student boredom

8/12/2019 Student Boredom

1/17

This article was downloaded by: [York University Libraries]On: 07 April 2014, At: 15:26Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

British Educational Research JournalPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/cber20

Boredom in the lecture theatre: aninvestigation into the contributor s,moderators and outcomes of boredomamongst university studentsSandi Mann a & Andrew Robinson aa Department of Psychology , University of Central Lancashire , UKPublished online: 20 Mar 2009.

To cite this article: Sandi Mann & Andrew Robinson (2009) Boredom in the lecture theatre: aninvestigation into the contributors, moderators and outcomes of boredom amongst universitystudents, British Educational Research Journal, 35:2, 243-258, DOI: 10.1080/01411920802042911

To link to this article: http: //dx.doi.org/10.1080/01411920802042911

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the Content) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,

and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever orhowsoever caused arising directly or indirectly in connection with, in relation to or arisingout of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions
http://www.tandfonline.com/page/terms-and-conditionshttp://dx.doi.org/10.1080/01411920802042911http://www.tandfonline.com/page/terms-and-conditionshttp://www.tandfonline.com/page/terms-and-conditionshttp://dx.doi.org/10.1080/01411920802042911http://www.tandfonline.com/action/showCitFormats?doi=10.1080/01411920802042911http://www.tandfonline.com/loi/cber20


2/17


3/17

external stimulation leads to increased neural arousal in search of varietyfailure tosatisfy this leads to the experience of boredom. OHanlon defined this as a uniquepsychophysical state that is somehow produced by prolonged exposure tomonotonous stimulation (1981, p. 54). Boredom is a distinct emotional state(Fisher, 1993; Farmer & Sundberg, 1986); boredom is an unpleasant, transientaffective state in which the individual feels a pervasive lack of interest in anddifficulty concentrating on the current activity [such that] it takes conscious effortto maintain or return attention to that activity (Fisher, 1993, p. 396).

This suggests that arousal may be affected by the meaning of the situation. If thestimulus means nothing to the individual or is perceived as less distinct andmonotonous, it gives rise to the state of boredom. A study by Perkins and Hill(1985) found that individuals who derive little enjoyment from thinking or fromincreasing their understanding of events around them were significantly more prone to

experiencing boredom. In addition, Csikszentmihalyi (1975) and Polly et al. (1993)believe that individuals who are more inclined to generate positive stimulation are lesslikely to experience boredom. Work by Fiske and Maddi (1961), Zuckerman (1979)and Watt and Blanchard (1994) have shown that boredom-prone individuals aredeficient at maintaining this adequate level of stimulation.

This, then, suggests that some people are more prone to boredom than others.Farmer and Sundberg (1986) developed the Boredom Proneness Scale as a generalassessment tool to measure a persons tendency towards experiencing boredom, andto discover a psychometrically determined scale of measuring ones proneness toboredom. They suggested that boredom proneness is a personality trait that canmoderate the experience of boredom and that the boredom-prone person is one whoexperiences varying degrees of depression, hopelessness, loneliness, distractibility, isless motivated and displays little evidence of autonomous orientation.

Boredom amongst students

In education, boredom has been linked with diminished academic achievement(Fogelman, 1976; Maroldo, 1986) and school dissatisfaction (Gjesne, 1977). Forexample, students who rated themselves as often bored had generally lower scores onacademic tests than those who were sometimes bored (Mikulas & Vodanovich, 1993).Other research has found a negative relationship between boredom susceptibility andgrade point average. Students who rated themselves as often bored had generally lowerscores on academic tests than those who were sometimes bored.

Student boredom has also been shown to be a contributor to truancy (e.g. Robinson,1975; Watt & Vodanovich, 1999). For example, boredom is one of the most frequentlyidentified causes for students leaving school temporarily (e.g. skipping classes, feigningillness) or permanently (Farmer & Sundberg, 1986; Larson & Richards, 1991).Students who do not miss classes have been shown to have higher performance scores(Robinson, 1975; Maroldo, 1986; Farmer & Sundberg, 1986; Mikulas & Vodanovich,

1993; Wallace et al. , 2003; Grabe, 2005; Handelsman et al. , 2005). As Fallis andOptotow (2003) point out in their study of high school students, class-cutting is aslippery slope: once begun, the academic damage is difficult to reverse (p. 104).

244 S. Mann and A. Robinson

w


4/17


5/17

2004) suggests that pictures are easier to remember than words and wheninformation coding is in both systems, like in PowerPoint, the information is easierto remember than information coded only in the verbal system. A study by Grabe(2005) showed that taught lectures with overhead presentation provide theopportunity to make detailed notes. In addition, students who used notes performedbetter in their examinations than non-note users.

However, in order to reduce boredom, students must be engaged in their learning;as Kanevsky and Keighley point out, learning is the opposite of boredom andlearning is the antidote to boredom (2003, p. 278). In an article published in TheGuardian (2003), mature student Tom Ward complains that whilst the increasinguse of PowerPoint in higher education is meant to enhance student learning, itfrequently has the opposite effect, inducing boredom, frustration and disengage-ment. The problem he found was that PowerPoint frequently fostered a teaching

environment in which tutors did not connect with their students by making eyecontact or engaging in exchanges. Instead, they just talked to the screen, read outmaterial on the screen and often presented far too much material because it was soeasy to do so; the presentations became a barrier between the teacher and thestudent and resulted in a learning environment that was so routine, so anodyne, sodull. Ward complains bitterly of the disk dealers whose efforts produce thatdreadful mask of passive boredom on students faces.

Part of the problem within higher education may lie within the traditional conceptionof the lecture, which implies a didactic transmission of material that students passivelyreceive. Indeed, the notion of university lecturers actually needing any sort of trainingin how to teach is a relatively new one; as an article in the Education supplement of TheGuardian points out, Teaching in a university remains a curious thing. Many peoplehave remarked on the fact that if you want to teach in a school you need a lengthy andintensive training, but to teach in a university you need a PhD, some red-hotrecommendations and a handful of decent publications (Wolff, 2006). Whilst mostuniversities do now provide training for teaching staff and a wider range of teachingmethods (and often use the term classes rather than lectures), teaching staff are stillcalled lecturers, so the traditional notion of teaching being a formal talk (as definedin the Chambers Dictionary ), is difficult to get away from.

Another issue that may be difficult to get away from is that of students viewing theteaching they are presented with purely as a means to obtain the information necessaryto pass examinations or coursework. In other words, students themselves may actuallyresist attempts at what Ramsden (2003) terms deep learning, i.e. where they approachtheir learning with the intention of understanding, in favour of more superficial surfacelearning in which there is an absence of the desire to understand. Students may bypassdeep learning, even if this underpins the teaching and learning strategy of theirinstitution, because university teaching contexts might discourage students fromcoming to grips with the fundamentals of their subject and encourage them to use tricks

and stratagems to pass examinations (Ramsden, 1984, p. 145). In other words,although there may well be stated course objectives and outcomes as part of theteaching and learning policy, students may want to find short-cuts and rules that will


w


6/17

simply enable them to pass, without the need to understand more than is necessary.That is, the surface learners are looking for the facts they think they will be tested on,not for the meaning of the material. According to Rhem (1995), studies show thatstudents in Australia adopt more and more surface approaches to learning as they movefrom high school to higher education because that is what they perceive as necessary forsuccess. Ramsdens work suggests that it is not enough to devise appropriate teachingmethods, but that teachers must examine their entire teaching and learning strategy soas to ensure that students are receptive to the kind of deep learning they are trying tofoster. It may be that students who are more receptive to deep learning will experienceless boredom within classes/lectures than those less receptive.

Consequences of boredom

Work by Sommers and Vodanovich (2000) found that people who suffer low arousallevels are more inclined to partake in coping strategies to alleviate their boredom.The employment of coping strategies involves the seeking of varied, novel, complexand intense experiences or sensation seeking (Greene et al. , 2000). Todman (2003)states that sensation seeking is caused by situation-dependent boredom as theindividual seeks relief from the boring situation. Work by Ferrell (2004) found thateverybody gets bored but different people have different ways of relieving thatboredom depending on their surroundings.

Sensation seeking can result in a relationship between boredom and riskybehaviours. For example, a number of researchers (e.g. Wallace et al. , 2003; Johnston & OMalley, 1986 as cited in Mikulas & Vodanovich, 1993; Watt &Blanchard, 1994) have reported boredom to be one of the most common causes of drug use. Greene et al. (2000) found that boredom has been linked with health riskbehaviours such as smoking, drug-taking, alcohol consumption and unsafe sex.

However, not all coping strategies involve risky behaviours. For instance, thesimple act of daydreaming and fantasizing can allow a person to alter the complexityof a situation and thus cope with the lack of stimulation (Tushup & Zuckerman,1977; Klinger, 1987). Ward (2003) observed first-hand the coping strategies thatstudents used to combat boredom:

Some dozed and daydreamed or doodled in time-dishonoured fashion; others tookrefuge in their mobile phones sending or reading text messages, or playing games. In thecorner in which I regularly sat, there were competitions of hangman, complete the songlyric, and quizzes of one sort or another. It was not long before this kind of subversionbecame more obvious as students started to skip classes. There were times whenattendance slumped to 50%. Some students even disappeared in the mid-session break,deciding that it wasnt worth staying and electing to do something else instead.

Current study

The current research into student boredom is lacking in a number of ways. Firstly,most of it concentrates on boredom in the classroom with school-age children, andthe current study aims to address this imbalance. Boredom at university level could

Boredom in the lecture theatre 247

w


7/17

have serious consequences for the young adults involved in terms of their academicsuccess. Because little is known of the experience of lecture-based boredom in highereducation, the aims of the current study are to (1) identify the factors that contributetowards and moderate the experience of student boredom (such as types of teachingenvironment and boredom proneness), and (2) to identify student coping strategiesand consequences of boredom.

Method

The study took a three-stage approach, with the first stage (Phase 1) taking the formof focus groups in order to help identify items for a broad questionnaire to be used inPhase 2. The results of Phase 2 were used to produce a more targeted questionnaireto be used in the main study (Phase 3).

Phase 1

Because little research to date has been carried out into the experience of boredomwithin higher education students, it was felt that an initial focus group stage shouldbe employed in order to more effectively develop a framework for the main study.Three groups of five students were recruited through opportunity sampling andasked to take part in a 20-minute discussion at a specified time and location.Participants in each group knew each other and were from a range of differentdisciplines. They were informed that their contributions were voluntary and

anonymous. The aim of the discussions was to identify items for inclusion inPhase 2; by holding the focus groups, it could be ensured that any items selectedwere generated by the target group of participants (i.e. students) rather than simplygenerated by the researchers or from previous research (which is scarce andinconclusive). Two main issues were discussed in the focus groups: coping strategiesduring a boring event (what do they do to relieve boredom during a boring lecture)and behavioural consequences of boredom (what they do after a boring day atuniversity). The following results were generated.

Question 1: If you find lectures boring, what do you do to relieve the boredom?

Responses mentioned by the participants included: play games on phone, textpeople, write shopping list, talk to neighbour, calculate finances, leave mid-session,stare into space, switch off, doodle, write notes to neighbour, colour in letters onhandout and decide not to attend the next lecture.

Question 2: After a particularly boring day at university, what do you feel the need to do?

Responses mentioned by the participants included: drink alcohol (alone), watch TV/

video/DVD, eat chocolate, play video games, phone friends, go to the library, goshopping, sleep, go out drinking, review the days lecture material, do somecoursework, smoke.


w


8/17

Phase 2

All the items generated in Phase 1 were put into a questionnaire that wasdistributed to 44 different students (i.e. who had not participated in Phase 1). The

aim of this phase was to identify from the original Phase 1 list those responses thatwere most prevalent for the main study. Phase 1 responses that were selected byless than 20% of the Phase 2 sample were not included in the main studyquestionnaire.

Main study

Participants

Two hundred and eleven students (66 male and 145 female) were recruited using

opportunity sampling at a university in the north-west of England. They wererecruited from general areas of the campus such as the Students Union or canteens,so that no one subject course area would dominate; data on subject studied were notcollected. The students invited to take part were not asked which year of study theywere in and it was assumed that participants across the range of year groups tookpart.

Materials

Each participant was given a questionnaire containing: (1) the instructions andinformation for the participant about their right to withdraw and their anonymity,(2) the shortened five-point Likert Boredom Proneness Scale (BPS) (permission touse granted by the authors) adapted slightly for student use (e.g. any items referringspecifically to work were changed to make them suitable for student life), (3)questions to assess how much time in lectures the student rates as boring, how muchtime they judge to have missed this academic year due to non-attendance, what Alevel or equivalent grades the participants obtained in order to gain access to auniversity course, and their boring ratings of various teaching methods, (4) questionsgauging the number of boredom coping strategies employed by the students during

the lecture.

Results

1. Experience of boredom

Table1 shows the responses that students gave to the question how much of yourlecture time do you rate as boring?

2. Factors contributing to student boredom: teaching elements

These items were scored on a 15 Likert scale and the distribution of scores is shownin Table 2.


w


9/17

3. Factors contributing to student boredom: boredom proneness

The internal consistency of the BPS in its original truefalse format has beenreported to be .79 (Farmer & Sundberg, 1986) and a KR-20 of .73 was reported by

Ahmed (1990). A testretest correlation of 0.83 was also reported after a 1-weekinterval (Farmer & Sundberg, 1996). The coefficient alpha of the revised five-pointversion of the BPS used in this study was somewhat lower at .58. The distribution of the boredom proneness scores is shown in Figure 1.

The boredom proneness scores were divided into three groups, high, medium andlow, according to standard deviation split. The mean score was 44.93 with astandard deviation (SD) of 11.93. Those participants scoring less than 1 SD belowthe mean were classified as low on BPS, those 1 SD above as high. Scores between32.97 and 56.83 points on the boredom proneness scale was classed as the middlegroup.

Table3 shows the distribution of boredom proneness scores.Results from a one-way analysis of variance (ANOVA) show that students who

score highly on the BPS rate more time in lectures as boring (mean 5 3.41,SD 5 1.13) than participants with low boredom proneness scores (mean 5 2.37,SD 5 0.81), (F (2, 210) 5 11.795, p5 .000).

Table 1. How much of students lecture time they rate as boring

% respondents

None of their lectures 2Some of their lectures 39Half of their lectures 29Most of their lectures 27All of their lectures 3

Table 2. Mean and standard deviations of boredom ratings of various teaching methods

Teaching method Mean SD

Laboratory work 3.33 3.05Computer sessions 3.17 2.51Online lecture notes 3.14 2.14Copying overheads in lectures 3.13 1.45PowerPoint without handout 2.98 1.2Workshops 2.97 2.61Video presentations 2.74 2.51Group work outside lectures 2.69 2.25PowerPoint with handout 2.6 1.35Seminars 2.57 1.7Practical sessions 2.41 2.54Group discussions in lectures 1.94 1.36

Higher scores, i.e. nearer to 5 5 higher boredom ratings.


w


10/17

A forward stepwise multiple regression analysis was performed to determine whichfactor contributed most to the boredom experienced in lectures ( Table5). Factors

entered were the five teaching methods rated the most boring (see Table 2) andboredom proneness. Before this was performed, a correlation matrix was producedbetween these variables to check for multi-collinearity. This is shown in Table 4.

4. Consequences of student boredom

A Pearson correlation shows that the more time in lectures rated as boring, the morelecture time students claim to have missed that academic year (r 5 0.17, p5 .016). Acorrelation was found between lecture time already missed and deciding to go to thenext lecture (r 5 .18, p5 .009). The more time is missed due to missing the nextlecture the more grade point average decreases (r 52 0.20, p5 .005).

Figure 1. Graph showing distribution of boredom proneness scores

Table 3. Distribution of boredom proneness scores

Number of respondents % respondents

Low boredom pronenessscore

35 16.6

Middle boredom prone-ness score

144 68.2

High boredom pronenessscore

32 15.2


w


11/17

However, boredom proneness had a moderating effect on these findings. When

boredom proneness is partialled out, the correlation between time in lectures ratedas boring and missing lecture time does not reach significance (r 5 0.096, p5 .165).Results from a one-way ANOVA confirm that students who score highly on the BPSadmitted to missing significantly more lecture time (mean 5 1.97, SD 5 0.74) thanstudents with low boredom proneness scores (mean 5 1.54, SD 5 0.51), (F (2,210) 5 3.61, p5 .029).

The influence of boredom proneness is also confirmed by the positive correlationbetween boredom proneness and time missed (r 5 0.18, p5 .008) and betweenboredom proneness and going to the next lecture (r 5 0.16, p5 .017), showing thatparticipants who score highly on the BPS spend less time in lectures.

Table 6 shows the percentage of students claiming to employ various copingstrategies during a boring lecture. One-way ANOVA results show that students whoscore highly on the BPS employed significantly more coping strategies in lecturetime (mean 5 5.97, SD 5 2.27) than students with low boredom proneness scores(mean 5 3.40, SD 5 2.56), (F (2,210) 5 10.20, p5 .000).

One-way ANOVA results show that individuals who are prone to boredom inlectures tend to play more games on their mobile phone (F (2,210) 5 4.015, p5 .019), send more text messages during lecture time (F (2,210) 5 4.196, p5 .016),make more shopping lists (F (2,210) 5 3.08, p5 .048), tend to switch off (F

(2,210) 5 5.62, p5 .004), doodle, (F (2,210) 5 4.29, p5 .015), write notes to theperson next to them (F (2,210) 5 6.71, p5 .001), daydream (F (2,210) 5 4.4, p5 .0.13), and decide not to go to the next lecture (F (2,210) 5 3.1, p5 .047) more

Table 4. Correlation matrix of main factors contributing to boredom in lectures

Computer Online notes Copyingoverheads

PowerPoint BPS

Lab work R 5 .43** R 5 .29** R 5 .06 R 5 .08 R 5 .09Computer R 5 .33 ** R 5 .045 R 52 .47 R 5 .03Online notes R 5 .02 R 5 .06 R 5 .006Copying over-heads

R 5 .32** R 5 .03

PowerPoint R 5 .08

**Correlation at the 0.01 level.

Table 5. Stepwise multiple regression of teaching methods and boredom proneness onto time inlectures rated as boring

Step Variable Beta R 2 R 2 change t Sig. t

1 BPS .414 .172 .172 6.58 , .00052 PowerPoint .164 .198 .027 2.63 , .0005

Final statistics: R 2 5 .164, F (2, 210) 5 25.7, p5, .0005.


w


12/17

than those students who score low on the BPS. The means and standard deviationsfor the low and high boredom prone group for these strategies is shown in Table7.

Discussion

1. The experience of student boredom

The findings suggest that 59% of students find at least half their lectures boring with30% (almost a third) claiming to find most or all their lectures boring. This seems anintolerably high percentage of boring lectures at university level, but these findingsneed closer examination before any conclusions can be drawn. One importantlimiting factor is that these were general estimates of time in lectures overall that thestudents reckoned, when looking back, were recalled to have been boring. Anotherlimiting factor could be the possibility that the data collected in this study may havebeen subjected to social desirability bias in that it may not be part of the student

Table 6. Percentage of students employing various coping strategies during boring lectures.

%

Daydream 75.4Doodle 66.4Switch off 61.6Colour in letters on the handout 59.7Talk to the person next to them 50.7Text people on mobile phone 45.5Write notes to friend 38.0Leave at break time 27.5Calculate money situation 23.2Play games on mobile phone 17.5Write shopping list 16.6

Table 7. Mean scores and standard deviations for strategies used by low and high boredom pronestudents

Strategy High BPS Low BPS

Mean SD Mean SD

Play games 0.28 0.45 0.029 0.17Text .059 0.5 0.26 0.44Shopping lists 0.28 0.46 0.06 0.24Switch off 0.88 0.34 0.54 0.5Doodle 0.75 0.44 0.46 0.51Write notes 0.63 0.49 0.2 0.41Daydream 0.72 0.46 0.57 0.5Skip next lecture 0.05 0.21 0 0


w


13/17

culture to be enthusiastic about lectures or classes. Specific lectures were not ratedand a useful amendment for future studies might be to ask students at the end of each lecture for their boredom ratings.

That said, the main factors that need to be considered in connection to thisfinding are contributing factors to the experience of student boredom. Two groupsof factors were considered in this study; those relating to the quality and intrinsicproperties of the lecture and those relating to the personal qualities of theindividual in terms of their boredom proneness. Each of these will be considered inturn.

2. Factors contributing to student boredom: qualities of the lecture

A range of different teaching methods was explored in terms of their contributions to

the experience of boredom by students. The highest boredom ratings were achievedfor laboratory work (mean 5 3.33) and computer sessions (mean 5 3.17), which issurprising given the hands-on nature of these teaching methods; it might be expectedthat these methods would be the most engaging, not the least. However, thesefindings do concur with the view expressed by the Higher Education Academys UK Centre for Materials Education, that students often find labs tedious and boringand do not take them seriously (Baillie & Hazel, 2006). One reason given by Baillieand Hazel (2006) is that many laboratory classes consist of controlled exercises,which are simple exercises designed by the teacher with the aim of verifyingsomething already known. Students, they say, can find these classes dull andtedious because of the predictability of the results and because they do not promoteRamsdens (1984) deep learning. More experimental designs are thought to be morestimulating and more likely to promote deep learning, but these require more in theway of time and resources.

Computer sessions too have the potential to be stimulating or tedious; the findingsof this study suggest that too many fall into the latter category. This could be due tothe manner in which computer sessions are conducted (e.g. are the computer tasksrelevant and interesting?), the resources available (e.g. is there a computer for eachstudent?), the availability of support (are there enough teaching staff to help

individual students?), etc. The fact that computers are a doing activity is clearly notenough to eliminate boredom, and this appears to be what Ramsden (1995, p. 4)means when he says that doing in itself isnt enough; although he was referringabout doing enough to promote deep learning, there is likely to be enough linkbetween interest, motivation and deep learning for this comment to apply equallyhere.

Online lecture notes (mean 5 3.14) and copying overheads in lectures(mean 5 3.13) come next in the boredom ratings and this is less of a surprise.These teaching methods are the least engaging and involve very little learner

engagement as the student simply copies material down. This task can be achievedwith little active processing or learning and thus can be expected to contribute tostudent boredom.


w


14/17

High up on the list of boring teaching methods is use of PowerPoint without ahandout (mean 2.98). Interestingly, providing a handout reduces the mean boredomrating to 2.6. The use of PowerPoint is discussed at length in the introduction to thisarticle and the reservations expressed by previous researchers (e.g. Bartlett et al. ,2000 and Ward 2003) in terms of over-reliance on this tool would appear to bejustified. Using PowerPoint presentations without an accompanying handout isclearly boredom-inducing, possibly because students are forced to copy everythingdown; copying notes in this way is only marginally less boring than copying old-fashioned overheads. The real power of PowerPoint seems to come with combiningit with the handout which, presumably, allows the student to concentrate on thematerial rather than on getting it all down on paper.

The least boring teaching methods were found to be seminars, practical sessions andgroup discussions. All these involve interaction and active learning rather than passive.

3. Factors contributing to student boredom: individual characteristics of the student

The boredom proneness of the students followed a fairly normal distribution (asshown in Figure 1). The results suggest that an individuals propensity towards thepersonality trait of boredom proneness has a large influence on their experience of boredom. High BP students rated more time in lectures as boring than low BPstudents, suggesting that boredom proneness is a significant predictor of experien-cing boredom in lectures.

A stepwise multiple regression was performed and two factors were shown to besignificant predictors of how much of lecture time students rated as boring. Thesefactors were boredom proneness (accounting for 17.2% of the variance) and theteaching method of PowerPoint without handout (accounting for a further 2.6 % of the variance). This suggests that these were the two main predictors of studentboredom, with boredom proneness being the most significant.

4. Consequences of student boredom

The effects of boredom for students fall into three categories of consequences: (1)

those relating to academic output and (2) those falling within the category of short-term coping strategies adopted during boring lectures.

Consequences relating to academic output. Correlational statistics suggest that lectureboredom has serious consequences for academic output, leading to students bothclaiming to have missed previous lectures and electing to miss future lectures.Previous research has shown a link between class attendance and grades achievedand this appears to be backed up in the current study, which found that the moretime missed, the lower the A level grade points were. However, caution should beexercised, since these grade points were obtained before commencing university so

could not be a direct consequence of missing boring lectures whilst at university.However, as there is a relationship between ratings of lecture boredom, missingclasses and previous grades, it could be that the experience of boredom is not


w


15/17


16/17

References

Ahmed, S. M. S. (1990) Psychometric properties of the Boredom Proneness Scale, Perceptual and Motor Skills , 71, 963966.

Baillie, C. & Hazel, E. (2006) Teaching materials laboratory classes. Higher Education AcademyUK, Centre for Materials Education. Available online at: http://www.materials.ac.uk/guides/labclasses.asp.

Bartlett, R. M., Cheng, S. & Strough, J. (2000) Multimedia versus traditional course instruction inintroductory psychology. Poster presented at the Annual American Psychological Association ,Washington DC, August.

Bartsch, R. A. & Cobern, K. M. (2003) Effectiveness of PowerPoint presentations in lectures,Computers and Education , 41, 7786.

Carlson, S. (2002) Wired to the hilt, Chronicle of Higher Education , A33A35.Cassady, J. C. (1998) Student and instructor perceptions of the efficacy of computer-aided

lectures in undergraduate courses, Journal of Educational Computing Research , 19, 175189.Csikszentmihalyi, M. (1975) Beyond boredom and anxiety (San Francisco, CA, Jossey-Bass).Fallis, R. K. & Optotow, S. (2003) Are students failing schools or are schools failing students?

Class cutting in high school, Journal of Social Issues , 59(1), 103119.Farmer, R. & Sundberg, N. D. (1986) Boredom proneness; the development and correlates of a

new scale, Journal of Personality Assessment , 50, 417.Ferrell, J. (2004) Boredom, crime and criminology, Theoretical Criminology , 8(3), 287302.Fisher, C. (1993) Boredom at work: a neglected concept, Human Relations , 46, 395417.Fiske, D. W. & Maddi, S. R. (1961) Functions of varied experience (Homewood, IL, Dorsey Press).Fogelman, K. (1976) Bored eleven-year olds, British Journal of Social Work , 6, 201211.Grabe, M. (2005) Voluntary use of online lecture notes: correlates of note use and note use as an

alternative to class attendance, Computers & Education , 44, 409421.Greene, K., Kramar, M., Walters, L. H., Rubin, D. L., Hale, J. & Hale, L. (2000) Targeting

adolescent risk-taking behaviours: the contributions of egocentrism and sensation-seeking, Journal of Adolescence , 23, 439461.

Gjesne, T. (1977) General satisfaction and boredom at school as a function of the pupilspersonality characteristics, Scandinavian Journal of Educational Research , 21, 113146.

Handelsman, M. M., Briggs, W. L., Sullivan, N. & Towler, A. (2005) A measure of collegestudent course engagement, Journal of Educational Research , 98(3), 184191.

Kanevsky, L. & Keighley, T. (2003) To produce or not to produce? Understanding boredom andthe honor in underachievement, Roeper Review , 26(1), 2029.

Klinger, E. (1987) Imagery and logotherapeutic techniques in psychotherapy, in: W. M. Cox (Ed.)Treatment and prevention of alcohol problems: a resource manual (New York, Academic Press),139156.

Larson, R. W. & Richards, M. H. (1991) Boredom in the middle school years: blaming schoolsversus blaming students, American Journal of Education , 99, 418443.

Liaw, S. S. (2004) Considerations for developing constructivist web-based learning, International Journal of Instructional Media , 31(3), 309321.

Maroldo, G. K. (1986) Shyness, boredom, and grade point average among college students,Psychological Reports , 59, 395398.

Mikulas, W. L. & Vodanovich, S. J. (1993) The essence of boredom, Psychological Record , 43(1),313.

OHanlon, J. F. (1981) Boredom: practical consequences and a theory, Acta-Psychologica , 49,5382.

Perkins, R. E. & Hill, A. B. (1985) Cognitive and affective aspects of boredom, British Journal of Psychology , 76(part 2), 221234.

Perry, T. & Perry, L. A. (1998) University students attitudes towards multimedia presentations,British Journal of Educational Technology , 29, 375377.


w


17/17

Polly, L. M., Vodanovich, S. J., Watt, J. D. & Blanchard, M. J. (1993) The effects of attributionalprocesses on boredom proneness, Journal of Social Behavior and Personality , 8, 123132.

Ramsden, P. (1984) The context of learning, in: F. Marton, D. Hounsell & N. Entwistle (Eds) Theexperience of learning (Edinburgh, Scottish Academic Press).

Ramsden, P. (1995) Deep/surface approach to learning: An introduction, The National Learning and Teaching Forum , 5(1), 15.

Ramsden, P. (2003) Learning to teach in higher education (Routledge, London).Rhem, J. (1995) Deep/surface approaches to learning; an introduction, The National Learning and

Teaching Forum , 5(1), 14.Robinson, W. P. (1975) Boredom at school, British Journal of Educational Psychology , 45, 141152.Shuta, V. J. (1993) The definition of boredom, as well as boredom vs. being doomed. Available

online at: http://www.pdv-systeme.de/users/martinv/pgg/02R/02R048.html.Sommers, J. & Vodanovich, S. J. (2000) Vengeance scores among college students: examining the

role of jealousy and forgiveness, Education , 121(1), 114119.Susskind, J. E. & Gurien, R. A. (1999) Do computer-generated presentations influence

psychology students learning and motivation to succeed? Poster presentation at the Annual Convention of the American Psychological Society , Denver, CO.

Todman, M. (2003) Boredom and psychotic disorders: cognitive and motivational issues,Psychiatry , 66(2), 146166.

Tushup, R. J. & Zuckerman, M. (1977) The effects of stimulus invariance on daydreaming anddivergent thinking, Journal of Mental Imagery , 2, 291302.

Van der Velde, E. G., Feij, J. A. & Toon, W. (1995) Stability and change of person characteristicsamong young adults: the effect of the transition from school to work, Personality and Individual Differences , 18(1), 8999.

Vygotsky, L. S. (1978) Mind in society: the development of higher psychological processes (Cambridge,MA, Harvard University Press).

Ward, T. (2003, May 20) I watched in dumb horror, The Guardian .

Wallace, J. C., Vodanovich, S. J. & Restino, B. M. (2003) Predicting cognitive failures fromboredom proneness and daytime sleepiness scores: an investigation within military andundergraduate samples, Personality and Individual Differences , 34, 635644.

Watt, J. D. & Blanchard, M. J. (1994) Boredom proneness and the need for cognition, Journal of Research in Personality , 28, 4451.

Watt, J. D. & Vodanovich, S. J. (1999) Boredom proneness and psychosocial development, Journal of Psychology , 133, 303314.

Wolff, J. (2006) Room for improvement among lecturers Guardian Education Supplement , 4 July.Zuckerman, M. (1979) Sensation seeking: beyond the optimal level of arousal (Hillsdale, NJ,

Erlbaum).


w

student boredom

Documents