers, & Bastiaens, 2004), strategy use for self-regulated learning (Van Grinsven & Tillema, 2006), high cognitive performance, in-depthlearning, and better recall of the acquired knowledge (Deci & Ryan, 2008; Grolnick & Ryan, 1987; Vansteenkiste, Simons, Lens, Sheldon, & Deci, 2004).

An autonomy-supportive teacher recognizes the personal goals of children(Deci & Ryan, 2000; 2008) by providing students with a degree of choice (Katz &Assor, 2007). The fact that children can choose from several options makes themfeel more in control of their behavior (Reeve et al., 2003). Another aspect of anautonomy-supportive teaching style includes providing a rationale for a task. Ifchildren receive a meaningful explanation of why it is useful for them to do a cer-tain learning task, the probability increases that children will internalize the per-sonal relevance of the learning task and, therefore, be motivated to learn (Deci,Eghrari, Patrick, & Leone, 1994; Reeve, Jang, Hardre, & Omura, 2002). Further-more, it is important that teachers acknowledge the students’ feelings by tryingto empathize with and respect the learner’s perspective (Reeve & Jang, 2006)and by avoiding the use of controlling language (Reeve, Deci, & Ryan, 2004b).

A structure-supportive teaching style refers to the amount of informationthat teachers provide to students about expectations and ways of effectivelyachieving desired educational outcomes (Skinner & Belmont, 1993). Providingstructure support means that teachers make their goals and expectations clear,explicitly describe the consequences of achieving or not achieving the goalsand consistently apply consequences (Connell, 1990; Connell & Wellborn,1991; Reeve et al., 2004b; Skinner & Belmont, 1993). Teachers can providesuch structure support by offering help and support and by adjusting teachingstrategies to the level of the child such that students better know how to accomplish goals (Reeve et al., 2004b; Skinner & Belmont, 1993).



Although some teachers may think differently, providing structure supportto children is not the opposite of providing autonomy support (Ryan, 1993).Support of autonomy and structure are two separate dimensions of a teachingstyle, each contributing its own unique role to supporting student motivationand engagement (Jang, Reeve, & Deci, 2010; Reeve et al., 2004b). Autonomysupport enriches students’ perceived autonomy, whereas structure support primarily enriches students’ perceived competence (Jang et al., 2010). Thus,they are both important. Providing structure support makes the learning envi-ronment less chaotic and more consistent and predictable for students. Theopposite of an autonomy-supportive teaching style is a controlling teachingstyle (Black & Deci, 2000). Controlling teachers interfere with students’ innermotives because they define what students should do (Reeve et al., 2004b).The reason that both aspects are important is that offering support only for autonomy is insufficient. If a teacher only supports autonomy, he or she createstoo much associative distraction by overwhelming students with too manychoices and increases the risk of students ‘getting lost’ and following ineffec-tive learning paths. Thus, in addition to autonomy support, structure supportplays a key role in an optimal teaching style (Jang et al., 2010). Research showsthat this combination leads to positive effects on optimal self-regulated learn-ing (Sierens, Van Steenkiste, Goossens, Soenens, & Dochy, 2009), student’s engagement (Jang et al., 2010), student’s motivation in digital learning (VanLoon, Ros, & Martens, 2012) and student self-determination in, for instance,physical education (Taylor & Ntoumanis, 2007).

However, in practice, teachers find it difficult to support both autonomyand structure. As previously stated, one of the reasons for this situation is thatthe two approaches seem to contradict each other. Whether teachers can betrained in these behaviors such that they use both dimensions in the classroomis an important question. It is this question that this study addresses.

4.1.2 Training TeachersTo date, little is known about the best way to improve teachers’ autonomy-supportive behavior in combination with structure-supportive behavior throughtraining. There are only a few studies addressing the professionalization ofteachers acquiring autonomy-supportive teaching skills (deCharms, 1976;Reeve, 1998; Reeve et al., 2004a; Su & Reeve, 2011). Moreover, research ontraining primary school teachers’ autonomy-supportive skills in combinationwith structure-supportive skills is scarce. Only Aelterman, Vansteenkiste, VanKeer, De Meyer, Van den Berghe, and Haerens (2013) have developed a train-ing for teachers on autonomy-supportive and structure-supportive teaching.However, this training is not put into practice. The authors made no attempt to



evaluate the impact of training on teachers’ teaching behaviors nor to students’ outcomes (Aelterman et al., 2013).

In addition, it is not easy to train teachers and to change their behavior.Much of the research on teachers’ professional learning activities is often char-acterized as ineffective (Borko, Jacobs, & Koellner, 2010; Hanushek, 2005). Thereason teacher professional development has been so disappointing is that forteacher learning to occur, changes in teachers’ beliefs and practices as well aschanges in students must occur (Clarke & Hollingsworth, 2002; Opfer & Ped-der, 2011). Therefore, teacher learning must be conceptualized as a complexsystem rather than as an event (Clarke & Collins, 2007; Collins & Clarke, 2008).

Research about the professional development of teachers has shown thatto change teachers’ behavior, certain principles should be taken into account.Firstly, teachers need time to develop, absorb, discuss, and practice newknowledge (Garet, Porter, Desimone, Birman, & Yoon, 2001). Thus, profes-sional development that involves significant numbers of contact hours over along period of time is typically associated with effectiveness (Guskey, 2000).Secondly, teachers’ learning should be situated and focused on authentic activ-ities in the classroom (Garet et al., 2001). Research shows that teachers learnmost effectively when activity is school-based and integrated into the dailywork of teachers (Garet et al., 2001; Hawley & Valli, 1999). Thirdly, the profes-sional growth of teachers requires opportunities for discussion, reflection, andfollow-up activities (Korthagen, Loughran, & Russell, 2006). Teachers learn ef-fectively when they reflect on how they should teach pupils (Borko & Putnam,1997). Finally, professional development has been shown to be more effectiveif teachers from the same school or year level participate collectively (Desi-mone, Porter, Garet, Yoon, & Birman, 2002; Garet et al., 2001).

This study is aimed at changing teachers to be more autonomy- supportiveand structure-supportive, based on the principles above. The aim of this studyis to understand whether primary school teachers can be trained to adopt anautonomy- supportive and structure-supportive teaching style during a schoolyear. The effects on teachers’ perceptions, students’ perceptions and objectiveobservations of teacher’s behavior will be studied.

4.1.3 The Present Study and HypothesesThe present study will examine the effects of training in which teachers’ auton-omy- supportive and structure-supportive behaviors become professionalized.This leads to the following hypotheses:

Teachers who are trained in autonomy-supportive and structure-supportiveskills during one year will increase their autonomy-supportive and structure-supportive behavior (hypothesis 1).



Student perceptions of teachers’ autonomy support, structure support andstudents’ motivation increase when teachers are trained in autonomy-support-ive and structure-supportive behavior (hypothesis 2).

Student reports of teachers’ autonomy support and structure support willpositively predict student motivation in the classroom (hypothesis 3).

4.2 Methodology4.2.1 DesignThe research is based on a one-group pre-test–post-test design. To test hy-pothesis 1, teachers were asked to assess their teaching style with respect tothe two dimensions – autonomy support and structure support – in their class-rooms during social science lessons. Independent assessors also made obser-vations in the classroom, scoring teacher behavior. Two clusters of items wereassessed, namely teachers’ autonomy support and teachers’ structure support.

To test hypotheses 2 and 3, students were asked to evaluate their teacher’suse of autonomy support and structure support and to report on their motivation.

4.2.2 ParticipantsThe study took place at a primary school in the Netherlands. All students andteachers are from the same school. The school is located in the South of theNetherlands and has a population of 350 students. The average learning out-comes of the students from the participating school were on the same level asthose of their peers at other schools throughout the country (Dutch Inspec-torate, 2007).

The initial teacher sample contained 24 elementary school teachers. Be-cause one teacher retired during the school year, this research is based on 23teachers (5 male, 18 female).

The initial student sample contained 170 students from grades three, four,five, and six. Students who did not complete the entire questionnaire were ex-cluded from the analyses. Hence, all analyses were based on a final sample of164 students from grades three, four, five, and six in primary education (91boys, 73 girls). The mean age of the students at the outset of the study was10.8 years (SD = 1.21, range = 8.5 - 13.5 years). These students were nestedwithin 8 classes, each with its own teacher.

4.2.3 TrainingTo strengthen autonomy-supportive and structure-supportive teaching behav-ior, training was given to the 24 teachers by an experienced external trainer.The training is based on the four principles described in the introduction tothis article. The first principle that teachers need time to develop and practice



new knowledge is met by the fact that the training involves a significant num-ber of contact hours over a long period of time. The training takes one schoolyear and consisted of four team meetings and coaching on the job.

During the first team meeting at the beginning of the school year, therewas a presentation given by the trainer, who explained the two dimensions ofthe teaching style, namely autonomy support and structure support. The em-pirical support for the assertion that students benefit when teachers supporttheir needs for autonomy and competence was shown to the teachers. Afterthis introduction, more detailed information was provided regarding the di-mensions of structure support and autonomy support. Examples were shownthat demonstrated structure support and autonomy support in the classroom.

Following this meeting, teachers were required to make a plan for howthey wanted to implement structure support and autonomy support in theirlessons. Thus, the second principle that teachers’ learning is situated and focuses on authentic activities in the classroom is met. While performing theselessons, each teacher was coached on the job by the trainer. This coaching involved the trainer attending one lesson in the classroom and making obser-vations of the teacher’s behavior. The trainer used a checklist. Following thelesson, the trainer discussed with the teacher what he had observed and iden-tified strengths and areas for improvement. The teacher took these points intoaccount when preparing for the subsequent lessons. In this way, the third prin-ciple, that the professional growth of teachers requires opportunities for dis-cussion, reflection, and follow-up activities, is practiced. Because teachers fromone school learn together, the fourth principle, that teachers from the sameschool participate collectively, is also realized.

In the second, third, and fourth meetings, which occurred two months, fourmonths, and seven months, respectively, after the first meeting, both auto -nomy support and structure support were discussed. During each meeting,film clips of the classroom visits that the trainer had made were shown to theteachers. These were good examples of autonomy and structure supportdemonstrated by the teacher. Afterwards, the teachers discussed what elements of autonomy support and structure support they have observed.Then, the teachers prepared their lessons for the coming period, taking intoaccount the principles of autonomy support and structure support. Again, during one of the lessons, each teacher was coached on the job with a check-list and feedback was given after the lesson about strengths and areas for improvement. The teacher took into account these points when preparing thefollowing lessons. The final team meeting was also used to evaluate the train-ing and the learning process. See Figure 4.1 for the schematic representationof the cyclic process of the training.



Figure 4.1. Schematic representation of the cyclic process of the training

4.2.4 ProcedureOn three occasions during one school year (before the training, between thesecond and third meetings, and after the last meeting), teachers were asked to fill out a questionnaire regarding observations of their own behavior duringsocial science lessons in a specific trimester.

On three occasions (before the training, between the second and thirdmeetings, and after the last meeting), students were asked to fill out a ques-tionnaire regarding their teacher’s behavior in the classroom during social science lessons. Teachers were asked to leave the room while the question-naire was being completed. The students had the same teacher throughoutthe entire school year.

Teachers were observed three times (before the training, between the sec-ond and third meetings, and after the last meeting) in the classroom during asocial science lesson. These lessons were videotaped. The observations of thelessons were assessed by external raters using a rating sheet; these raters objectively measured the autonomy-supportive and structure-supportive be-havior of the teachers.

4.2.5 Measures4.2.5.1 Teacher report: autonomy support and structure supportTeachers were asked to assess their teaching style with respect to the two dimensions– autonomy support and structure support– in the classroom duringsocial science lessons, using the Teacher as Social Context Questionnaire



Input and feedback in

team meetings about

autonomy support and

structure support

Preparation of

new lessons

Practice lessons in

the class

Coaching on the

job

(Belmont, Skinner, Wellborn, & Connell, 1988). The subscale for autonomy support was composed of twelve items, for example, “I try to give students alot of choices about classroom assignments.” The subscale for structure sup-port was composed of fifteen items, for example, “I always tell the studentswhat I expect of them.” All items were answered using a 1 - 4 Likert scale,which ranged from 1 (completely disagree) to 4 (completely agree). Previousresearch (e.g., Skinner & Belmont, 1993) that used this questionnaire hasdemonstrated acceptable internal consistency for the two subscales. In thepresent study, Cronbach’s alpha coefficients were .77 (autonomy support) and.74 (structure support).

4.2.5.2 Student perceptions of autonomy support and structure supportStudents were asked to evaluate their teachers’ use of the two teaching dimen-sions using the short student version of the Teacher as Social Context Question-naire (Belmont et al., 1988). The students rated their own teacher. We used thesubscales autonomy support (eight items, e.g., “This teacher gives me a lot ofchoices about how to do my schoolwork” and structure support (eight items,e.g., “If I can’t solve a problem, this teacher shows me different ways to try to doit”). All items were answered using a 1 - 4 Likert scale, which ranged from 1(completely disagree) to 4 (completely agree). Scale scores were calculated byaveraging the items within the scale (negative items were reverse coded). Skinner and Belmont (1993) demonstrated the internal consistency of a longerversion of the questionnaire. In the present study, Cronbach’s alpha coefficientswere .80 (autonomy support) and .81 (structure support).

4.2.5.3 Student motivationStudents reported their motivation using the subscale for intrinsic motivationof the Intrinsic Motivation Inventory (IMI) (Ryan, 1982). For example, the itemsthat measure intrinsic motivation are: “I enjoyed doing this lesson very much”and “This lesson was fun to do”. All seven items were answered using a 1 - 4Likert scale, which ranged from 1 (completely disagree) to 4 (completelyagree). Previous research has demonstrated the internal consistency of thisscale (e.g., McAuley, Duncan, & Tammen, 1987). The present study shows thatthe Cronbach’s alpha coefficient was .85.

4.2.5.4 Observations of autonomy-supportive and structure-supportive behavior

Not only were the teachers asked to report on their own behavior; independ-ent assessors also made classroom observations and scored teacher behavior.Two raters who were trained with classroom observational skills rated teachers’



provision of autonomy support and structure support. The rating sheet fea-tured two clusters of items to assess measures of the teacher’s autonomy support and structure support. Each item was scored using a 1–3 Likert scale.The items were taken and slightly modified from an existing questionnaire, theTeacher as Social Context Questionnaire (Belmont et al., 1988).

The raters scored four autonomy-supportive instructional behaviors. Au-tonomy support includes non-controlling behavior (no coercion through forceor authority), respect (acknowledging the importance of student opinions, feel-ings, and agendas), choice (encouraging students to follow their own interestsor providing options), and relevance (providing a rationale for learning activi-ties). The interrater reliability was rs = .87. The four autonomy-supportive actsof instruction were positively intercorrelated; therefore, we averaged them into a single overall teacher-provided autonomy support score (α = .70).

The raters scored four instructional behaviors to represent teacher-pro-vided structure support. Structure support includes items tapping teacher clarity of expectations, contingency (consistency and predictability of re-sponse), instrumental help and support and adjustment of teaching strategies.The interrater reliability was rs = .87. The four structure-supportive acts of instruction were positively intercorrelated; therefore, we averaged them into a single overall teacher-provided structure support score (α = .87).

4.2.6 Data AnalysesTo test the hypothesis that the teachers trained in autonomy-supportive andstructure-supportive skills during one year would increase their autonomy-sup-portive and structure-supportive behavior (hypothesis 1), a general linearmodel with repeated-measures was employed because the same teachers par-ticipated in all conditions. The scores of each teacher on the first, second, andthird instances of measurement were compared. Two repeated-measures mod-els were constructed, with perceptions of the teacher’s autonomy- supportiveand structure-supportive teaching styles as dependent variables and time asthe independent variable. The same was done for the observations made. Ageneral linear model with repeated-measures was employed such that thescores of each teacher’s observation on the first, second, and third instances ofmeasurement were compared.

To test hypothesis 2, that students’ perceived autonomy support, per-ceived structure support and motivation increase when teachers trained theirautonomy-supportive and structure-supportive behavior, three linear mixedmodels were constructed with the perception of the student’s perceived au-tonomy, perceived structure support and motivation as the dependent vari-ables and time as the independent variable. Because repeated-measures data



have a hierarchical structure (students are nested in classes), we analyzed amultilevel model, more specific a growth model. Nesting students in classeswas taken into account by including the class as a fixed factor in the analysis.This is necessary because when the class is not a factor, the data result in anunderestimation of the standard errors of regression coefficients and a subse-quent overestimation of statistical significance (Hox, 2002).

The hypothesis that students’ reports of teacher’s autonomy support andstructure support would positively predict students’ motivation in the class (hypothesis 3) was tested by constructing a general linear model with analysisof covariance. Because the number of classes is small (N = 8), the analysis ofcovariance approach was used (Snijders & Bosker, 1999). Nesting students inclasses was taken into account by including the class as a fixed factor in theanalysis.

4.3 Results4.3.1 Autonomy-supportive and Structure-supportive Behavior of TeachersIt was expected that teachers who were trained in autonomy-supportive andstructure-supportive skills during one year would increase their autonomy-sup-portive and structure-supportive behavior (hypothesis 1). Table 4.1 reports thedescriptive statistics, the means and the standard deviations of autonomy sup-port and structure support of teachers at the three time-points in the school year.

To test hypothesis 1, repeated-measures ANOVA was performed with thequestionnaire results regarding perceptions of the teachers of their teachingstyle at the beginning, at the midpoint and at the end of the school year.Mauchly’s test was not significant. This result indicated that the assumption ofsphericity has been met.

The results show that time significantly affected the teachers’ perceptionsabout their autonomy-supportive behavior (F(2, 44) = 4.29, p < .05). Post hoctests revealed that autonomy-supportive behavior differed significantly be-tween the beginning and the end of the school year (p < .05). The results showthat time significantly affected the perceptions of teachers about their struc-ture-supportive behavior (F(2, 44) = 3.75, p < .05). Post hoc tests revealed thatstructure-supportive behavior differed significantly between the beginning andthe end of the school year (p < .05).

The same test was performed for the observations that were made. Repeated measures ANOVA was performed using the observations of eachteacher at the beginning, at the midpoint and at the end of the school year.Mauchly’s test was not significant. The results show that time significantly affected the observed autonomy-supportive behavior of teachers (F(2, 24) =18.26, p < .001). Post hoc tests revealed that the observed autonomy-support-



ive behavior differed significantly between the beginning and the end of theschool year (p < .01). Additionally, autonomy-supportive behavior differed significantly between the middle and the end of the school year (p < .05). Theresults also show that time significantly affected the observed structure-sup-portive behavior of teachers (F(2, 24) = 23.00, p < .001). Post hoc tests re-vealed that structure-supportive behavior differed significantly between thebeginning and the end of the school year (p < .001). Additionally, structure-supportive behavior differed significantly between the middle and the end ofthe school year (p < .01).

Finally, the results show that autonomy-supportive and structure-support-ive behavior differed significantly between the beginning and the end of theschool year. The same pattern was seen in the observations that were made inthe classroom.

Table 4.1

Descriptive Statistics for Perceived and Observed Autonomy Support and Structure Support

of Teachers

Begin School Year Mid School Year End School Year

M SD M SD M SD

Perceived

Autonomy Support 2.95 0.45 3.00 0.32 3.16 0.47

Perceived

Structure Support 3.12 0.34 3.20 0.25 3.26 0.34

Observed


Observed


4.3.2 Perceived Autonomy Support, Perceived Structure Support and Motivation of Students

The hypothesis was made that students’ perceived autonomy support, per-ceived structure support and motivation increase when teachers were trainedregarding their autonomy-supportive and structure-supportive behavior (hy-pothesis 2). Table 4.2 reports the descriptive statistics, the means and the stan-dard deviations of perceived autonomy support, perceived structure supportand motivation of students at the three time points in the school year.

To test hypothesis 2, three linear mixed models with the perception of thestudent’s perceived autonomy, perceived structure support and motivation as



the dependent variables and time as the independent variable were con-structed. Because repeated-measures data that have a hierarchical structure(students are nested in classes) were analyzed, a growth model was used. Thisis a specific multilevel model.

The results show that time significantly affected the motivation of students(F(1, 144.99) = 7.75, p < .01). The class did not significantly predict the motiva-tion of students. So being in a specific class did not predict motivation. Addi-tionally, the interaction of time and class did not significantly predict themotivation of students. The relationship between time and motivation of stu-dents showed no significant variance in intercepts across students. In addition,the slopes did not vary across students, and the slopes and intercepts did notsignificantly covary.

The results show that time did not significantly predict the perceived auto -nomy support of students. In contrast, the class significantly affected the per-ceived autonomy support of students (F(7, 419.76) = 6.29, p < .001). Theinteraction of time and class did not significantly predict the perceived auto -nomy support of students. The relationship between time and the perceivedautonomy support of students showed no significant variance in interceptsacross students. In addition, the slopes did not vary across students, and theslopes and intercepts did not significantly covary.

The results show that time significantly affected the perceived structuresupport of students (F(1, 147.80) = 21.39, p < .001). The class also significantlypredicted the perceived structure support of students (F(7, 149.88) = 2.67, p <.05). The interaction of time and class did not significantly predict the per-ceived structure support of students. The relationship between time and theperceived structure support of students showed no significant variance in inter-cepts across students. The slopes varied significantly across students (var (u1j)= 0.05, p < .05), but the slopes and intercepts did not covary.

To summarize, the results show that students’ motivation increases duringthe school year if teachers are trained in autonomy-supportive and structure-supportive behavior. Students’ perceived structure support also increases dur-ing the school year. The extent to which a student is experiencing a teacher’sstructure support during the school year differs by class and depends on thestructure-supportive behavior of the teacher. Students’ perceived autonomysupport did not significantly increase over time. In addition, there is a large difference in students’ perceived autonomy support between the classes.



Table 4.2

Descriptive Statistics for Perceived Autonomy Support, Perceived Structure Support and

Motivation of Students

Begin School Year Midpoint School Year End School Year

M SD M SD M SD

Perceived


Perceived


Motivation 3.11 0.65 3.20 0.68 3.28 0.65

4.3.3 Effects of Perceived Autonomy Support and Perceived Structure Support on Motivation

The hypothesis that students’ reports of teacher’s autonomy support and struc-ture support would positively predict students’ motivation in the class (hypothe-sis 3) was tested by constructing a general linear model with analysis ofcovariance. The class is included as a fixed factor in the analysis, autonomy sup-port and structure support were entered as simultaneous predictors. The sameanalysis of covariance for the three times of the year was performed. At all time-points, Levene’s test was not significant. This result indicated that the assump-tion of homogeneity of variance was met, and the group variances were equal.

The results at the beginning of the school year show that the class was not re-lated to the motivation of the students. In contrast, there was a significant effectof autonomy support on motivation (F(1, 154) = 10.88, p < .01), and there was asignificant effect of structure support on motivation (F(1, 154) = 43.54, p < .001).

The results at the midpoint of the school year show that the class was not re-lated to the motivation of the students. In contrast, there was a significant effectof autonomy support on motivation (F(1, 154) = 8.92, p < .01), and there was asignificant effect of structure support on motivation (F(1, 154) = 8.03, p < .01).

The results at the end of the school year show that the class was not relatedto the motivation of the students. In contrast, there was a significant effect of autonomy support on motivation (F(1, 154) = 20.24, p < .001), and there was asignificant effect of structure support on motivation (F(1, 154) = 8.11, p < .01).

The predictors to examine hypothesis 3 can be found in Table 4.3. At all timesduring the year, autonomy support and structure support, as covariates, are significant predictors for motivation. As described in Table 4.3, the same effectswere found at the beginning, the midpoint, and at the end of the school year.



Table 4.3

Results of the Parameter Estimates for Autonomy Support and Structure Support on Motiva-

tion During the School Year

Begin School Year Midpoint School Year End School Year

Motivation β SE B t β SE B t β SE B t

Intercept 1.11** 0.30 3.76 1.18* 0.38 3.06 1.64** 0.32 5.19

Autonomy Support 0.28* 0.09 3.30 0.32* 0.11 2.99 0.36** 0.08 4.50

Structure Support 0.48** 0.07 6.60 0.30* 0.11 2.83 0.22* 0.08 2.85

Note. *p < .01. **p < .001.

4.4 DiscussionThere is substantial empirical evidence that teachers’ teaching style influencesstudents’ motivation. Much less is known about the trainability of (a combina-tion of) such styles. Can teachers’ teaching style be changed to enhance students’ motivation? Based on SDT research, training was performed that focused on a teaching style that combined autonomy support and structuresupport to fulfill these psychological needs. In addition, the training was basedon the main principles of effective teacher professional development.

Training teachers in these principles is not previously done. Although combining autonomy support and structure support is not easy and may evenseem counterintuitive, and because, more generally, research shows that it is not easy to train teachers and change their behavior (Borko et al., 2010;Hanushek, 2005), teachers who were trained in autonomy-supportive andstructure-supportive skills during one year did increase their autonomy-sup-portive and structure-supportive behavior. Thus, the first hypothesis was confirmed. The results show that the training significantly affected the auto - nomy-supportive and structure-supportive behavior of teachers. Scores on selfreports and assessment scales for autonomy-supportive and structure- supportive behavior differed significantly between the beginning and the endof the school year. Not only was progress made in the perception of teachers’behavior, but objective assessment of teachers’ behavior indicated that teach-ers improved their autonomy-supportive and structure-supportive behavior. Inaccord with previous research, it appears that teachers can not only be trainedin autonomy-supportive behavior (deCharms, 1976; Reeve, 1998; Reeve et al.,2004a; Su & Reeve, 2011) but also in the combination of structure-supportiveand autonomy-supportive behavior.

The second hypothesis was only partially confirmed. Students’ motivationincreased significantly during the school year when teachers were trained inautonomy-supportive and structure-supportive behavior. Students’ perceived



structure support also increased significantly during the school year. In contrastto students’ perceived structure support and motivation, students’ perceivedautonomy support did not significantly increase over time. The fact that per-ceived autonomy support did not increase over time can be explained by thefact that providing autonomy support is more difficult to observe by studentsthan structure support. By providing autonomy support, teachers give childrenmore freedom and more ownership of their own learning (Reeve et al., 2003).Providing structure support means creating clear expectations, consequences,help and support (Connell, 1990; Reeve et al., 2004b; Skinner & Belmont,1993). It is likely that these are behaviors that can be easily noted by students.This finding is confirmed by the perception of the teachers. After the training,teachers still feel more skilled in providing structure support than in providingautonomy support. Also previous research pointed out that structure-support-ive behaviors are considered more familiar than autonomy-supportive behaviors that were found to be more innovative (Aelterman et al., 2013).

The third hypothesis, that students’ reports of teacher’s autonomy supportand structure support would positively predict students’ motivation in theclass, was confirmed. Autonomy support and structure support yielded a positive effect on motivation. This finding is in line with previous research thatshows that both styles are needed for optimal self-regulated learning (Sierenset al., 2009), students’ engagement (Jang et al., 2010), students’ motivation indigital learning (Van Loon et al., 2012) and students’ self-determination (Taylor& Ntoumanis, 2007). The present study also shows that the effects of the relationship between autonomy support, structure support and motivation isstable over time. The same effects of autonomy support and structure supporton motivation were found at the beginning, the midpoint and the end of theschool year.

Overall, the results seem to consistently build on the outcomes of previousstudies. Teacher behavior can be changed to reflect a teaching style that enhances students’ motivation. However, there are some limitations to con-sider. First, because the students are nested within different classes and aretaught by different teachers, the factor “class” was included in the analyses.Although the number of students is large, the number of classes in this study isvery small; therefore, the results should be interpreted with caution (Kreft &Deleeuw, 1998). For future studies, it is recommended to include more classes.Second, the data on the teachers and students cannot be compared with agroup of teachers who are not trained. In this study, this limitation is partiallyovercome by using multiple methods of data collection (triangulation) (Camp-bell & Fiske, 1959). The variables of autonomy-supportive and structure-sup-portive behavior of teachers are from different operationalized optics, namely,



perception of the teacher’s own behavior, perceptions of the student regard-ing his teacher’s behavior and assessment of the teachers behavior by observers.

4.4.1 ConclusionThis study provides potentially important guidelines for teachers. It has be-come clear that a combined teaching style includes autonomy-supportive behaviors such as providing choices, a rationale for a task, respecting thelearners’ perspective and avoiding the use of controlling language; and also includes structure-supportive behaviors such as making expectations clear, describing the consequences of achieving or not achieving the expectations,offering help and support, and adjusting teaching strategies to the level of thechild. This style shows that it is not a matter of only autonomy support or onlystructure support but rather that both are unique teacher behaviors that contribute to the motivation of students. Because structure ensures that thelearning environment is consistent and clear, students are better able to makeappropriate choices.

It is also clear how teachers can be trained in this teaching style. Althoughit is not easy to change teacher’s behavior, this study succeeded in changingteachers’ teaching styles to be more autonomy and structure-supportive in ashort time and increased students’ motivation. The training does not simplyfocus on providing more autonomy support or offering more structure support,but stresses the importance of the combination of autonomy support andstructure support. It is precisely this combination that leads to motivated students. Because these insights are important, it is vital to perform follow-upstudies to determine which elements of the training have been especially important in changing the teachers’ behavior.



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4 This chapter is submitted for publication as: Van Loon, A.-M., Ros, A., & Martens, R. (2013). Char-acteristics of an effective teacher professional development program on students’ motivation.

This chapter is presented as: Van Loon, A.-M. (2011, November). Promoting teachers’ autonomysupportive and structuring behavior: effective design principles at European Association for Prac-titioner Research on Improving Learning Conference, Nijmegen, the Netherlands.

Chapter 5Characteristics of an Effective Teacher Professional DevelopmentProgram on Students’ Motivation4

AbstractPrevious chapter has shown that it is possible to construct an effective profes-sional development program (PDP) that succeeds in increasing teachers’ auto -nomy-supportive and structure-supportive teaching behavior so students aremore motivated to learn. The PDP was based on seven design principles of effective professional development. In this study we focused on the extent towhich each principle contributed to this effect and if these design principles areequally important for all teachers. The study took place at one elementary schoolin the Netherlands. The results indicate there are four design principles that con-tributed most to the professional deve lopment of teachers: the intensity of theprogram, the opportunities for active learning, the possibility of applying thelearning in classroom practice, and the fact that the program builds on previousknowledge of teachers. The three design principles that contributed the least—collective participation, opportunities for reflection, and modeling—were valuedsignificantly differently by teachers whose start situation or increase in autonomy-supportive and structure-supportive skills over the PDP was low, average, andhigh.

Keywords: Students’ motivation, Teachers’ training, Professional deve -lopment program, Design principles

5.1 IntroductionThe motivation of students in elementary schools decreases over time (Gottfried, Flemming, & Gottfried, 2001; Stoel, Peetsma, & Roeleveld, 2001).Teachers wonder what they can do to motivate children in their classes. Moti-vational science is an important part of educational psychology (Van Nuland,Dusseldorp, Martens, & Boekaerts, 2010). The influential Self-DeterminationTheory (SDT) has, in its quest for answers to these motivational problems, received substantial empirical support (for overviews see Deci & Ryan, 2008;Ryan & Deci, 2002). SDT indicates that the source of motivation is internal tothe student, and when the teacher fulfills the students’ basic psychologicalneeds, motivation will flourish, since it is an innate propensity (Deci & Ryan,2000). These psychological needs are the need for competence (White, 1959),autonomy (DeCharms, 1968; Deci, 1975) and relatedness (Baumeister & Leary,1995). So teachers, by their behavior in the classroom, can enhance or de-crease students’ motivation by fulfilling their basic needs. If teachers want toincrease the motivation of students, their own behavior will have to changeinto more needs-supporting behavior. However, educational research showsthat changing the educational behavior of teachers is a very complex matter(Fullan, 1991). Nevertheless, previous chapter showed that it may be possibleto construct an effective professional development program (PDP) that can actually change teacher behavior in classroom practice (Van Loon, Ros, &Martens, 2013). After such a PDP teachers were significantly more supportiveof students’ basic needs and, as a consequence, students were more moti-vated (Van Loon et al., 2013). However, an important remaining question is:What exactly makes such a PDP work? Therefore, this study focuses on whichaspects of this successful PDP do teachers recognize as contributing to theirprofessional development? This article aims to contribute to existing know -ledge about effective professional development of teachers and to deepen ourunderstanding of the application of SDT in the classroom.

5.1.1 Autonomy Support and Structure SupportFrom research on the SDT (Ryan & Deci, 2000; 2002), evidence has built upthat a teacher has to be autonomy-supportive to fulfill the need for autonomy(Reeve, Ryan, Deci, & Jang, 2007). Also, he or she has to provide structuresupport to fulfill the need for competence (De Brabander, Rozendaal, &Martens, 2009; Grolnick & Ryan, 1989; Skinner & Belmont, 1993; Tucker et al.,2002) and to promote students’ engagement and motivation in the class (Jang,Reeve, & Deci, 2010; Sierens, Van Steenkiste, Goossens, Soenens, & Dochy,2009; Taylor & Ntoumanis, 2007; Van Loon, Ros, & Martens, 2012). The needfor autonomy involves being self-organized and having a sense of choice about


Chapter 5 | Characteristics of an Effective Teacher PDP on Students´ Motivation

one’s behavior. The need for competence involves the experience of efficacywhile completing a (learning) task (Ryan & Deci, 2000).

Autonomy support is about a variety of teacher behaviors such as acknow -ledging the perspective of students, which enhances students’ feelings of voli-tion (Reeve, Nix, & Hamm, 2003). An autonomy-supportive teacher recognizesthe personal goals of children (Deci & Ryan, 2000; 2008) by providing studentswith a degree of choice (Katz & Assor, 2007). The fact that children can choosefrom several options makes them feel more in control of their behavior (Reeveet al., 2003). Another aspect of an autonomy-supportive teaching style is pro-viding a rationale for a task. If children receive a meaningful explanation of whyit is useful for them to do a certain learning task, the probability increases thatchildren will internalize the personal relevance of the learning task and, there-fore, be motivated to learn (Deci, Eghrari, Patrick, & Leone, 1994; Reeve, Jang,Hardre, & Omura, 2002; Van Nuland, Taris, Boekaerts, & Martens, in press).Furthermore, it is important that teachers acknowledge their students’ feelingsby trying to empathize with and respect the learner’s perspective (Reeve &Jang, 2006) and by avoiding the use of controlling language (Reeve, Deci, &Ryan, 2004).

Besides autonomy support, providing structure support is also a key part of a teaching style that promotes students’ motivation (Connell, 1990; Skinner& Belmont, 1993; Skinner, Furrer, Marchand, & Kindermann, 2008). Providingstructure support means that teachers make their goals and expectations clearand explicitly describe the consequences of achieving or not achieving thegoals (Connell, 1990; Connell & Wellborn, 1991; Reeve et al., 2004; Skinner & Belmont, 1993). Teachers may also provide structure support by offeringhelp and support and by adjusting their teaching strategies to the level of thechild so that students know better how to accomplish goals (Reeve et al.,2004; Skinner & Belmont, 1993).

Research by Jang et al. (2010) has shown that autonomy support and structure support are separate and independent aspects of a teaching style,and that each plays its own unique part in enhancing students’ motivation andengagement. Although it is difficult to change teacher behavior, previous chapter has shown that it is possible to construct an effective PDP that actuallysucceeds in changing teachers’ behaviors into a combination of a more autonomy-supportive and structure-supportive teaching behavior within oneyear (Van Loon et al., 2013). The effects of the PDP on teachers’ autonomy-supportive and structure-supportive behavior were found to be significant. Asa consequence students experienced more autonomy and structure, and theywere more motivated to learn. The PDP was based on several design principlesof effective professional development. In this study we focus on which design



principles seem to be the most important for increasing these skills in teachersand whether they can in practice be applied to autonomy support and struc-ture support in tandem; this is in order that we can learn from this example ofeffective teacher professional development for future programs.

5.1.2 Teacher Professional DevelopmentProfessional development is about teachers’ learning, and transforming theirknowledge into practice for the benefit of their students’ growth (Avalos,2011). After all, the most powerful influence on students’ learning is the qualityof teaching that students experience (Hawley & Valli, 1999). However, as statedbefore, it is not easy to train teachers and change their behavior to improvethe quality of their teaching (Fullan, 2007). Often teachers’ professional devel-opment is characterized as ineffective (Borko, Jacobs, & Koellner, 2010;Hanushek, 2005). The reason teachers’ professional development has been sodisappointing is that teacher learning is a complex process often in a complexorganization (Clarke & Collins, 2007; Collins & Clarke, 2008; Evers, Kreijns, Vander Heijden, & Gerrichhauzen, 2011). For teacher’s behavioral change to occur,changes in teachers’ beliefs and practices must occur (Clarke & Hollingsworth,2002; Opfer & Pedder, 2011). Therefore, teacher learning must be conceptual-ized as a complex system rather than as an event (Clarke & Collins, 2007;Collins & Clarke, 2008).

One way of translating the complex nature of teacher development is tofocus on professional development approaches that are more closely alignedwith constructivist and situational theories that are grounded in classroompractice and involve the formation of professional learning communities, in-stead of workshops or courses outside the school (Borko et al., 2010). Increas-ingly, teachers’ professional development is conceptualized as a learningprocess that is embedded within the context of the school and that takes placein the workplace (e.g. Putnam & Borko, 2000; Sleegers, Bolhuis, & Geijsel,2005; Smylie & Hart, 1999).

Based on literature reviews and accounts of successful professional devel-opment programs (PDP’s), different principles or features of high-quality PDPcan be distinguished that increase teachers’ learning and change their prac-tice, and ultimately improve students’ learning (Desimone, 2009; Desimone,Porter, Garet, Yoon, & Birman, 2002; Garet, Porter, Desimone, Birman, & Yoon,2001). Many authors have used different terms for the same design principles;therefore, we have summarized the literature according to seven design princi-ples that can be hypothesized as being effective in improving teaching prac-tice.

These principles are: the intensity of the PDP; the emphasis on the collec-



tive participation; the integration into the daily work of teachers; the oppor-tunities for active learning; the opportunities for reflection; the opportunitiesfor modeling; and, the coherence of teachers’ professional development.Each principle is described below:1. Research shows that for professional development activities to result in a

change of teacher behavior they need to be of sufficient duration, whichincludes both the span of time over which the activity is spread and thenumber of hours spent in the activity (Cohen & Hill, 2001; Fullan, 1993;Guskey, 1994). Activities that effectively support teachers’ professionallearning need to be sustained and intensive rather than brief and sporadic.Traditional learning activities such as one-off workshops and conferencesare less likely to lead to teacher change (Hawley & Valli, 1999). Thus, pro-fessional development that involves a significant number of contact hoursover a long period of time is typically associated with effectiveness(Guskey, 2000).

2. Professional development is far more effective in changing teachers’ class-room practice when it involves the collective participation of teachersfrom the same school, department, or grade (Desimone et al., 2002; Garetet al., 2001; Wayne, Yoon, Zhu, Cronen, & Garet, 2008). Collective partici-pation sets up potential interactions and discussions which can be a power-ful form of teacher learning (Borko, 2004; Fullan, 1991; Guskey, 1994;Little, 1993; Loucks-Horsley, Hewson, Love, & Stiles, 1998; Rosenholtz,1989; Wegerif & De Laat, 2011). Collective participation provides teacherswith opportunities to discuss and negotiate the meaning of the new learn-ing and its implications for practice with their colleagues (Timperley, Wil-son, Barrar, & Fung, 2007).

3. Professional development is most meaningful to teachers when it is closelyconnected to their work in classrooms (Hargreaves & Fullan, 1992; Wilcox,1998). Research shows that teachers learn most effectively when the pro-fessional activity is school-based, focused, and integrated into authenticactivities in the classroom (Garet et al., 2001; Greeno, 1994; Hawley & Valli,1999; Wideen, Mayer-Smith, & Moon, 1998). Professional developmentshould be “school based” or “integrated into the daily work of teachers”(Hawley & Valli, 1999; Joyce & Showers, 2002). Situating the professionaldevelopment content within the practice of teaching helps to ensure thatwhat teachers are learning is relevant to their classroom practice (Borko etal., 2010).

4. The engagement of teachers in active learning is also related to the effec-tiveness of professional development (Garet et al., 2001; Loucks-Horsley etal., 1998). Active learning is about the learner applying new knowledge,



and teachers becoming actively engaged in meaningful discussion, plan-ning, and practice (Lieberman, 1996; Loucks-Horsley et al., 1998). Teachersare less likely to change practice as a result of passive learning activitiessuch as presentations and the memorizing of new knowledge (Birman, Desimone, Porter, & Garet, 2000; Desimone et al., 2002; Garet et al., 2001;Loucks-Horsley et al., 1998; Wayne et al., 2008).

5. The professional growth of teachers requires opportunities for reflectionand follow-up activities (Korthagen, Loughran, & Russell, 2006). Teacherslearn effectively when they reflect on how they should teach pupils (Borko& Putnam, 1997). Research has shown that teachers reported that theyfound the cycle of classroom observation and feedback helpful in support-ing their implementation of new practices (Timperley et al., 2007). Tillema(2000) demonstrated that reflection after practice has a positive effect onbelief change, whereas reflection prior to practice did not result in beliefchange, resulting in an unstable change of practice. Thus, learning aboutteaching requires opportunities for reflection after practice.

6. Effective professional development requires opportunities for learners tosee preferred instructional strategies in practice. When teacher-educatorsmodel instructional strategies, teachers have the opportunity to expe -rience these strategies as learners, and then reflect on the effectiveness of the strategies from the perspective of teachers (Borko et al., 2010). According to research, teachers who are given opportunities to see parti -cular approaches implemented in real or simulated classroom situations, either through modeled or videotaped lessons, indicate that this is one ofthe most useful aspects of the PDP (Adey, 2004).

7. And finally, a professional development activity is more likely to be effec-tive in improving teachers’ knowledge and skills if it forms a coherent partof a wider set of opportunities for teacher learning and development andwhen it builds on what teachers have already learned (Garet et al., 2001).The extent to which teacher learning is consistent with teachers’ know -ledge and beliefs is important (Desimone, 2009). Learning is an activeprocess where learners construct new understandings based on what theyalready know and believe (Borko et al., 2010).

In addition, teacher learning becomes hard to define by means only of the aggregation and generalities of design principles because the nature of learn-ing depends also on the uniqueness of the person (Opfer & Pedder, 2011).Some teachers change more than others through participation in professionaldevelopment programs (Franke, Carpenter, Levi, & Fennema, 2001). Teachersbring both past experiences and beliefs to their teaching and learning (Opfer& Pedder, 2011). In understanding what determines whether teacher learning



is to occur, the characteristics of individual teachers should also be taken intoaccount.

5.1.3 The Present Study and Research QuestionsAlthough research shows that these principles are effective in teachers’ profes-sional development (Garet et al., 2001; Hiebert, 1999; Loucks-Horsley et al.,1998), there is little direct evidence of the relative contribution that each ofthese principles makes to changing teaching behavior into being more needssupporting and to increasing student motivation, and also of whether there aredifferences in how different types of teachers evaluated each design principle.There is still little known about which design principles are most effective fordifferent types of teachers. Thus, there is a clear need for systematic researchon the effectiveness of these principles for professional development.

This leads to the following research questions:1. Which design principles have contributed most to teachers’ professional

development according to teachers? 2. a). Are there differences between teachers’ evaluation of which design

principles have contributed most to their professional development forteachers with high, average, and low initial autonomy-supportive and struc-ture-supportive skills?

3. b). Are there differences between teachers’ evaluation of which designprinciples have contributed most to their professional development forteachers with a high, average, and low increase in their autonomy-support-ive and structure-supportive skills following the PDP?

5.2 Methodology5.2.1 DesignAn effective PDP that professionalizes teachers in their autonomy-supportiveand structure-supportive behavior was developed. The research was a quantita-tive study. To answer Questions 1 and 2, teachers were asked to indicate whichdesign principles had contributed to their own professional development.

5.2.2 ParticipantsThe study took place at an elementary school in the Netherlands. The school islocated in the south of the Netherlands and has a population of 350 students.The average learning outcomes of the students from the participating schoolwere on the same level as those of their peers at other schools throughout thecountry (Dutch Inspectorate, 2007).

The initial teacher sample contained 24 elementary school teachers. Because one teacher retired during the school year, this research was actually



based on 23 teachers (5 male, 18 female). On average, the teachers had 13.1years of teaching experience, and they taught a class size of 19.0 students.

5.2.3 InterventionTo strengthen autonomy-supportive and structure-supportive teaching behav-ior, a PDP was given to the 24 teachers by an experienced external trainer. ThePDP is based on the seven design principles described in the introduction.

During the first team meeting at the beginning of the school year, therewas a presentation given by the trainer, who explained the two dimensions ofthe teaching style, namely autonomy support and structure support. The em-pirical support for the assertion that students benefit when teachers supporttheir needs for autonomy and competence was shown to the teachers. Afterthis introduction, more detailed information was provided regarding the di-mensions of structure support and autonomy support. The teachers wereshown examples that demonstrated structure support and autonomy supportin the classroom. The trainer also brought the dimensions of autonomy sup-port and structure support into the classroom practice. The trainer offeredstructure support by providing the learning goals of the PDP, making the ex-pectations clear, and describing how the teachers could reach the goals. Au-tonomy support was also provided by giving teachers the choice of whichlesson they wanted to put their new skills into practice.

Following this meeting, the teachers were required to make a plan for howthey wanted to implement structure support and autonomy support in theirlessons. While performing these lessons, each teacher was coached on the jobby the trainer. This coaching involved the trainer attending one lesson in theclassroom and making observations on the teacher’s behavior. The trainer useda checklist. Following the lesson, the trainer discussed with the teacher whathe had observed and identified strengths and areas for improvement. Theteacher took these points into account when preparing for the subsequent lessons.

In the second, third, and fourth meetings, which took place two, four, andseven months after the first meeting, both autonomy support and structure sup-port were discussed. During each meeting, film clips of the classroom visits thatthe trainer had made were shown to the teachers. These clips were good exam-ples of autonomy and structure support demonstrated by the teacher. Afterwards, the teachers discussed collectively what elements of autonomy sup-port and structure support they had observed. Then, the teachers prepared theirlessons for the coming period, taking into account the principles of auto nomysupport and structure support. Again, during one of the lessons each teacherwas coached on the job by means of a checklist and feedback was given after



the lesson about strengths and areas for improvement. The final team meetingwas also used to evaluate the PDP and the learning process. Table 5.1 describesthe operationalization of the seven design principles in the PDP.

Table 5.1

Operationalization of the Design Principles

Design principle Operationalization of the design principlein the PDP

1. Professional development activities shouldbe sustained and intensive rather thanbrief and sporadic.

The PDP took one school year and con-sisted of four team meetings and on thejob coaching.

2. Professional development is more effectivein changing teachers’ classroom practicewhen it has collective partici pation fromteachers from the same school, depart-ment, or grade.

Teachers from one school learned together.They discussed and negotiated the mean-ing of autonomy support and structure sup-port and the implications for practice withtheir colleagues in the four team meetings.

3. Professional development should beintegrated into the daily work of teachers.

The PDP took place at school during theschool year and was about improvingteachers’ autonomy-supportive and structure-supportive teaching skills in theclassroom.

4. Effective professional activities engageteachers in active learning.

Following the team meetings, teacherswere required to make a plan for how theywanted to implement structure supportand autonomy support in their lessons andpractice the new skills in these lessons.

5. The professional growth of teachers re-quires opportunities for reflection andfollow-up activities.

While performing these lessons with autonomy support and structure support,each teacher was coached on the job bythe trainer. The trainer used a checklist.Following the lesson, the trainer discussedwith the teacher what he had observedand identified strengths and areas for improvement. The teacher took thesepoints into account when preparing for the subsequent lessons.

6. Effective professional development incor-porates processes such as modeling pre-ferred instructional strategies.

In the PDP, examples were shown thatdemonstrated autonomy support andstructure support in the classroom. Also,the trainer brought the dimensions of autonomy support and structure supportinto practice.

7. Professional development should form a coherent part on what teachers have already learned.

The program was a follow-up to earliertraining meetings which were about theeducational approach of the school.



5.2.4 ProcedureAt the end of the school year, after teachers had completed the program,teachers were asked to fill in a questionnaire about what they had learnedabout autonomy support and structure support in the classroom and which de-sign principles had contributed to their own professional development.

On three occasions during one school year (before the first meeting, be-tween the second and third meetings, and after the last meeting), teacherswere asked to fill out a questionnaire with their observations on their own au-tonomy-supportive and structure-supportive behavior during social science les-sons in a specific trimester.

5.2.5 Measures5.2.5.1 Measuring design principlesTeachers were asked to indicate which design principles had contributed totheir own professional development.Therefore a questionnaire was developed.The questionnaire contained the seven principles that could be hypothesizedas being effective in improving teaching practice: the intensity of the PDP; theemphasis on collective participation; the integration into the daily work ofteachers; the opportunities for active learning; the opportunities for reflection;the opportunities for modeling; and the coherence of teachers’ professionaldevelopment.

All items were answered using a 5-point Likert scale, which ranged from 1,completely disagree, to 5, completely agree. Teachers had to indicate to whatextent each principle had contributed to their professional development. A de-scription of how we measured and scaled each of the seven principles of pro-fessional development is set out as follows:

IntensityTeachers were asked if the intensity of the PDP had contributed to their pro-fessional development. The items were: “The duration of the PDP has con-tributed to my professional development” and “The number of team meetingsfor the PDP contributed to my professional development.” Cronbach’s alphacoefficient was .83.

Collective ParticipationTeachers were asked if the collective participation in the PDP had contributedto their professional development. The single item that measured this was,“Opportunities for exchange of knowledge, ideas, and experiences with col-leagues in the meetings have contributed to my professional development.”



Integration into daily work Teachers were asked if the integration of the knowledge into their daily workhad contributed to their professional development. This was measured by theitem: “Opportunities for integration of knowledge into practice in my ownclass have contributed to my professional development.”

Active learningTo measure active learning, teachers were asked if the active participation inthe PDP had contributed to their professional development. The items were:“Opportunities for my active participation during the PDP have contributed tomy professional development” and “Opportunities to apply the new skillsabout autonomy support and structure support in the lessons have contributedto my professional development.” Cronbach’s alpha coefficient was .89.

Opportunities for reflectionTeachers were asked if opportunities for reflection had contributed to theirprofessional development. This was measured by the item: “Opportunities forreflection on my own behavior from the coaching in the classroom visits havecontributed to my professional development.”

ModelingTo measure opportunities for modeling, teachers were asked if the opportunitiesfor modeling within the PDP had contributed to their professional development.The items were: “Opportunities to see good examples of providing autonomysupport and structure support in the meetings have contributed to my profes-sional development” and “Opportunities to learn from the trainer who also of-fered autonomy support and structure support in the PDP have contributed tomy professional development.” Cronbach’s alpha coefficient was .85.

CoherenceTeachers were asked if the coherence of the PDP had contributed to their professional development. This is measured by the item: “Building new know -ledge on what I already knew about autonomy support and structure supporthas contributed to my professional development.”

5.2.5.2 Measuring teachers’ differencesTeachers were asked to assess their teaching style with respect to the two dimen -sions—autonomy support and structure support—in the classroom during socialscience lessons, using the Teacher as Social Context Questionnaire (Belmont, Skinner, Wellborn, & Connell, 1988). The subscale for autonomy support was com-



posed of twelve items, including for example, “I try to give students a lot of choicesabout classroom assignments.” The subscale for structure support was composedof fifteen items, including for example, “I always tell the students what I expect ofthem.” All items were answered using a 4-point Likert scale, which ranged from 1,completely disagree, to 4, completely agree. Previous research (e.g., Skinner & Belmont, 1993) that has used this questionnaire has demonstrated that there is acceptable internal consistency for the two subscales. In the present study, Cron-bach’s alpha coefficients were .74 (autonomy support) and .77 (structure support).

5.2.6 Data AnalysesTo answer Question 1 quantitative data based on the questionnaire that measured the design principles was used. Mean scores and standard devia-tions were computed, and the principles were ranked on the basis of the highest mean score to the lowest mean score.

To answer Question 2a the scores of every teacher for autonomy supportand structure support on the first measurement were used. On the basis of allthe scores of the individual teachers at the first measurement, a mean scoreand standard deviation were calculated. Three groups were created: teacherswho scored more than a 1/2 SD below the mean score (Group 1); teachers whoscored between 1/2 SD below the mean score and 1/2 SD above the meanscore (Group 2); and, teachers who scored more than 1/2 SD above the meanscore (Group 3). How each group evaluated the design principles was exam-ined. The three groups were compared using one-way ANOVAs. The assump-tions for these parametric tests were met. The variances in each conditionwere fairly similar, the measurements were independent and autonomy support and structure support were measured on an interval scale.

The same was done for Question 2b, as the scores of every teacher on autonomy support and structure support on the first and third measurementwere used. The difference between the third and the first measurement was calculated for each teacher—these are the difference scores that indicate the increase in the skills of teachers. On the basis of all the difference scores for theindividual teachers, a mean score and standard deviation were calculated. Threegroups were created: teachers who scored more than 1/2 SD below the meanscore (Group 1); teachers who scored between 1/2 SD below the mean scoreand 1/2 SD above the mean score (Group 2); and, teachers who scored morethan 1/2 SD above the mean score (Group 3). How each group evaluated thedesign principles was examined. The three groups were compared using one-wayANOVAs. The assumptions for these parametric tests were met. The variances in each condition were fairly similar, the measurements were indepen dent and autonomy support and structure support were measured on an interval scale.



5.3 Results5.3.1 Which Design Principles have Contributed Most to Teachers’

Professional Development According to Teachers To answer the first question about what teachers attribute their behavioralchange to, mean scores and standard deviations of the ratings for each designprinciple were computed. Table 5.2 reports the descriptive statistics of thecontribution of each design principle to teachers’ professional developmentaccording to teachers. The mean score and standard deviation for all the design principles were M = 3.20, SD = 0.38.

Table 5.2

Descriptive Statistics for the Contribution of each of the Design Principles of Teachers

Professional Development

Rank Design Principle Minimum Maximum M SD

Order Score Score

1. 1. Intensity 2.00 5.00 3.61 0.77

2. 4. Active learning 2.00 5.00 3.57 0.77

3. 3. Integration into daily work 2.00 5.00 3.48 0.73

4. 7. Coherence 2.00 5.00 3.30 0.88

5. 2. Collective participation 1.00 4.00 3.00 1.04

6. 5. Reflection 1.00 4.00 2.74 0.81

7. 6. Modeling 1.00 4.00 2.67 0.80

As the results show, four design principles are above the mean score: the in-tensity of the PDP; the opportunities for active learning; the integration intothe daily work of teachers; and, the coherence with the professional develop-ment and previous knowledge of teachers. The results for the design principlesfor collective participation, opportunities for reflection, and opportunities formodeling are below the mean score.

5.3.2.1 Are there differences between teachers’ evaluation based on initial skills?

The differences in the evaluation of the design principles were measured be-tween teachers who started with a low score on autonomy support and structuresupport on the first measurement (Group 1), teachers who started with an aver-age score on autonomy support and structure support on the first measurement(Group 2), and teachers who started with a high score on autonomy support andstructure support on the first measurement (Group 3). The three groups werecompared on how they evaluated the design principles using one-way ANOVAs.



The result of Levene’s test was not significant. This result indicated that the assumption of equal variances is met and that the variances were not sig-nificantly different (i.e., they are roughly equal between groups). The one-wayANOVAs showed that on three of the design principles the three groupsscored significantly differently.

First, one-way ANOVA showed that the three groups significantly differedon Principle 2 “collective participation” (F(2, 20) = 4.88, p < .05). Post hoctests revealed that Group 1 scored significantly higher on collective partici -pation than Group 3 (p < .05), as shown in Figure 5.1.

Second, one-way ANOVA showed that the three groups significantly differed on Principle 5 “reflection” (F(2, 20) = 6.84, p < .05). Post hoc tests revealed that Group 2 scored significantly higher on reflection than Group 3 (p < .05), as shown in Figure 5.2.

Third, one-way ANOVA showed that the three groups significantly differedon Principle 6 “modeling” (F(2, 20) = 9.39, p < .05). Post hoc tests revealedthat Groups 1 and 2 scored significantly higher on modeling than Group 3 (p < .05), as shown in Figure 5.3.

In summary, when looking at the different starting situations of teachers,teachers with a low starting situation on autonomy support and structure support valued collective participation and modeling more than teachers witha high start situation. Teachers with an average start situation attached morevalue to reflection and modeling than teachers with a high start situation.There was no significant difference for the other design principles evaluated by the three groups.

Figure 5.1. Group differences for the design principle: collective participation



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Figure 5.2. Group differences for the design principle: reflection

Figure 5.3. Group differences for the design principle: modeling

5.3.2.2 Are there differences between teachers’ evaluation based on the increase of skills?

The differences in the evaluation of the design principles were measured between teachers who had a low increase in autonomy support and structuresupport on the third measurement compared to the first measurement (Group1), teachers who had an average increase in autonomy support and structure



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support on the third measurement compared to the first measurement (Group 2), and teachers who had a high increase in autonomy support andstructure support on the third measurement compared to the first measure-ment (Group 3). The three groups were compared on how they evaluated thedesign principles using one-way ANOVAs.

The Levene’s test result was not significant. This result indicated that theassumption of equal variances is met and that the variances were not signifi-cantly different (i.e., they are roughly equal between groups). The one-wayANOVA’s show that three groups only scored significantly differently on Principle 5 “reflection” (F(2, 20) = 5.88, p < .05). Post hoc tests revealed that Group 3 scored significantly higher on “reflection” than Group 2 did (p < .05),as shown in Figure 5.4.

In summary, when looking at the different increases for teachers, teacherswith a high increase in autonomy-supportive and structure-supportive skills valued reflection more than teachers with an average increase in autonomy-supportive and structure-supportive skills. There was no significant differencefor the other design principles evaluated by the three groups.

Figure 5.4. Group differences on the design principle: reflection



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5.4 DiscussionWe have attempted to develop an effective PDP that professionalizes teachersin their autonomy-supportive and structure-supportive behavior. Researchshows that autonomy support and structure support are separate and inde-pendent aspects of teaching style, each playing its own unique part in enhan -cing students’ motivation (Jang et al., 2010; Sierens et al., 2009; Taylor &Ntoumanis, 2007; Van Loon et al., 2012). Although it is difficult to changeteacher behavior (Borko et al., 2010; Fullan, 2007; Hanushek, 2005), previouschapter has shown that it is possible to construct an effective PDP programthat actually succeeds in significantly increasing teachers’ autonomy-supportive and structure-supportive teaching behavior so students are more motivated tolearn (in line with Van Loon et al., 2013). The PDP was based on seven designprinciples of effective professional development. In this study we focused onthe extent to which each design principle contributed to more autonomy-sup-portive and structure-supportive teaching behavior and if these design princi-ples were equally important for all teachers.

The results for Question 1 (Which design principles have contributed mostto teachers’ professional development according to teachers?) showed that according to teachers there were four design principles that contributed mostto their professional development. These were the intensity of the PDP, the opportunities for active learning, the integration into the daily work of teach-ers, and the coherence with the professional development and previous know -ledge of teachers. Collective participation, opportunities for reflection, andopportunities for modeling were reported as being least important for teach-ers’ professional development.

When we look at the results for Question 2 (Are there differences betweenteachers’ evaluation of which design principles have contributed most to theirprofessional development?), the results should be more nuanced than those ofQuestion 1. It turns out that it is precisely the three design principles that are theleast highly evaluated by teachers—collective participation, opportunities for reflection, opportunities for modeling—that are valued signi ficantly diffe rentlyby teachers with a low, average, and a high (a) start situation or (b) increase intheir autonomy-supportive and structure-supportive skills following the PDP.

Teachers with a low initial situation on autonomy support and structuresupport valued collective participation and modeling more than teachers witha high start situation. Teachers with an average start situation attached morevalue to reflection and modeling than teachers with a high start situation. Inaddition, teachers with a high increase in autonomy-supportive and structure-supportive skills valued reflection more than teachers with an average increasein autonomy-supportive and structure-supportive skills.



It can therefore be concluded that teachers with a low start situation takethe most advantage of collective participation and modeling relative to teach-ers with a high start situation. One explanation for this could be that theseteachers have a lot to learn from their colleagues and from examples, as op-posed to teachers who already are more skilled at the outset. The situation isthe same for teachers with an average start situation when it comes to model-ing and reflection. This means that active learning activities are especially im-portant for teachers who are medium- and low-skilled.

There are some limitations to consider. First, the number of teachers in thisstudy is small. For future studies, it is recommended that more teachers shouldbe included. Second, the data for the teachers cannot be compared with that fora group of teachers who are not trained. Third, the extent to which a designprinciple has contributed to the professional development of teachers can onlybe measured by a Likert-type scale. In follow-up studies, interviews about thecontribution of each principle could provide an added value in terms of findingout more exactly what teachers think about the contribution of each principle.

To conclude, our results indicate that effective professional developmentshould at least be intense in nature (intensity), give teachers opportunities forhands-on work (active learning), be integrated into the daily life of the school(integration into daily work), and build on previous knowledge of teachers (coherence). The PDP which incorporates these principles is more likely to produce enhanced knowledge and skills than one where these principles areabsent. Thus, to improve professional development, it is important to focus onthe duration and the core features (i.e., active learning, integration into dailywork, and coherence) of the professional development program. This is in linewith previous research about effective professional development for teachers(Garet et al., 2001). However, there is an important nuance: despite that collec-tive participation, opportunities for reflection and modeling were reported asbeing least important for teachers’ professional development, there were sig-nificant differences between different groups of teachers. Teachers with lowand average initial skills attached more value to these principles than teacherswho were already skilled at the start of the PDP. This means that there must bedifferentiated in the way the professionalization of teachers takes place. Teach-ers learn more effectively when the design principles of the PDP are connectedwith their different needs.



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Chapter 6Discussion

This dissertation investigates how teachers can promote (digital) motivatedlearning in students and be trained in this. The motive for this research is elaborated in four challenges, derived from experiences of teachers and researchers, grounded with literature results.

The first challenge concerns motivation problems in education. In practicewe see that despite the importance of motivation for school performance (e.g. Pintrich & Schrauben, 1992; Ryan & Deci, 2000; Skinner & Belmont,1993), motivation generally decreases during school years (Gottfried, Flem-ming, & Gottfried, 2001; Stoel, Peetsma, & Roeleveld, 2001). Teachers wonderhow they can motivate students. One thing that schools can do to motivatestudents is to use information and communication technology (ICT) in theclassroom (Liu & Bera, 2005; Liu, Horton, Olmanson, & Toprac, 2011; Mayer,2011). How to use digital applications in the classroom to motivate studentsand produce effective education is the second challenge for teachers. In linewith this, the third challenge is about how teachers can be professionalized increating a motivated learning environment because their professionalization isoften characterized as ineffective (Borko, Jacobs, & Koellner, 2010; Hanushek,2005). Finally, the fourth challenge has to do with the research approach. Infact, research can help to equip teachers with knowledge and insights to meetthe three challenges just described. To do this, it is important that the researchis relevant to teaching practice and leads to practical conclusions (Martens &Diepstraten, 2011; Reeves, 2006).

In the light of these challenges, the aim of this research is to expand the bodyof knowledge in the field of student motivation and teacher professionalization,and to help teachers to motivate students in their daily teaching practice.

6.1 Recapitulation of the Results of the Present ThesisThe current thesis tried to address four specific research questions in order toanswer the general question of how teachers can promote (digital) motivatedlearning in students and be trained in this. In the following sections the resultsare presented per research question. These four specific research questionscorrespond with the four empirical chapters of the thesis. For the sake of clarity, the results will be presented in separate sections.

The four specific research questions (RQs) are:

1. What should good digital learning environments contain to stimulate andmotivate students to learn? What is the combined and relative effect of auto nomy support and structure support on motivation and learning out-comes in digital environments?


Chapter 6 | Discussion

2. Can teachers be trained in applying autonomy support and structure sup-port in their digital learning tasks so students experience more autonomy,competence and motivation in these tasks?

3. Can teachers be trained to adopt an autonomy-supportive and structure-supportive teaching style during a school year, so students experiencemore autonomy support and structure support and their motivation in-creases?

4. Which design principle does teachers recognize as contributing to theirprofessional development in autonomy-supportive and structure-support-ive behavior?

Results RQ 1: What should good digital learning environments contain tostimulate and motivate students to learn? What is the combined and relativeeffect of autonomy support and structure support on motivation and learningoutcomes in digital environments?To answer the research question the principles of autonomy support and struc-ture support, of the Self-Determination Theory (SDT) were operationalized indigital learning tasks. The research was experimental in nature, based on a 2(with or without autonomy support) x 2 (with or without structure support) de-sign. Participants were 320 fifth- and sixth-grade students from eight elemen-tary schools throughout the Netherlands. To measure the intrinsic motivationof students, the Intrinsic Motivation Inventory (IMI) (Ryan, 1982) was used. Thelearning outcomes were measured by assessing the learning presentations cre-ated by students.

The findings showed that students provided with a digital learning taskwith autonomy support experienced a greater sense of autonomy, and students provided with structure support experienced a greater sense of com-petence. A digital learning task characterized by both autonomy support andstructure support had a positive effect on intrinsic motivation. The resultsshowed that even a single dimension (autonomy support or structure support)was sufficient to foster intrinsic motivation. There was also a positive interac-tion between autonomy support and structure support. This suggests, how-ever, that when both autonomy support and structure support are present theyare mutually supportive and result in high motivation. If both are absent, how-ever, low intrinsic motivation results. This finding concurs with previous re-search, suggesting that environments that inhibit the fulfillment of these needsyield fewer optimal forms of motivation (Deci & Ryan, 2008).

A digital learning task characterized by both autonomy support and struc-



ture support had also a positive effect on learning performance. The positive in-teraction effect indicated that the combination of autonomy support and struc-ture support leads to the best learning outcomes. A digital learning task thatonly provided structure support also had a positive effect on learning outcomes,but a digital learning task with only autonomy support had no impact on learn-ing outcomes. Specifically, autonomy support was only associated with betterlearning outcomes in conditions that also provided structure support. A possibleexplanation for this finding is that when students work on a digital learning taskwith only autonomy support and no structure support, they may be too easilydistracted from the purpose of the assignment. Students could be confused bythe options offered when there is no corresponding guidance on the differentsteps they should take to reach a solution. Such confusion could lead them tolose sight of their objectives and become less focused on the goals of the task,which, in turn, could negatively affect their learning outcomes.

In summary, the results show that when autonomy support and struc-ture support are present, digital learning tasks featuring problem-based learn-ing in a digital environment lead to a positive effect on intrinsic motivation andlearning outcomes of students.

Results RQ 2: Can teachers be trained in applying autonomy support andstructure support in their digital learning tasks so students experience moreautonomy, competence and motivation in these tasks?The previous research question examined the effect of autonomy support andstructure support in digital learning tasks on motivation and learning outcomesof students, that researchers have made. To answer Research question 2, therewas focused whether teachers can be trained in applying autonomy supportand structure support in their own digital learning tasks so that primary andsecondary school students experience more autonomy, competence and moti-vation in these tasks.

Participants were 184 fifth-, sixth-, seventh- and eighth- grade studentsand 20 teachers. The research was based on a one-group pre-test post-testdesign. Teachers were trained in applying the principles of autonomy supportand structure support in their digital PBL tasks. The training lasted two monthsand consisted of three team meetings. Teachers were required to create a planfor implementing autonomy support and structure support in their digital PBLtasks. During each meeting, teachers were coached in relation to theirstrengths and areas for improvement in their digital tasks. After the last meet-ing, they completed their new digital PBL task and offered it to the students intheir class.

Questionnaires filled in by teachers and students measured the progress of



digital learning tasks in fulfilling the need for autonomy, competence and moti-vation. To measure students’ perceived autonomy, perceived competence andintrinsic motivation, again the Intrinsic Motivation Inventory (IMI) (Ryan, 1982)was used, and to measure autonomy support and structure support in the digi-tal PBL tasks, teachers were asked to assess their task using a rating sheet. Theitems were adapted from an existing questionnaire, the Teacher as Social Con-text Questionnaire (Belmont, Skinner, Wellborn, & Connell, 1988).

The results showed that teachers saw their digital PBL tasks as more auto -nomy- and structure-supportive after completing the training. Teachers assessedthe degree of structure support within digital PBL tasks as higher than the degreeof autonomy support. On the basis of the low scores on autonomy support andstructure support before training and the increase in these scores after training, it can be concluded that training on these two principles was effective.

The results also showed that students’ perceived autonomy, perceivedcompetence and intrinsic motivation scores on the digital PBL tasks afterteachers completed the training were higher than those before teachers com-pleted the training. An examination of the difference between primary andsecondary school students demonstrated that primary school students scoredhigher on perceived autonomy, perceived competence and intrinsic motivationin digital PBL tasks before and after the training than secondary school stu-dents did. This is in line with previous research that shows that students in secondary education are less motivated than primary school students (Wig-field, Eccles, Schiefele, Roeser, & Davis-Kean, 2006). It is possible that thesestudents’ lower motivation scores resulted from the lower levels of autonomysupport and structure support provided by teachers in secondary education.However, compared with primary school students, secondary school studentsevidenced a greater increase in perceived autonomy, perceived competenceand intrinsic motivation.

In terms of the research question, the results show that teachers can betrained to apply autonomy support and structure support in their digital PBLtasks. Teachers indicated that their tasks were more autonomy- and structure-supportive after they completed the training and students experienced moreautonomy, competence, and motivation in these tasks.



Results RQ 3: Can teachers be trained to adopt an autonomy-supportive andstructure-supportive teaching style during a school year, so students experi-ence more autonomy support and structure support and their motivation increases?Based on Research questions 1 and 2, where the effect of autonomy supportand structure support in digital learning tasks was examined, Research ques-tion 3 is about an autonomy-supportive and structure-supportive teachingstyle. There is attempted to answer the question how teachers can be trainedto adopt an autonomy-supportive and structure-supportive teaching style during a school year so students experience more autonomy support andstructure support and their motivation increases.

The data for this research were collected from a sample of 23 elementaryteachers and 164 students from grades three, four, five, and six at a primaryschool in the Netherlands. The research was based on a one-group pre-testpost-test design. Questionnaires were used to measure the perceived teachingstyle of teachers and students’ perceptions of their teachers’ teaching style.Student motivation was again measured by the Intrinsic Motivation Inventory(IMI) (Ryan, 1982). Observations were made to analyze the teaching style during social science lessons, based on a rating sheet, the Teacher as SocialContext Questionnaire (Belmont et al., 1988). In addition, teachers were askedto assess their teaching style by using the Teacher as Social Context Question-naire (Belmont et al., 1988). Students were also asked to evaluate their teach-ers’ use of the two teaching dimensions (autonomy support and structuresupport) using the short student version of the Teacher as Social ContextQuestionnaire (Belmont et al., 1988).

Teachers were trained in their autonomy-supportive and structure-support-ive teaching skills by an experienced external trainer. The training took oneschool year and consisted of four team meetings and coaching on the job.Teachers were required to indicate how they wanted to implement structuresupport and autonomy support in their social science lessons. While perform-ing these lessons, each teacher was coached on the job by the trainer. Theteacher took strengths and improvements into account when preparing subse-quent lessons.

Although research shows that it is not easy to train teachers and changetheir behavior (Hanushek, 2005) the results indicate that teachers can adopt ateaching style that combines autonomy support and structure support to fulfillthe psychological needs of students. Teachers who were trained in autonomy-supportive and structure-supportive skills during a year did increase their auto -nomy-supportive and structure-supportive behavior. Scores on self-reports forautonomy-supportive and structure-supportive behavior differed significantly



between the beginning and the end of the school year. Not only was progressmade in the perception of teachers’ behavior, but objective observations ofteachers’ behavior also confirmed this.

In line with this, students’ motivation and perceived structure support increased significantly during the school year when teachers were trained in auto nomy-supportive and structure-supportive behavior. In contrast students’perceived autonomy support did not significantly increase over time. This canbe explained by the fact that providing autonomy support is more difficult toobserve by students than structure support. By providing autonomy support,teachers give children more freedom and more ownership of their own learn-ing (Reeve, Nix, & Hamm, 2003). Providing structure support means creatingclear expectations, consequences, help and support (Connell, 1990; Reeve,Deci, & Ryan, 2004a; Skinner & Belmont, 1993). It is likely that these are behav-iors that can be easily noted by students. This finding is confirmed by the per-ception of the teachers. After the training, teachers still feel more skilled inpro viding structure support than in providing autonomy support. Also previousresearch pointed out that structure-supportive behaviors are considered morefamiliar than autonomy-supportive behaviors that were found to be more inno-vative (Aelterman, Vansteenkiste, Van Keer, De Meyer, Van den Berghe, &Haerens, 2013).

In addition, students’ reports of teacher’s autonomy support and structuresupport positively predicted students’ motivation in the class. The same effectsof autonomy support and structure support on motivation were found at thebeginning, the midpoint and the end of the school year, so this relationship isstable over time; autonomy support and structure support yielded a positiveeffect on motivation.

Although it is not easy to change teacher’s behavior, this study succeededin changing teachers’ teaching styles to be more autonomy- and structure-sup-portive and increased students’ motivation.

Results RQ 4: Which design principle does teachers recognize as contributingto their professional development in autonomy-supportive and structure-sup-portive behavior? The results of Research question 3 showed that training to increase autonomy-supportive and structure-supportive behavior of teachers was successful. Research question 4 examined which design principle does teachers recognizeas contributing to their professional development in autonomy-supportive andstructure-supportive behavior.

The professional development program (PDP) of training teachers in auto - nomy-supportive and structure-supportive skills was based on seven design



principles, derived from literature, that are considered to be effective in professional development of teachers. Little is known, however, about whichdesign principle does teachers recognize as contributing to their professionaldevelopment in autonomy-supportive and structure-supportive teaching be-havior and if these design principles are equally important for all teachers. Theprinciples were: opportunity for an intense PDP; emphasis on collective partici-pation; integration into the daily work of teachers; opportunities for activelearning; opportunities for reflection; opportunities for modeling, and coher-ence in teachers’ professional development.

The study took place at a primary school in the south of the Netherlands. Ithas a population of 350 students. The teacher sample contained 23 elemen-tary school teachers. The research group was the same as in Research question3. At the end of the school year, after teachers had followed the training,teachers were asked to fill in a questionnaire about what they had learnedabout autonomy support and structure support in the classroom and which design principle had contributed to their professional development. The questionnaire contained the seven principles that could be hypothesized as effective in improving teaching practice.

The data in the study showed that there are four design principles thatcontributed the most to the professional development of teachers accordingto teachers. These were the intensity of the program, opportunities for activelearning, the opportunity to apply what was learned in classroom practice (integration into the daily work of teachers) and the fact that the programbuilds on previous knowledge of teachers (coherence in teachers’ professionaldevelopment). Collective participation, opportunities for reflection, and modeling were reported as least important to teachers’ professional develop-ment. When we look more closely at the three design principles, it is clear thatthese are valued significantly differently by teachers with a low, average and ahigh start situation or increase in autonomy-supportive and structure-support-ive skills. Teachers with a low start situation on autonomy support and struc-ture support valued collective participation and modeling more than teacherswith a high start situation. Teachers with an average start situation attachedmore value to reflection and modeling than teachers with a high start situation.In addition, teachers with a high increase in autonomy-supportive and struc-ture-supportive skills valued reflection more than teachers with an average increase in autonomy-supportive and structure-supportive skills.

It can therefore be concluded that teachers with a low start situation in particular took the greatest advantage of collective participation and modelingcompared with teachers with a high start situation. One explanation for thiscould be that these teachers have a lot to learn from colleagues and examples



as opposed to teachers who are already more skilled at the beginning. This isthe same for teachers with an average start situation in terms of modeling andreflection. This means that active learning activities are especially important toteachers who are medium- and low-skilled.

To conclude, the results indicate that effective professional developmentaccording to teachers should at least be intense in nature (intensity), givesteachers opportunities for “hands-on” work (active learning), should be inte-grated into the daily life of the school (integration into daily work) and buildson pre vious knowledge of teachers (coherence). The PDP with these principlesis more likely to produce enhanced knowledge and skills than if these princi-ples are absent. Because there are significant differences between differentgroups of teachers the ways in which professionalization of teachers takesplace must also be different.

6.2 From Results to Main ConclusionsThe results for the four specific research questions help to answer the generalquestion of how teachers can promote (digital) motivated learning in studentsand can be trained in this?

To answer the first part of the question, the principles of SDT are opera-tionalized. SDT indicates that the source of motivation is internal to the student, and when the learning environment fulfills the students’ basic psycho-logical needs, motivation will flourish (Deci & Ryan, 2000). The psychologicalneeds are the need for autonomy, competence, and relatedness (Deci & Ryan,2000). By contrast, when the learning environment frustrates psychologicalneeds and is too complex or too controlling, students consider the learningenvironment as sub-optimal and motivation will decrease (Van Nuland, 2011).This research is particularly focused on the need for autonomy and compe-tence. It has been investigated how these two basic needs can be fulfilled inthe classroom so that students’ motivation increases.

It emerges that perceived autonomy increases when a learning environ-ment provides autonomy support by offering choices, a rationale for a task,and non-directive language. An autonomy-supportive learning environmenthelps to fulfill the need of autonomy because students can experience free-dom in the activity (Reeve, Ryan, Deci, & Jang, 2007). A learning environmentthat provides structure support through clear goals, expectations, conse-quences, guidance, and procedures contributes to greater perceived com -petence because it makes a learning environment consistent and predictablefor students (Connell, 1990; Grolnick & Ryan, 1989; Skinner & Belmont, 1993;Tucker et al., 2002).

To promote (digital) motivated learning in students, teachers have to



provide autonomy support and structure support in combination. When auto -nomy support and structure support are present, in the behavior of teachers orin a digital learning task, this leads to a positive effect on intrinsic motivation.For digital learning tasks applies that structure support has a positive effect onboth intrinsic motivation and learning achievement, but this effect was not observed for autonomy support. Autonomy support without structure supportproduced the least effective learning outcomes. The explanation may be thatstructure support encourages metacognitive reflection, so students are betterable to deal with choices and this leads to more effective learning (Bannert,2004).

Teachers generally think that autonomy support and structure support aretwo opposing principles. Often, teachers only meet the need for one or theother but not both (Reeve & Jang, 2006; Reeve, Jang, Carrell, Jeon, & Barch,2004b). In fact our research confirms that autonomy support and structure support are two separate dimensions of a learning environment that motivatesstudents. Studies on SDT often pay more attention to autonomy support thanstructure support (deCharms, 1976; Reeve, 1998; Reeve et al., 2004b). The combined impact of autonomy support and structure support has not beenpreviously studied in the context of digital learning (Chen & Jang, 2010) andresearch is scarce on learning in the classroom in this context (Jang, Reeve, &Deci, 2010; Sierens, Vansteenkiste, Goossens, Soenens, & Dochy, 2009; Taylor& Ntoumanis, 2007).

Although it is not easy to change teachers‘ behavior (Hanushek, 2005), thisresearch shows that teachers can be trained to apply autonomy support andstructure support in their digital learning tasks and in their behavior in theclassroom so students are more motivated. The training does not simply focuson providing more autonomy support or offering more structure support, butstresses the importance of a combination of both. Training teachers in this wayhas not previously been done. Previous research has focused only on trainingautonomy-supportive behavior (deCharms, 1976; Reeve, 1998; Reeve et al.,2004b; Su & Reeve, 2011).

In answering the second part of the research question, how teachers can betrained in promoting motivated learning in students, this research shows thatthe success of the training is owed to four design principles: the intensity of thetraining (Cohen & Hill, 2001; Fullan, 1993; Guskey, 1994), opportunities for ac-tive learning (Garet, Porter, Desimone, Birman, & Yoon, 2001; Loucks-Horsley,Hewson, Love, & Stiles, 1998), integration into daily practice (Hawley & Valli,1999; Joyce & Showers, 2002) and the coherence with present know ledge ofteachers (Borko et al., 2010). According to teachers these were the four designprinciples that contributed most to their professional development.



Although collective participation (Desimone, Porter, Garet, Yoon, & Bir-man, 2002), opportunities for reflection (Korthagen, Loughran, & Russell, 2006)and modeling (Adey, 2004) were reported as least important to teachers’ professional development, there are significant differences between differentgroups of teachers. Teachers with low and average initial skills attach morevalue to these principles than teachers who are already skilled at the start ofthe training.

In conclusion, it can be stated that the results of the research show a consistent image. All studies suggest that a combination of autonomy supportand structure support contributes to motivated students. Also teachers canlearn to apply autonomy support and structure support in their lessons. The results indicate that motivated students and effective education are not aboutoffering only autonomy support or only structure support but about establish-ing the right balance between freedom of choice on the one hand and clearguidance on the other.

6.3 DiscussionThe results of this thesis can help to solve the challenges concerning students’motivation in education. These challenges relate to the deployment of digitalapplications, the professionalization of teachers and the role of the researchapproach. In the following paragraph the results are discussed in the contextof solving each challenge. Also the focus of the research is indicated.

Motivational challengeStudents’ motivation declines over time; students find school boring, and theydo not enjoy learning (Skinner, Furrer, Marchand, & Kindermann, 2008). There-fore an important challenge for schools is to motivate students. This researchfound that if the learning environment fulfills the need for autonomy and competence in combination, intrinsic motivation of students flourishes. Teachers’ behavior has to be both autonomy-supportive to fulfill the need forautonomy (Reeve et al., 2007) and structure-supportive to fulfill the need forcompetence (Grolnick & Ryan, 1989; Skinner & Belmont, 1993; Tucker et al.,2002).

This research focused on intrinsic motivation. Intrinsic motivation is the natural tendency to engage in activities for the inherent joy an activity gives(Ryan & Deci, 2000). Other forms of motivation are disregarded. Ryan and Deci(2000) describe a motivation continuum of the degree to which a person is motivated as emanating from the self (i.e. self-determined). The left of the self-determination continuum is a-motivation, the state of lacking the intention toact; at the right of the continuum is the classic state of intrinsic motivation.



Extrinsically motivated behaviors cover the continuum between a-motivationand intrinsic motivation, varying in the extent to which their regulation is autonomous. The more autonomous extrinsic motivation such as integratedextrinsic motivation is also associated with greater engagement (Connell &Wellborn, 1991) and better performance (Miserandino, 1996). This researchonly measured whether or not students are intrinsically motivated and not towhat extent they are extrinsically oriented because extrinsic motivation is considered to be inferior to intrinsic motivation with regard to psychologicalwell-being in the long-term (Ryan & Deci, 2000).

Autonomy support in this research is operationalized by giving choices, pro-viding a rationale and using non-directive language. Providing choices involvesoption choices and not action choices. With action choices, a student canchoose whether s/he does the task or not (Reeve et al., 2003). This is not thecase with option choices; the student is going to perform the task anyway andonly the way in which s/he does varies (Reeve et al., 2003). Although optionchoices contain less autonomy than action choices, it is clear from this researchthat these options still create more ownership among students that promotesmotivation. In addition, providing option choices can also be easily combinedwith structure support. Structure support includes among other things provid-ing clear learning goals and this, in turn, significantly increases learning per-formances (Latham & Locke, 2006). There is a question whether action choicesgo together with the provision of clear learning goals. In an educational settingthere is a fixed curriculum that students have to follow. If there are actionchoices, students can decide for themselves if they are going to do the task ornot, with the risk that not all learning goals are achieved, which has conse-quences for the learning performance of students. Therefore it is questionablewhether action choices have an added value besides option choices.

Teachers often think that autonomy support and structure support are contrasting dimensions whereas in fact these principles are complementary toeach other. Autonomy support ensures a greater sense of autonomy and structure support ensures a sense of competence of students. Each one fulfillsanother basic need. The teacher as a professional should, in every new situa-tion, consider whether s/he is providing enough autonomy support and structure support in combination to motivate students.

Motivational challenge in a digital learning environmentAs regards the digital opportunities available today in education, it is oftenthought that students are automatically more motivated and learn more fromthese new applications. This is naive. Digital learning tasks in the classroom arenot necessarily more motivating and informative.



This research focused on digital learning tasks that rely on conceptualknowledge, so-called digital problem-based learning (PBL) tasks, instead oftasks that improve skills by using drill and practice methods. In PBL tasks, theemphasis is on solving complex problems in rich contexts, so students cancompare information from different sources, linking it with existing knowledgeand building new insights (Barrows, 1996).

The findings of this research show that when digital PBL tasks offer muchautonomy support but are unstructured they have little motivational merit andadd little educational value. So besides providing autonomy support a digitalPBL task also has to provide structure support. Probably this has something todo with cognitive load, as if students are offered choices without assistanceand guidance they get lost in all the possibilities available (Sweller, 2004). Anincreased degree of freedom can discomfit students (Hoffman & Richie, 1997).Many learners do not make effective choices and may experience informationoverload (Azevedo & Witherspoon, 2009; Liu & Bera, 2005; Narciss & Körndle,1998). Therefore, if teachers want to use digital learning tasks in the classroomeffectively they should be aware that such tasks support both autonomy byproviding choice, a rationale and non-directive language and also structuresupport by providing clear goals, expectations, consequences, guidance and clear procedures to students. Only when these two principles are appliedin combination is there a positive effect on the motivation and learning performance of students.

The technique supplied by digital learning environments provides all kindsof possibilities for meeting autonomy support and structure support. Throughthe use of hypermedia students have access to different information resources(i.e. texts, images, and video sequences) in a nonlinear way (Hoffman & Richie,1997), so they have plenty of choices, and the need for autonomy can be fulfilled. Hypermedia also offer computer-based cognitive tools which providestructure support and facilitate the learning process (Lajoie, 1993). Cognitivetools are computer-based instruments that assist learners in accomplishingcomplex cognitive tasks and decrease the cognitive load (Lajoie, 1993). For example, tools are a roadmap of the courses required to complete a task successfully and a template for interpreting and organizing information andpresenting methods for solving problems. These tools can fulfill students’ need for competence.

Because the expectation is that in the next few years digital learning inschools will increase and teachers will become more skilled in designing theirown digital learning tasks using, for example, sites such as Wikiwijs.nl, it is im-portant that teachers know how to deploy digital learning tasks in a didacticand effective way. Mere attractiveness is not sufficient; the specific underlying



didactical principles of the task such as autonomy support and structure sup-port help to make the task motivating and informative.

Professionalization challengeCreating a learning environment that motivates students demands new know -ledge and skills of teachers. How teachers can be professionalized most effec-tively is the question. Research shows that changing the educational behaviorof teachers is a very complex matter (Fullan, 1991).

The training described in the study, focused on changing teacher behaviorin the class, was done with the whole team of teachers and took place inschool. Previous research shows that this ensures a sustainable change ofteacher behavior because professional development must be conceptualizedas a learning process that is embedded within the context of the school, involves the formation of professional learning communities and takes place inthe workplace (e.g. Putnam & Borko, 2000; Sleegers, Bolhuis, & Geijsel, 2005;Smylie & Hart, 1999) instead of workshops or courses outside the school(Borko et al., 2010).

The results indicate that successful training according to teachers, is intense in nature (intensity), gives teachers opportunities for “hands-on” work(active learning), is integrated into the daily life of teachers (integration intodaily work) and builds on the previous knowledge of teachers (coherence). Theimportance for active learning is in line with previous research that indicates,that to translate the complex nature of teacher development, PDPs should beclosely aligned with a constructivist approach (Borko et al., 2010). This meansthat teachers are given the opportunity to discover knowledge through theirown active exploration (Slavin, 1994) and activate their own prior conceptionsand relate them to new knowledge (Järvelä & Niemivirta, 1999).

Because teachers’ learning is a complex process (Clarke & Collins, 2007;Collins & Clarke, 2008) the focus must not only be on knowledge but also onskills and attitude (Bergenhenegouwen & Mooijman, 2010). Knowledge isneeded to link new information in a larger framework consisting of insights. Skillsare important for the exercise of new insights in practice. Attention to attitude isessential for awareness of the implicit images a teacher has about what is goodfor students and to provide fresh insights. The principles of teachers’ professio -nalization in this research appeal for these various aspects. The knowledge ele-ment is accommodated by the coherence principle: new information is linked toexisting knowledge. Opportunities for practicing new skills in the classroom are given by the principles of active learning and integration in daily work, andattention to attitude is met by the principle of opportunities for reflection.

Although reflection is not the most important principle, teachers with an



average start situation and a high increase in autonomy-supportive and struc-ture-supportive skills attach more value to reflection than teachers with a highstart situation and low increase. This is consistent with the finding that designprinciples are not always equally important for all teachers but must be differ-entiated depending on the needs of the teacher (Opfer & Pedder, 2011).

In summary, as regards the professionalization of teachers it is important tomeet the principles but also differentiate in the needs of teachers and the purpose of training. So for the understanding of what determines teachers‘learning the characteristics of individual teachers should also be included. Thisincreases the chance that the professionalization of teachers is effective and asa consequence students benefit.

Research challengeBecause this research aims to contribute to the improvement of teaching practice, and to increasing scientific insights, a practice-based scientific research approach was chosen. Often there is a gap between educationalpractice and educational research and the impact of scientific research on educational practice is disappointing (Broekkamp & van Hout-Wolters, 2006;Martens, 2010; Onderwijsraad, 2011). This research has tried to take the complexity and context of the daily practice into account. The research hasyielded important additions to SDT. The principles of autonomy support andstructure support were applied and investigated in a regular classroom situation,and the feasibility of applying these principles to teachers was considered.

There are two kinds of quality criteria for practice-based scientific research,according to Verschuren (2009) (cf. Martens, Kessels, de Laat, & Ros, 2012; Ros& Vermeulen, 2010). Because the present study is about scientific research thebasic criteria have been fulfilled (internal validity, external validity, control -lability, cumulativity and ethical aspects). The extent to which the study complies with these basic criteria is discussed further in the limitations section.As regards the usability criteria, this research tries to comply as much as pos -sible with the features that are specific to practice-based scientific research.How the research meets the usability criteria is described below.

1. Understandability of research resultsThe results are understandable and accessible for the educational field. In thisresearch the results are disseminated in multiple ways. Examples include Dutchlanguage publications, presentations and tools including a checklist, onlinetraining, and an observation list. These are the practice-oriented products thatemerged from this dissertation.



2. Acceptance and experienced legitimacyThe educational field experienced the results as true, relevant and legitimate.Schools indicated the problems and challenges related to students’ motivationand were involved at an early stage in the formulation of the research ques-tions. The research was carried out at these schools and the results discussedwith teachers about how they could fit these in daily classroom practice.

3. Learning opportunitiesThe research has produced knowledge to improve teaching practice. Some ofthe instruments which were developed for data collection could also be usedas a reflective tool for teachers‘ use in daily practice, independently of the research. Examples include a checklist to assess the quality of a digital task andan observation list to determine the autonomy-supportive and structure-sup-portive behavior of teachers. There were also learning opportunities createdfor schools by training of teachers, by practical recommendations and by conversations with teachers about the combination of autonomy support andstructure support.

More intensive forms of data collection were used, for example obser vations,with multiple view points (of students, teachers and objective observers) andrepeated measurements, to achieve a good understanding of the processesand an integral view of classroom practice and better understanding of thatcomplex reality (Martens et al., 2012). Although little qualitative research hasbeen done, this multi-method approach means that relationships between vari-ables were addressed.

In summary it can be stated that in different ways, before, during and aftercompletion of the research the impact on practice has been taken into account. The ambition was to meet the criteria of practice-based scientific research. The point of departure was the real problems of teachers which werealso translated into theoretically interesting problems that could be investi-gated. The research provided a valuable contribution to knowledge, profes-sional development and tools for the participating schools.

6.4 Limitations and Directions for Future ResearchThe research reported and discussed in the current thesis has some limitationsand suggests areas for future research.

In the study of teachers’ training, the data could not be compared withthose of a group of teachers who were not trained. This limitation was partiallyovercome by the use of multiple methods of data collection (triangulation). Thevariables of autonomy support and structure support were operationalized from



multiple perspectives, namely, teachers’ perceptions, perceptions of studentsand assessments by objective observers. That does not mean that in the futuredata can also be collected on the basis of an experimental and control group.

Although the number of students in this research is large, the number ofteachers and schools is very small. Only one secondary school participated inthe research. For future studies that will replicate this research, it is recom-mended to include more teachers and schools.

With regard to digital learning, the study consisted of a relatively short task that students completed in approximately an hour and a half. In future research, the effects of autonomy support and structure support on studentmotivation and learning performance should be examined in digital tasks ofvaried duration that require students to spend more time completing them.Learning outcomes of students are measured by scoring student presentations,so there is a limited image of the acquired knowledge of pupils. For a betterview of the knowledge that students have gained, student performance in thefuture should be measured in a number of ways.

In this research intrinsic motivation was measured by the Intrinsic Motiva-tion Inventory (IMI) (Ryan, 1982). Although this is an internationally validatedand reliable instrument, it constitutes a limited operationalization of motiva-tion. To understand better why students are motivated or not, the underlyingmotives of students should also be measured. More qualitative research isneeded to define the underlying motivational processes of students.

The dimensions of autonomy support and structure support in this researchwere measured by the Teacher as Social Context Questionnaire (Belmont et al.,1988), but the different aspects of the dimensions autonomy support andstructure support (for example providing a rationale, offering option choices orproviding clear goals) in terms of motivation and learning performance havenot been studied. Follow-up work should investigate the contributions of specific aspects of autonomy support and structure support to clarify themechanisms underlying the relationships found. For example, it is possible thatthe learning goals, one aspect of structure support, explained the effect onmotivation to a greater extent than other structural aspects. Unfortunately, theinvestigation of this possibility fell beyond the scope of this research. Thus, future research should take into account the effect of specific aspects of auto -nomy support and structure support to clarify the exact ways in which these dimensions have an effect on the motivation and learning performance of students.

In contrast to perceived autonomy and competence of students, related-ness was disregarded in this research. The rationale behind this is that related-ness is not specifically task-oriented, but more a general pedagogical



condition in the school climate. Relatedness is necessary in order to learn. Because perceived relatedness is not measured, it could not be estimated towhat extent all pupils experienced sufficient relatedness in the classroom, andtherefore research results related to intrinsic motivation could have been affected in a negative or a positive way. Relatedness is now mainly associatedwith relations with teachers and fellow students, but the rise of social mediameans it will also play a greater role in the digital learning environment. Itwould therefore be interesting to examine the role of relatedness in the use ofsocial media in the classroom in further research.

In addition, it is important to consider the context in which the researchtook place. Most of the schools in this research work according to construc-tivist learning principles so they mainly focused on conceptual knowledge. Inthese schools, students experience more autonomy than do those in otherschools. Because students are more comfortable dealing with autonomy support, this could have affected the results. In follow-up research it would beadvisable to involve schools with different backgrounds, not only those who already work on autonomy support but also the more traditional schools wherethis is less common.

All limitations considered, it can be stated that more research is needed toexamine the underlying motivational and learning processes of students, theeffect of specific aspects of autonomy support and structure support and therole of relatedness. Therefore future research should include more teachersand schools with different backgrounds and the use of qualitative as well as experimental methods.

6.5 Theoretical and Practical ImplicationsIt has become clear that a learning environment that combines autonomysupport and structure support contributes to the motivation and performanceof students in terms of digital learning and learning in the class. Because research on the impact of autonomy support and structure support on moti -vation and learning is scarce (Jang et al., 2010; Sierens et al., 2009; Taylor &Ntoumanis, 2007) and has not been previously studied in the context of digitallearning (Chen & Jang, 2010), this research contributes to the further sub -stantiation and operationalization of SDT in educational settings. Previousstudies on SDT have only looked at providing autonomy support (deCharms,1976; Reeve, 1998; Reeve et al., 2004b; Su & Reeve, 2011) and are less focused on the combination with structure support. The fact that structure support contributes to a greater sense of competence among students is under exposed in the theory of self-determination, perhaps because it is as-sumed that this will thwart the autonomy of students. In contrast, this research



shows that both autonomy support and structure support are two separate dimensions of a learning environment that motivates students; they are comple-mentary.

This research also shows that teachers can be trained to apply autonomysupport and structure support in their digital learning tasks and in their be ha -vior in the classroom. To train teachers effectively it is important to join theseveral design principles (intensity, active learning, integration into daily workand coherence) on which the training is based. The findings build on theknowledge about sustainable professional development of teachers which suggests that there must be a focus on classroom practice and the formationof professional learning communities instead of workshops or courses outsidethe school (Borko et al., 2010; Putnam & Borko, 2000; Sleegers et al., 2005;Smylie & Hart, 1999).

The dissertation has not only theoretical relevance but also important practical implications. Teachers are given insights for providing autonomy support and structure support to improve the motivation and performance ofstudents. It is not a matter of either autonomy support or structure support, butof striking the right balance between the two so the learning environment isconsistent and clear and students are better able to make appropriate choices.In general, teachers support autonomy when they nurture students’ inner moti-vational resources by providing options, communicate rationales for activities,and rely on non-directive language. Teachers support students’ competence bymeans of clearly stated learning goals, expectations, consequences, guidance,and procedures. This thesis provides specific guidelines on how to design digitallearning tasks, so that teachers not only take advantage of the appealing ap-pearance or novelty of the technology but also the didactic and educational sub-stance of digital tasks that improve motivation and promote learning.

The research findings will also help teacher trainers to design effective professionalization programs. Besides the fact that several important designprinciples can be distinguished in the professionalization of teachers, thereshould be differentiated between the needs of teachers

Finally, this research shows that it is possible to do practice-based scientificresearch. Because there is attention to the needs of teachers, the findings are,we hope, more practicable for schools and more valuable for teachers. To makeresearch practice-based it is important that the usability criteria are met. This requires teachers and researchers to adopt another role; they should cooperatemore, so researchers can understand what education really needs and teacherscan obtain knowledge about new insights to solve daily problems.



6.6 Concluding RemarksMotivation problems of students in education are often underexposed. It is important that teachers know how to create the right conditions to facilitatelearners’ motivation. This research shows that a right balance between auto - nomy support and structure support is essential. In schools it is often apparentthat teachers struggle between these two dimensions. Teachers who only payattention to freedom of choice and do not offer structure because it would disrupt the autonomy of students provide an environment that is permissive oreven laissez-faire. In contrast to teachers with a high degree of structure sup-port, but who do not support students’ inner endorsement of their classroomactivities, a controlling learning environment is ensured. This research con-tributes to resolving this apparent paradox. Autonomy and structure are notopposing but complementary concepts. When teachers provide students withboth autonomy and structure, there are opportunities for choice, voice and initiative within a safe and predictable environment, with a positive effect onmotivation and learning.

In this thesis, there is not only evidence from theory that autonomy andstructure can be combined, but it is also demonstrated that this works in practice and that teachers are able to achieve this in their daily practice.



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Summary (in Dutch)

Elke leraar droomt van gemotiveerde leerlingen in de klas die met plezier naarschool gaan en graag willen leren. Als leerlingen gemotiveerd zijn, zijn ze betrokken, nieuwsgierig en zijn ze beter in staat om te gaan met uitdagingenen tegenslagen. Ook halen gemotiveerde leerlingen vaak betere schoolresul -taten. In de praktijk blijkt echter dat leerlingen vaak niet gemotiveerd zijn. Gedurende hun schoolloopbaan neemt de motivatie af, vinden leerlingen hetsaai op school en zijn ze minder betrokken bij schoolse taken.

Leraren vragen zich vaak af wat ze hieraan kunnen doen. Een mogelijkheiddie leraren hebben om leerlingen te motiveren is de inzet van Informatie enCommunicatie Technologie (ICT) in de klas. In de laatste decennia is er eengrote toename van ICT en digitale toepassingen in scholen. De niet-lineaire,associatieve en interactieve mogelijkheden van multimedia geven leer lingende mogelijkheid om op basis van hun eigen interesses en leerbehoeftennieuwe informatie op te doen. De verwachting is dat, met de toename van dedigitale mogelijkheden in de klas, leraren zelf ook meer digitale leertaken voorleerlingen zullen gaan ontwerpen, waaronder bijvoorbeeld leertaken die zijngebaseerd op Probleem Gestuurd Leren (PGL). Bij digitale leertaken geba-seerd op PGL, ligt de nadruk op het verwerven van conceptuele kennis doorhet oplossen van complexe problemen in rijke contexten.

Ondanks het potentieel van digitale leertaken blijkt dat de inzet van dezetaken niet automatisch leidt tot gemotiveerde leerlingen en doeltreffend on-derwijs. Onderzoek toont aan dat de kwaliteit van digitale leertaken, gemaaktdoor leraren, vaak van een laag niveau is. Taken zijn vaak onduidelijk wat be-treft hun leerdoelen en ze bieden onvoldoende houvast voor een gestructu-reerd en resultaatgericht leerproces. Leerlingen hebben vaak zoveelkeuzemogelijkheden dat ze een overload aan informatie ervaren. Het creërenvan een leeromgeving die leerlingen motiveert, vraagt nieuwe kennis en vaar-digheden van leraren. De vraag is hoe leraren zo effectief mogelijk kunnenworden geprofessionaliseerd, zodat deze leeromgeving ook gerealiseerdwordt. Professionalisering van leraren blijkt echter complex. Om ervoor te zor-gen dat leraren daadwerkelijk ander gedrag vertonen in hun dagelijkse prak-tijk, is het van belang dat de professionalisering plaatsvindt in de klas, in plaatsvan workshops of cursussen buiten de school.

In dit onderzoek staat de vraag centraal hoe leraren de motivatie bij leer -lingen kunnen bevorderen, zowel met als zonder ICT, en hoe ze hierin kunnenworden geprofessionaliseerd. Om deze vraag te beantwoorden maken we gebruik van uitgangspunten en inzichten van de Zelf-Determinatie Theorie(ZDT) van Ryan en Deci. Deze theorie geeft aan dat de leeromgeving moetvoldoen aan drie psychologische basisbehoeften om de intrinsieke motivatievan leerlingen aan te spreken. Intrinsieke motivatie is de natuurlijke neiging


Summary

van een leerling om activiteiten uit te voeren vanwege het inherente plezierdat wordt beleefd bij het uitvoeren van de activiteit. Dit in tegenstelling tot extrinsieke motivatie, waar gedrag is gebaseerd op externe beloningen. Extrinsieke motivatie wordt gezien als inferieur aan intrinsieke motivatie. Depsychologische basisbehoeften zijn de behoeften aan autonomie, competentieen sociale verbondenheid. De behoefte aan autonomie betreft een gevoel vaneigenaarschap over je gedrag. De behoefte aan competentie betreft de erva-ring dat je je bekwaam voelt om een activiteit uit te voeren en sociale verbon-denheid wordt gedefinieerd als “het gevoel je verbonden te voelen metanderen”.

In dit onderzoek concentreren we ons op autonomie en competentie. Alsleraren de intrinsieke motivatie van leerlingen willen aanspreken dan zullenhun gedrag en de leeromgeving autonomieondersteuning moeten bieden om aan de basisbehoefte van autonomie te voldoen en structuurondersteuning moeten bieden om aan de basisbehoefte van competentie te voldoen.

Autonomieondersteuning houdt in dat leerlingen een zekere mate vankeuzevrijheid wordt geboden, dat er uitleg wordt gegeven over het belangvan een activiteit en dat het taalgebruik niet directief is. Omdat autonomie -ondersteunende leeromgevingen voor veel associatieve afleiding kunnen zorgen en leerlingen overladen met keuzes, moet er naast autonomie ookstructuur worden geboden. Het bieden van structuurondersteuning betekentdat leraren hun doelstellingen en verwachtingen duidelijk kenbaar maken enexpliciet beschrijven wat de consequenties zijn van het wel of niet behalen vandeze doelstellingen. Bovendien kunnen leraren structuurondersteuning biedendoor het geven van hulp en begeleiding, en door het verstrekken van duide-lijke procedures zodat leerlingen beter weten hoe ze de doelen kunnen berei-ken. In het algemeen zijn leraren geneigd te denken datautonomieondersteuning en structuurondersteuning twee conflicterende principes zijn. Het tegendeel is waar, het zijn twee complementaire basis -behoeften. Ondanks het belang van een autonomieondersteunende leeromge-ving in combinatie met een structuurondersteunende leeromgeving is er nogweinig onderzoek gedaan naar wat dit betekent voor leerkrachtgedrag, digi-taal leren en het professionaliseren van leraren in de toepassing hiervan. In ditproefschrift is geprobeerd een antwoord te formuleren op de volgende onder-zoeksvragen: 1. Aan welke kenmerken moeten digitale leeromgevingen voldoen om een

positief effect te hebben op de motivatie en leerprestatie van leer lingen? 2. Kunnen leraren autonomieen structuurondersteuning in hun digitale

leertaken toepassen zodat leerlingen meer autonomie, competentie enmotivatie ervaren?


Summary

3. Kunnen leraren getraind worden in het ontwikkelen van een leerkrachtstijlwaarin zij leerlingen autonomie en structuur bieden, zodat leerlingen meerautonomieondersteuning, structuurondersteuning en motivatie ervaren?

4. Welke aspecten van de training hebben volgens leraren bijgedragen aanhun professionele ontwikkeling gericht op het bieden van autonomie enstructuur?

De onderzoeksaanpak om bovenstaande vragen te beantwoorden, kan getypeerd worden als praktijkgericht wetenschappelijk onderzoek. Het primaire doel van praktijkgericht wetenschappelijk onderzoek is praktischeproblemen van leraren oplossen en bijdragen aan de verbetering van het onderwijs op een wetenschappelijke manier. Bij praktijkgericht wetenschap -pelijk onderzoek is het vertrekpunt de problemen in de praktijk, met aandachtvoor de onderwijscontext en gericht op bruikbare oplossingen.

In hoofdstuk twee van het proefschrift wordt de eerste onderzoeksvraagbeantwoord door middel van een experimenteel design waarvoor variantenvan eenzelfde digitale leertaak zijn ontwikkeld. Het onderzoek is uitgevoerd bijleerlingen in de bovenbouw van het primair onderwijs. Het blijkt dat een digi-tale leertaak, gekenmerkt door zowel autonomieondersteuning en structuuron-dersteuning een positief effect heeft op de motivatie van leerlingen. Zelfs alsde taak slechts autonomieondersteuning óf structuurondersteuning bevat, zijnde leerlingen significant meer gemotiveerd dan in de conditie waar dit beidenontbreekt. Voor leerprestaties geldt dat een digitale leertaak die zowel auto-nomie als structuur biedt, bijdraagt aan hoge resultaten. Een digitale leertaakdie alleen structuurondersteuning verleent heeft ook een positief effect op deleerresultaten, echter een digitale leertaak met slechts autonomieonder -steuning heeft geen positieve invloed op de leerresultaten. Een mogelijke verklaring voor deze bevinding is dat wanneer leerlingen werken aan een digitale leertaak met alleen autonomieondersteuning en geen structuuronder-steuning, verward kunnen raken door de opties die worden geboden en doordat ze geen hulp krijgen in hun keuzeproces, het leerdoel uit het oog verliezen en minder efficiënt zich nieuwe kennis eigen maken.

Hoofdstuk drie is een vervolg op het onderzoek uit hoofdstuk twee. Hierinstaat de vraag centraal of leraren de principes van autonomieondersteuning en structuurondersteuning in digitale leertaken die zij zelf ontwikkelen, kunnentoepassen zodat leerlingen meer autonomie, competentie en motivatie bijdeze taken ervaren. Hiervoor zijn leraren in het primair- en voortgezet onder-wijs getraind. Leraren hebben na de training hun zelfontworpen leertaken aan-geboden aan de leerlingen in hun klas. Het blijkt dat leerlingen bij het makenvan deze digitale leertaken meer autonomie, competentie en motivatie erva-ren dan bij de taken die ze kregen aangeboden voordat de leraren waren ge-


Summary

traind. Basisschoolleerlingen hebben in het algemeen een groter gevoel vanautonomie, competentie en motivatie bij de digitale leertaken dan leerlingenin het voortgezet onderwijs. Dit is in overeenstemming met eerder onderzoekdat laat zien dat leerlingen in het voortgezet onderwijs minder gemotiveerdzijn dan leerlingen in het primair onderwijs. De mogelijke oorzaak van deze lagere motivatie is dat leraren in het voortgezet onderwijs minder autonomieen structuur bieden. Door de training hebben leraren in het voortgezet onder-wijs echter meer leerwinst geboekt dan leraren in het primair onderwijs.

In hoofdstuk twee en drie is het effect van autonomieondersteuning enstructuurondersteuning bij digitale leertaken onderzocht, in hoofdstuk vier envijf staat het gedrag van leraren centraal. Onderzocht is of leraren in het primair onderwijs kunnen worden getraind in het bieden van autonomie enstructuur aan leerlingen tijdens lessen wereldoriëntatie, zodat leerlingen meerautonomieondersteuning, structuurondersteuning en motivatie ervaren. Leraren zijn getraind in hun autonomieondersteunende en structuuronder -steunende vaardigheden. De training duurde een jaar en bestond uit team -bijeenkomsten en coaching in de klas. Op basis van literatuurstudie gericht opkenmerken van effectieve trainingsprogramma’s zijn zeven ontwerpprincipesvastgesteld. Deze vormden het uitgangspunt van de opzet van de training.Hoewel eerder onderzoek aantoont dat het niet gemakkelijk is leraargedrag teveranderen, geven leraren zelf aan na een jaar meer autonomieondersteuningen structuurondersteuning te bieden aan de leerlingen in hun klas. Objectieveobservaties bevestigen dit beeld. Verder blijkt dat leerlingen na een jaar meerstructuurondersteuning van hun leraren ervaren en gemotiveerder zijn voor delessen wereldoriëntatie. Echter leerlingen ervaren niet meer autonomieonder-steuning. Een verklaring hiervoor is dat autonomieondersteuning minder waarneembaar is voor leerlingen dan structuurondersteuning. Autonomie -ondersteuning betekent dat leerlingen meer vrijheid krijgen in hun manier vanleren. Dit is waarschijnlijk minder herkenbaar dan vormen van structuuronder-steuning waarbij het gaat om duidelijke doelen, verwachtingen, consequen-ties, begeleiding en procedures.

In hoofdstuk vijf wordt onderzocht welke ontwerpprincipes van de trainingin hoofdstuk 4 volgens leraren hebben bijgedragen aan hun professionele ont-wikkeling. Het blijkt dat er vier ontwerpprincipes zijn die volgens leraren, hetmeest hebben bijgedragen aan hun ontwikkeling gericht op het bieden vanautonomie en structuur. Dit zijn: de intensiteit van het programma, mogelijkhe-den om actief te leren, de mogelijkheid om het geleerde toe te passen in deklas en dat de training aansluit bij de voorkennis van leraren. De drie overigeontwerpprincipes: het feit dat leraren als schoolteam deelnemen aan de trai-ning, werkvormen gericht op reflectie en het zien van autonomieen structuur-


Summary

ondersteunende voorbeelden, werden als minder belangrijk beschouwd. Uitnadere analyse blijkt dat deze drie principes verschillend worden gewaardeerddoor leraren met een lage, gemiddelde en een hoge beginsituatie – en dieveel of weinig hebben geleerd van de training.

Concluderend kan op basis van dit proefschrift worden gesteld dat om gemotiveerd leren te bevorderen, de digitale leeromgeving en leraren zelfzowel autonomie als structuur moeten bieden. Leraren denken in het alge-meen dat autonomieondersteuning en structuurondersteuning twee conflic -terende principes zijn. In feite bevestigt dit onderzoek dat dit tweeafzonderlijke dimensies zijn die samen zorgen voor gemotiveerde leerlingen.Hoewel het niet gemakkelijk is om gedrag van leraren te veranderen, toont ditonderzoek aan dat leraren getraind kunnen worden om autonomie in combi -natie met structuur te bieden zodat leerlingen meer autonomie, competentieen motivatie ervaren. Het onderzoek toont aan dat door een juiste inzet vanICT en leraargedrag in de klas, er een bijdrage kan worden geleverd aan hetoplossen van het motivatieprobleem van leerlingen op school. Dit proefschriftheeft naast theoretische inzichten ook praktische handvatten opgeleverd waardoor leraren beter zijn toegerust om een motiverende en leerzame leer-omgeving te creëren.


Summary



Curriculum Vitae

Anne-Marieke van Loon was born on December 29, 1980, in Roosendaal, The Netherlands. After pre-university secondary education, she completed her Bachelor’s degree in 2002 as a primary school teacher at Fontys PABOin ‘s-Hertogenbosch. Afterward, she studied pedagogy while working as a primary school teacher. In 2005, she completed her Master’s degree in Educational Science at Radboud University Nijmegen and began working asa educational psychologist at De Kempen, Schoolbegeleidingsdienst in Eersel.From 2006 onward, she has worked as an educational consultant and researcher at KPC Groep in‘s-Hertogenbosch while completing her Ph.D. research at the Open University in Heerlen on student motivation and the role of autonomy support and structure support.

In May 2013 Anne-Marieke will start as a teacher educator at HAN Universityof Applied Sciences in Nijmegen.


Curriculum Vitae

List of publications and presentations


List of publications and presentations

Van Loon, A.-M. (2010, November). Effective Digital Learning Tasks: Their Impact on Learning and Motivation. Paper presented at the European Association for Practitioner Research on Improving Learning Conference,Lisbon, Portugal.

Van Loon, A.-M. (2011, June). Autonomieondersteunend en structurerend leerkrachtgedrag [Autonomy-supportive and structure-supportive teacherbehavior]. Paper presented at the Onderwijs Research Dagen, Maastricht,the Netherlands.

Van Loon, A.-M. (2011, November). Promoting teachers’ autonomy supportiveand structuring behavior: effective design principles. Paper presented atthe European Association for Practitioner Research on Improving LearningConference, Nijmegen, the Netherlands.

Van Loon, A.-M. (2012, November). Designing Digital Problem Based LearningTasks that Motivate Students. Paper presented at the European Associa-tion for Practitioner Research on Improving Learning Conference,Jyväskylä, Finland.

Van Loon, A.-M., Ros, A., & Martens, R. (2012, March). Autonomieonder -steuning en structuur in digitale leertaken. Presentation at Katholieke Universiteit Leuven, Kortrijk, Belgium.

Van Loon, A.-M., Ros, A., & Martens, R. (2012). Motivated learning with digitallearning tasks: what about autonomy and structure? Educational Technology Research and Development, 60(6), 1015-1032.

Van Loon, A.-M., Ros, A., & Martens, R. (2013). Characteristics of an effectiveteacher professional development program on students’ motivation. Manuscript submitted for publication.

Van Loon, A.-M., Ros, A., & Martens, R. (2013). Designing digital problembased learning tasks that motivate students. Manuscript submitted forpublication.

Van Loon, A.-M., Ros, A., & Martens, R. (2013). Training teacher’s autonomy-supportive and structure-supportive behavior. Manuscript submitted forpublication.

Acknowledgements (in Dutch)

Het is zover.. m’n proefschrift is af. In 2009 ben ik als buitenpromovenda begonnen bij het Wetenschappelijk Centrum Leraren Onderzoek (LOOK) van de Open Universiteit in Heerlen. Ditin combinatie met mijn werk als onderwijsadviseur bij KPC Groep. Nu vier jaarlater, kijk ik terug op een leerzame en vruchtbare periode.

Graag wil ik mijn dank uitspreken voor iedereen die me geholpen heeft tijdenshet voltooien van dit proefschrift. Op de eerste plaats gaat mijn dank uit naarmijn promotoren Rob en Anje. Rob, bedankt voor al je inhoudelijke input, je interessante gedachten over onderwijsvernieuwing en relevantie van onderzoek voor de onderwijspraktijk.Bedankt ook voor je opbouwende feedback, je oog voor detail en de ruimteen autonomie die je me gaf om m’n promotietraject te doorlopen. Anje, bedankt voor al je hulp en begeleiding. Door jouw praktische instekenen geboden structuur werden de doelen realistisch en haalbaar. Je hebt megeholpen om prioriteiten te stellen waardoor zaken overzichtelijk en behap-baar werden. Ik ben je niet alleen dankbaar voor je pragmatische insteek, maarook voor het optimisme en vertouwen in mij gedurende het promotietraject.Ook jouw gezelligheid heeft ertoe bijgedragen dat het steeds weer leuk wasom te overleggen.

Ook wil ik graag mijn (oud)leidinggevenden bij KPC Groep bedanken die hetmede mogelijk hebben gemaakt om dit onderzoek uit te voeren: Jan Arts,Paul Bemelen, Iwan Basoski, Marius Berendse, Lia van Meegen en Johan vander Horst. Maar ik denk hierbij ook aan mijn onderzoekscollega’s, waar ik deafgelopen twee jaar intensief mee heb mogen samenwerken om praktijk -gericht onderzoek bij KPC Groep op de kaart te zetten: José, Ria, Jos, Marjan,Suzanne, Marieke, Mariëlle, Evelien en Linda. Graag wil ik Nell Toemen bedanken voor haar kennis en kunde op het gebied van het managen van R&D projecten en haar oog voor politiek-bestuurlijke verhoudingen.

Tevens wil ik graag een aantal collega’s noemen bij wie ik altijd een luisterendoor vond en met wie ik veel gezellige koffie- en theemomentjes heb door -gebracht: Sophie, Martine, Maartje, Laura, Hélène, Nanda en Simone. Annebedank ik voor haar creatieve inbreng. In het bijzonder wil ik Kris Verbeeck bedanken. Kris heeft me in contact gebracht met mijn promotor en me geïn-spireerd om meer te willen weten over wat auto nomie nu werkelijk betekent.


Acknowledgements

Natuurlijk ben ik ook veel dank verschuldigd aan de leraren en leerlingen diehebben meegewerkt aan mijn onderzoek. Met name basisschool Aan de Bronin Weert, wiens leraren een jaar lang hun deuren hebben opengesteld om depraktijk te onderzoeken, ben ik zeer erkentelijk. In het bijzonder wil ik hierbijook basisschool Wittering.nl in Rosmalen noemen. Dankzij de bevlogenheidvan de professionals was het een genoegen om de praktijk nader te beschou-wen. In dit kader wil ik Astrid van den Hurk en Toon Joosten bedanken, dankzijhun begeleidings- en advieswerkzaamheden op de scholen heb ik me kunnenrichten op de rol van onderzoeker.

Ik had mijn promotieonderzoek niet kunnen uitvoeren als er geen tijd voor ontspanning was geweest waarbij ik me opnieuw kon opladen en mijn werk-zaamheden kon relativeren. Ik wil dan ook graag mijn vrienden en familie bedanken voor al hun steun en gezellige momenten samen.

Speciale dank gaat uit naar mijn twee paranimfen, Mandy en Lorien, hartstikkefijn dat jullie me vandaag terzijde willen staan! Maar ik wil graag ook Annika,Jeannette, Edith, Mirjam, Judith en Annette bedanken voor hun vriendschapen steun. En niet te vergeten mijn vriendinnen van de middelbare school en demeiden van de uni, wat kennen we elkaar al een lange tijd.

Heel graag wil ik ook mijn familie en schoonfamilie bedanken. Lieve Chiel enMarja, bedankt dat jullie altijd klaar staan, de Donk voelt ook als thuiskomen.Marjolein, ik heb het getroffen met jou als zus. Als onderwijskundige methumor ben je altijd een geweldige sparringpartner voor mij! Lieve papa enmama, bedankt dat jullie er altijd voor mij zijn. Door jullie liefdevolle opvoe-ding en het vertrouwen in mij, kun je als kind de wereld aan!

En tot slot een heel groot dankjewel voor de twee liefste mannen in mijn leven:Wouter en Hugo. Lieve Wouter, bedankt voor het meelezen, mee denken en vragenstellen, zonder jouw steun en liefde was het me niet gelukt. En Hugo, jelaat de wereld stralen. Ik ben gelukkig met jullie!

Anne-Marieke van LoonRosmalen, 6 maart 2013


Acknowledgements

A problem which is often mentioned by teachers is that students are notmotivated. Also, research indicates that students’ motivation declines overtime. Teachers are a crucial factor in motivating students, both in terms oftheir behavior in the classroom and in designing digital learning tasks.

This dissertation is concerned with how appropriate teacher behavior anddigital learning tasks can be motivating and how teachers can be trainedin learning this behavior and designing these tasks. In general, striking theright balance between autonomy support and structure support isessential to promote students’ motivation.

As a result of the findings of this dissertation, the body of knowledge inthe field of student motivation will be expanded. This thesis offers someguiding insights and principles that teachers need to fit into their dailypractice in order to motivate students in their classes.

Motivated Learning: Balancing BetweenAutonomy and Structure

Mo

tivated Learning

: Balancing

Betw

een Auto

nom

y and Structure

Anne-M

arieke van Loo

n

Motivated Learning: Balancing BetweenAutonomy and StructureAnne-Marieke van Loon

Motivated learning omslag:Opmaak 1 27-03-2013 10:18 Pagina 1

motivated learning: balancing between autonomy and structure

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