using marketing models to review academic staff acceptance v2
TRANSCRIPT
USING MARKETING MODELS TO REVIEW ACADEMIC STAFF ACCEPTANCE OF DIGITAL
TECHNOLOGY TO ENHANCE LEARNING IN HIGHER EDUCATION
Dr Sue Greener
Brighton Business School, University of Brighton, UK
INTRODUCTIONhttp://www.brighton.ac.uk/bbs/
RESISTANCE• “Resistance is what keeps us from attaching
ourselves to every boneheaded idea that comes along” (Maurer 1996, cited in Waddell and Sohal, 1998: 545)
ACADEMIC STAFF ADOPTION OF TECHNOLOGY – AND MARKETING MODELS
Morris & Rippin (2002) Institutional adoption models: Enthusiast/explorer, emulator, efficiency seeker, entrepreneur
The basic marketing model: Product, Price, Place & Promotion (e.g. Kotler) Sheth & Sisodia (2012) Acceptability, Affordability, Accessibility, &
Awareness
Acceptability
• Extent to which the innovation meets user expectations
Affordability
• Ability and willingness to pay (not just money but time)
Accessibility
• Availability and convenience of innovation
Awareness• Knowledge of products, features,
applications
RESPONSES TO USING LEARNING TECHNOLOGIES
• MOST FULFILLING?• “fun”, “access anytime”,
“learning with students”, “real time interaction”, “creative process”, “empowering students”
• LEAST FULFILLING?• “unreliable access”,
“clumsy operation”, “extra workload”, “not enough time to experiment”, “not knowing how”, “colleague inertia”
The self-professed early adopters focussed more on technical software issues of adoption
The mainstream group focussed more on time and workload issues
Comparing literature and findings
• Ajzen & Fishbein (1975) Theory of Reasoned Behaviour: Attitude Toward
Behavior: “an individual’s positive or negative feelings about performing the target behavior” (p. 216) and Subjective Norm -“the person’s perception that most people who are important to him think he should or should not perform the behavior in question” (p. 302).
• Davis’ Technology Acceptance Model (1989): Perceived usefulness and Perceived ease of use – focussed on the individual
• Liao and Lu (2008): Compatibility (with teaching beliefs) and Relative advantage (of change compared with status quo)
• Venkatesh et al (2003): Unified Theory of Acceptance & Use of Technology (UTAUT) – including social influence
But also consider digital skillsets, personal entrepreneurship, subject disciplines and frequency of internet usage
Staff unlikely to adopt TEL:Themes arising from unstructured interviews
1.Lack of interest and curiosity with regard to learning technologies
2.Difficulties with navigation on web and VLEs
3.Persuaded of view that uploading materials would decrease class attendance
4.Focussed on the learning value of face to face interaction in the classroom
5.Focussed on the learning value of face to face interaction in the classroom
6.Strong core pedagogic beliefs, often drawing on personal experiences of learning
7.Unhappy about sharing materials on web or VLE
8.Association of web usage with surface learning for students
9.Aiming to reproduce face to face teaching paradigm online
10.Belief that they are lazier than those who use learning technologies, justifying this on time grounds
11.Often last minute preparation of teaching
Themes arising from unstructured interviews
Hypothesized factors differentiating academic population in relation to learning technologies adoption
1.Lack of interest and curiosity with regard to learning technologies
Internet usage, teacher role? self-efficacy?
2.Difficulties with navigation on web and VLEs
Digital skill set
3.Persuaded of view that uploading materials would decrease class attendance
Teaching beliefs
4.Focussed on the learning value of face to face interaction in the classroom
Teaching beliefs
5.Focussed on the learning value of face to face interaction in the classroom
Teaching beliefs
6.Strong core pedagogic beliefs, often drawing on personal experiences of learning
Subject sub-disciplines, teaching beliefs
7.Unhappy about sharing materials on web or VLE
Internet usage, teacher role?
8.Association of web usage with surface learning for students
Teaching beliefs
9.Aiming to reproduce face to face teaching paradigm online
Teaching beliefs / digital skill sets
10.Belief that they are lazier than those who use learning technologies, justifying this on time grounds
Digital skill set
11.Often last minute preparation of teaching
Teaching beliefs, teacher role?
Themes arising from unstructured interviews
Hypothesized factors differentiating academic population in
relation to learning technologies adoption
Sheth and Sisodia model (2012) dimensions implicated
1.Lack of interest and curiosity with regard to learning technologies
Internet usage, teacher role? self-efficacy?
Awareness: product knowledge
Acceptability: psychological acceptability
2.Difficulties with navigation on web and VLEs
Digital skill set Awareness: product knowledge
Acceptability: functional acceptability3.Persuaded of view that uploading
materials would decrease class attendanceTeaching beliefs Awareness: product knowledge
4.Focussed on the learning value of face to face interaction in the classroom
Teaching beliefs Acceptability: psychological acceptability
5.Focussed on the learning value of face to face interaction in the classroom
Teaching beliefs Acceptability: psychological acceptability
6.Strong core pedagogic beliefs, often drawing on personal experiences of learning
Subject sub-disciplines, teaching beliefs
Acceptability: psychological acceptability
7.Unhappy about sharing materials on web or VLE
Internet usage, teacher role? Acceptability: functional acceptability
8.Association of web usage with surface learning for students
Teaching beliefs Acceptability: functional acceptability
9.Aiming to reproduce face to face teaching paradigm online
Teaching beliefs / digital skill sets
Accessibility: convenience
10.Belief that they are lazier than those who use learning technologies, justifying this on time grounds
Digital skill set Affordability: psychological affordability
11.Often last minute preparation of teaching
Teaching beliefs, teacher role?
Affordability: psychological affordability
CONCLUDING COMMENTS
• In addition to the initial factors from the literature, the teacher perspective of their role is proposed as a key determinant to technology adoption to enhance learning. In turn this is based on pedagogic beliefs.
• But how do we change such deep-seated values?• The rapid growth and spread of digital technology has tended to
paint some teachers into a corner – either they embrace change and see this as a professionally rewarding move, offering them learning and improved achievements with students, or they may feel cut off from the growing move to use VLEs as more than repositories for materials, and dig their heels in as enthusiasts try to “convert” them – a form of inoculation theory.
• Could we use the Sheth & Sisodia 4As model to demonstrate value in TEL to reluctant faculty – focussing on messages about Acceptability, Affordability, Accessiblity and Awareness?
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USING MARKETING MODELS TO REVIEW ACADEMIC STAFF ACCEPTANCE OF DIGITAL
TECHNOLOGY TO ENHANCE LEARNING IN HIGHER EDUCATION
Dr Sue Greener
Brighton Business School, University of Brighton, UK