USING MARKETING MODELS TO REVIEW        ACADEMIC STAFF ACCEPTANCE OF       DIGITAL TECHNOLOGY TO ENHANCE        LEARNING I...
INTRODUCTION      http://www.brighton.ac.uk/bbs/
RESISTANCE• “Resistance is what keeps us from attaching  ourselves to every boneheaded idea that comes  along” (Maurer 199...
ACADEMIC STAFF ADOPTION OF TECHNOLOGY             – AND MARKETING MODELS Morris & Rippin (2002) Institutional adoption mo...
RESPONSES TO USING LEARNING           TECHNOLOGIES• MOST FULFILLING?• “fun”, “access  anytime”, “learning with  students”,...
Comparing literature and findings•    Ajzen & Fishbein (1975) Theory of Reasoned Behaviour: Attitude Toward     Behavior: ...
Staff unlikely to adopt TEL:                Themes arising from unstructured interviews1.Lack of interest and curiosity wi...
Hypothesized factors differentiating academic     Themes arising from unstructured interviews   population in relation to ...
Hypothesized factors                                                   differentiating academic population in             ...
CONCLUDING              COMMENTS• In addition to the initial factors from the literature, the teacher  perspective of thei...
•                                  REFERENCES    Bovey, W. H. & Hede, A. (2001) Resistance to organisational          •   ...
USING MARKETING MODELS TO REVIEW        ACADEMIC STAFF ACCEPTANCE OF       DIGITAL TECHNOLOGY TO ENHANCE        LEARNING I...
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Using marketing models to review academic staff acceptance v2

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For DITECH 2013 Hradec Kralove

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  • AbstractTraditional management approaches suggest that resistance is an enemy of change. However there is an increasingly attractive counter view which suggests that, resistance is something to be explored and understood, in order that communication and understanding about the proposed change is better implemented. This is the approach taken in this paper, which seeks to explore resistance among academic staff to the adoption of technology affordances in Higher Education teaching and learning. The initial hypothesis based on survey research suggests that there will always be faculty who try to avoid information and communication technologies (ICTs) – beyond basic PowerPoint™ and email - and thus will be unable to take advantage of learner engagement through the pedagogical affordances both of virtual learning environments (VLEs) and of Web 2.0. Institutions increasingly require staff to adopt basic engagement with VLEs, but that is as far it goes with many teachers. Rather than just have to put up with this situation, or make people participate despite their personal views, we should seek to understand better what causes such resistance, what underlying personal pedagogies are driving this perspective, and how best to accommodate strongly held personal pedagogic diversity amongst teaching staff. The application of a recent marketing model to the adoption of digital technology helps us to understand both the negative force of resistance and the potential positives we might find useful. The research discussed in this paper analyses initial qualitative unstructured interviews with staff, selected for their reluctance to explore the possible learning and teaching affordances of ICTs. Results from this initial study have been discussed in relation to current thinking on change management discussions of resistance (Waddell and Sohal, 1998, Ford et al., 2008), and the application of a business marketing model which focusses on customer centrality has then been applied to guide our thinking and offer some tentative recommendations on how this phenomenon may be further studied and how institutions wishing to develop staff adoption of ICTs in learning and teaching may proceed. .KeywordsTechnology Enhanced Learning. Resistance To Change. Pedagogies.
  • IntroductionBrighton Business School has been using and evaluating learning technologies, initially through an intranet and then through virtual learning environments (VLEs), for over a decade (Flowers et al., 1998). For much of this time, academic staff enthusiasm for developing learning and teaching has been the main driver for adoption (Greener et al., 2007), however, as for many other Higher Education Institutions (HEIs), this has led to a disparate pattern of adoption. From the outset, the introduction of these technologies in learning and teaching has led to both more and less informed debate, with academics often vehement on both sides. The use of technologies in learning challenges the nature of the academic’s role (Greener, 2008) and offers us vehicles by which to drive forward teaching beliefs and pedagogic practice, but can also crash into the barriers of time-poor teachers’ deeply held values and sense of self-efficacy.
  • ResistanceAs Flowers, Newton and Paine pointed out back in 1998, there is much about the notion of culture change involved in the adoption of learning technologies. These writers used Rogers’ work (1962) on the diffusion of innovation and Moore’s “chasm” between early adopters and mainstream users of technology change (1991) to explore staff responses to their new intranet for learning and teaching. Traditional management approaches suggest that resistance is exhibited by mainstream and “laggards” in relation to the change, and this seems self-evident when we look at the total academic population of an HEI in relation to technology-enhanced learning. Conferences on e-learning offer many examples of exciting innovations which have not quite made it to the mainstream. The enthusiasts are prepared to put in more time, more effort and more love to achieve the innovation they believe in, than those for whom the innovation is presented as a given. We tend to describe this reaction against the enthusiasts as “resistance”. Although usually considered a negative concept, Waddell and Sohal (1998) among others discuss the positive utility of resistance. Seeing resistance as a potentially positive response to change starts to counter the idea that all change is good and all resistance is bad. We know from the dangers of groupthink (Janis, 1983) that an idea which is subject to little opposition may be a flawed idea and lead to bad decisions, or as Maurer suggests: “Resistance is what keeps us from attaching ourselves to every boneheaded idea that comes along” (Maurer 1996, cited in Waddell and Sohal, 1998: 545) But as Ford, Ford and D’Amelio explain (2008), even positive thinking about the utility of resistance can lead to a reification of the idea of resistance. Innovators come to expect resistance and this becomes a self-fulfilling prophecy, whereas all that may be there under the label of “resistance” is a thoughtful scepticism, which is bred from endless media hyperbole about “the latest” thing to hit our screens. These authors offer the concept of “inoculation theory” which assumes resistance is something to be countered and ends up hardening the presumed resistance.  “Inoculation theory suggests that change agents who do not develop and provide compelling justifications that overcome the potential or prevailing counterarguments, or who fail to demonstrate the validity of those justifications, end up inoculating recipients and increasing their immunity to change.” (Ford et al., 2008 : 366) Such a theory has an immediate resonance with those of us who return from e-learning research conferences full of great ideas for application to teaching and learning, only to find a distinct lack of enthusiasm amongst our colleagues, indeed strong opposition from some. It is then easy to make assumptions that X will never consider technology and Y will not be prepared to change their ways of teaching, points of view which clearly set up their own ripples of resistance. Ford et al’s contribution to this debate (albeit in the field of change management rather than learning technology) is to make us sit up and take notice that our assumptions about non-enthusiasts for technology could actually be causing some of the resistance we encounter. They make the positive case for resistance, an increasingly attractive counter view, which suggests that resistance is something to be explored and understood, in order that communication and understanding about the proposed change is better implemented.
  • academic staff adoption of technology and marketing modelsBovey and Hede (2001) put forward the idea in their paper on defence mechanisms in organisational change that too often change is driven in organisations from the top with a major emphasis on the technical features of the change and with little attention to the individuals involved. This notion is reflected in Morris and Rippin’s account of educational institutions’ adoption of technology for learning (2002) in which they analyse institutional adoption strategies as enthusiast/explorer, emulator, efficiency seekers and entrepreneurs, none of which strategies focus on individual teachers’ responses to the imposition of learning technologies from the top. So should we take a more user-centric view? In a very recent publication (2012) in the business marketing field, Sheth and Sisodia offer a new take on traditional marketing approaches from an organisation perspective (generally known as the 4 Ps of price, place, product and promotion) and design a new marketing model from the user or customer perspective. Just as the early adopter model from Rogers and later Moore (1991) related the theory of adoption to marketing products and services which has been frequently used in the discussion of technology adoption, so Sheth and Sisodia offer a marketing model which we can apply to staff adoption of technologies for learning. Their model looks at the innovation’s acceptability (the extent to which the innovation meets user expectations), affordability (ability and willingness to pay – in our case from an institutional perspective, although educators will also pay in terms of professional time), accessibility (the availability and convenience of the innovation) and awareness (both of brand and product knowledge). Institutions increasingly require staff to adopt basic engagement with VLEs, but that is as far it goes with many teachers. Rather than just have to put up with this situation, or make people participate despite their personal views, we should seek to understand better what causes such responses, what underlying personal pedagogies are driving this perspective, and how best to accommodate strongly held personal pedagogic diversity amongst teaching staff. As part of anongoingproject to explore and map academic staff stances in relation to e-learning and e-teaching, the exploratory research discussed in this paper first analyses survey responses from staff involved in e-learning and then initial qualitative unstructured interviews with staff, selected for their reluctance to explore the possible learning and teaching affordances of ICTs.
  • findingsResearch conducted through two small surveys of academic staff involved in some way with technology enhanced learning, many of them engaging with this for the first time, produced evidence that trying to understand staff responses to e-learning and e-teaching was not going to be a straightforward area of enquiry. The staff groups surveyed had all expressed an active interest in learning and teaching by participating in the surveys, and the table below shows responses to questions about what they found most and least fulfilling in their early experience of using TEL. Table 1: Snapshot of data from staff surveys showing most and least fulfilling responses to using learning technologies for the first time. (Codes denote respondents).Table 1 gives a flavour of a range of factors considered relevant to the experience of using learning technologies. There are some familiar joys such as empowerment of students, creativity, innovation and some familiar sorrows such as technology difficulties and time taken to prepare the design. In an initial review of these and other findings from the surveys (Greener and Rospigliosi, 2009), the aim was to explore differences between respondents who were personally stating they were early adopters and enthusiastic about new technologies, and those who considered themselves mainstream in relation to innovation adoption. The expected differences were not as clear as expected. While the self-professed early adopters did focus more on the technical software issues of adoption, and the mainstream group focussed more on time and workload issues, there were few other distinctions between the two groups.  
  • This leads us to look more closely at the way staff might be responding to innovation in learning and teaching. Underpinning most models of technology acceptance and behaviours, the Theory of Reasoned Action discussed by Ajzen and Fishbein (1975) has driven a range of attempts to explain and understand how people respond to new ideas and products from the perspective of social psychology. Liao and Lu (2008) discuss the Davis’ Technology Acceptance Model (1989) and alternatives to TAM’s perceived usefulness and ease of use and derive “relative advantage” and “compatibility” as drivers to new technologies adoption by teachers. Relative advantage can be easily understood as perceived advantages offered by the technology in comparison with alternatives. Compatibility relates to the relationship between the technology and the adopter’s beliefs, values and philosophy of teaching. The variation in teaching beliefs and personal pedagogies which might affect the pedagogic use of learning technologies seems logical, but this analysis alone could easily lead to the labelling of staff as for or against technologies on the basis of apparently static pedagogies. It would be easy for enthusiastic adopters to suggest that those who did not adopt technologies were in some respect worse teachers with didactic and outdated beliefs about learning and teaching. This idea does not stand up to scrutiny, since in our HEI there are several known teachers who are respected for award-winning teaching in the classroom and who are nonetheless opposed to the adoption of learning technologies.UTAUT is a more recent model (Venkatesh et al 2003) aiming to develop the simple TAM dimensions focussed largely on performance expectancy, effort expectancy, social influence and facilitating conditions affecting user intentions and behaviour concerning technology. There have been critics of this model (e.g. Bagozzi 2007) as it includes a very wide number of independent variables, but the principle of inclusion of social influence as a separate variable, moving away from TAM’s focus on the single user where social influence would be included within the two TAM dimensions, is consistent with, for example, Bandura’s Social Cognitive theory. Our increasing understanding of the power of social media and networking, providing for learning professionals a rapid recommendation process for new applications provides demonstration of the need to consider social influence in adoption of technologies in learning. If we return to the Sheth and Sisodiamodel, we can see that from a user’s perspective, innovations in technology for learning suffer differing levels of acceptability. This latter dimension of the model refers to both functional acceptability, including how easy it is to use, quality and reliability, and psychological acceptability, including social and emotional value and perceived risk. The common concern over time to implement new innovations in Table 1 relate to functional acceptability (and to some extent psychological affordability), and the concern that such teaching will not be taken seriously relates to psychological acceptability. Technology access and availability concerns relate to the model’s dimension of accessibility.This suggested that a search was needed for other possible distinguishing factors within the academic population, factors which might help us understand responses to TEL adoption with sufficient depth to enable improved ways of interpreting and supporting this kind of change. One such distinguishing factor was proposed by Trowler’s work (2009) on sub-disciplines, which introduced distinctions between subject disciplines relating to dimensions such as hard/soft, urban/rural, convergent/divergent, and pure/applied focus. Could such differences help to explain responses to technology? Another factor to be considered in future research would be general experience of internet use. A useful paper by Eynon focussing on young people offers a simple typology of internet usage: peripherals, normatives, all-rounders and active participants (Eynon, 2009). It could be argued that the active participants category, who represented 14% of her data based on over 1000 participants, and were regularly communicating, seeking information, using entertainment, using creative sites for writing or music and participating in blogging, wiki editing, podcasting etc, could be a similar category to Drent and Meelissen’s “personal entrepreneurs” (2008) in terms of technology usage and exploration – activities confined to early adopters. One further factor from current literature which may help us to distinguish amongst the academic population is the digital skillset available to them. Van Deursen and van Dyk (2009) discussed skillsets to do with internet use and identified four groups of such digital skills: operational, formal (e.g. navigation), information (search and evaluation) and strategic (pursuing and solving a problem or goal through use of internet skills. It could be hypothesized that active participants/personal entrepreneurs would be high scorers on all four skillsets but that other groups such as those opposing the use of technology were lower on information and strategic skills. All these distinguishing factors: subject sub-disciplines, internet usage, digital skillsets, as well as personal beliefs about teaching are hypothesized as potentially helpful in mapping the academic population in relation to e-learning adoption.
  • Next stage of researchInformal and unstructured interviews were carried out among Business School academic staff to test the possible relevance of these divergent factors among a set of the population which was least enthusiastic about learning technologies. This was done informally as a pilot study to explore the viability of this line of enquiry. All interviews were recorded and subjected to thematic analysis. Early results show the following themes.  Table 2: Themes from interviews with reluctant users of learning technologies and their relationship with hypothesized factors differentiating the academic population in relation to learning technologies adoption.
  • Next stage of researchInformal and unstructured interviews were carried out among Business School academic staff to test the possible relevance of these divergent factors among a set of the population which was least enthusiastic about learning technologies. This was done informally as a pilot study to explore the viability of this line of enquiry. All interviews were recorded and subjected to thematic analysis. Early results show the following themes.  Table 2: Themes from interviews with reluctant users of learning technologies and their relationship with hypothesized factors differentiating the academic population in relation to learning technologies adoption.
  • Next stage of researchInformal and unstructured interviews were carried out among Business School academic staff to test the possible relevance of these divergent factors among a set of the population which was least enthusiastic about learning technologies. This was done informally as a pilot study to explore the viability of this line of enquiry. All interviews were recorded and subjected to thematic analysis. Early results show the following themes.  Table 2: Themes from interviews with reluctant users of learning technologies and their relationship with hypothesized factors differentiating the academic population in relation to learning technologies adoption.
  • Concluding commentsThese findings so far suggest that our hypothesized factors may help to explain some of the divergence in the ways academic staff relate to technology-enhanced learning. Teaching beliefs appear to be most clearly represented in the themes arising from the data, while subject sub-disciplines so far are proving less helpful. An additional factor, that of teacher role, has been applied to try to understand the degree of openness or preparedness to share materials either with colleagues or on the web. It could be argued that this is strongly related to the sense of connectedness experienced by many regular web users, so that in fact this is a product of internet usage. The ideas relating to a teacher’s role also seem relevant to the theme of last minute preparation. The latter point is doubtless not confined to reluctant users of technology, however their lack of use of technology may contribute to the need for last minute preparation. Alternatively this could be explained by an attitude or belief about pedagogy.It may be, however, that in this analysis we are putting too much emphasis on teaching beliefs. The difficulty in Higher Education is to find a way to change them. While new academic staff are generally required to undertake courses in learning and teaching to help develop and challenge their personal pedagogies, existing academic staff have little incentive to review and challenge these beliefs. The rapid growth and spread of digital technology has tended to paint these 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 as discussed above. It is clear from the early findings that staff who say no to technology do show strong beliefs about pedagogy. These are frequently related to the member of staff’s own prior learning experiences, which did not involve such digital technologies and are not simply a rejection of the new, but a statement of belief and value, particularly evidenced in strong defences of the importance of classroom interaction to produce insight and deeper learning behaviours from students. When things do go “wrong” for these teachers, they are less likely to seek help from colleagues or rethink their pedagogy, believing that they can put things right by sticking to what they know that works for them or, in just a few cases, blaming the students and the technology they are using.The above table also demonstrates some possible relationships between factors affecting adoption of technology with reluctant users and their relationship to the 4As model of Sheth and Sisodia. The latter model offers a simpler way of understanding the criteria which are being used for technology adoption and can offer a way forward for demonstrating value to such reluctant users through concentrating on Acceptability, Awareness, Affordability and Accessibility of technology tools for learning. The research so far has been limited to small scale unstructured interviews with staff who were kind enough to take part and happy to consider themselves reluctant users of learning technologies. This preliminary study has helped us to explore factors which might be used to map the academic population in relation to the use of technologies in learning and teaching. The methods used have been qualitative as what we are exploring here are differences of perceptions relating to beliefs, behaviours and educational environments. Further research is suggested which explores a broader, more representative sample of academic staff, perhaps controlling for subject discipline in the first instance, and attempting to build profiles of responses to technology on the basis of pedagogies, digital skillsets, internet usage, views on teacher roles in HE and self-efficacy in relation to technologies.
  • ReferencesGreener. (2008) Identity crisis: Who is teaching whom online? European Conference on E-Learning (ECEL) 2009. Agia Napa, Cyprus.Greener. & Rospigliosi, A. (2009) Tread softly: Making secure steps towards wider adoption of pedagogically-focussed e-learning at brighton business school. In Blackey, H., Jefferies, A., Masterman, L. & Whalley, B. (Eds.) In dreams begins responsibility - choice, evidence and change. . University of Manchester, England, UK, The 16th Association for Learning Technology Conference (ALT-C 2009). Held 8-10 September 2009.Greener., Rospigliosi, A. & Shurville, S. (2007) Engaging from the inside: Reflections on the value of social cognitive theory for learning in online discussions. International Conference on E-Learning (ICEL) 2007. New York.Bovey, W. H. & Hede, A. (2001) Resistance to organisational change: The role of defence mechanisms. Journal of Managerial Psychology, 16, 534-548.Davis, F. D. (1989) Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13, 319-340.Drent, M. & Meelissen, M. (2008) Which factors obstruct or stimulate teacher educators to use ict innovatively? Computers & Education, 51, 187-199.Eynon, R. (2009) Mapping young people's use of new technologies for learning. Implications for policy and practice. British Educational Research Association Annual Conference (BERA 2009). Manchester, UK.Fishbein, M., and Ajzen, I. (1975) Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA,.Flowers, S., Newton, B. & Paine, C. (1998) Creating a faculty intranet: A case study in change. Education and Training, 40, 340-346.Ford, J. D., Ford, L. W. & D'amelio, A. (2008) Resistance to change: The rest of the story. Academy of Management Review, 33, 362-377.Janis, I. (1983) Groupthink: Psychological studies of policy decisions and fiascoes., Boston, Houghton Mifflin.Liao, H.-L. & Lu, H.-P. (2008) The role of experience and innovation characteristics in the adoption and continued use of e-learning websites. Computers & Education, 51, 1405-1416.Moore, G. (1991) Crossing the chasm: Marketing and selling technology products to mainstream customers, Oxford, Harper Business.Morris, H. & Rippin, A. (2002) E-learning in business and management: The current state of play. BEST 2002 Supporting the Teacher, Challenging the Learner. Edinburgh, BEST.Rogers, E. M. (1962) Diffusion of innovations (1st ed.). , New York, Free Press.Sheth, J.N. & Sisodia, R.S. (2012) The 4A's of Marketing: Creating Value for Customers, Companies and Society. Oxon.: Routledge.Trowler, P. (2009) Beyond epistemological essentialism: Academic tribes in the 21st century. IN Kreber, C. (Ed.) The university and its disciplines : Teaching and learning within and beyond disciplinary boundaries. London, Routledge.Van Deursen, A. J. A. M. & Van Dijk, J. A. G. M. (2009) Using the internet: Skill related problems in users' online behaviorInteracting with Computers, in press.Venkatesh, V.; Morris, M.G.; Davis, G.B. & Davis ,F.D. (2003), "User Acceptance of Information Technology: Toward a Unified View", MIS Quarterly, 27, pp. 425–478Waddell, D. & Sohal, A. S. (1998) Resistance: A constructive tool for change management. Management Decision, 36, 543-548. 
  • AbstractTraditional management approaches suggest that resistance is an enemy of change. However there is an increasingly attractive counter view which suggests that, resistance is something to be explored and understood, in order that communication and understanding about the proposed change is better implemented. This is the approach taken in this paper, which seeks to explore resistance among academic staff to the adoption of technology affordances in Higher Education teaching and learning. The initial hypothesis based on survey research suggests that there will always be faculty who try to avoid information and communication technologies (ICTs) – beyond basic PowerPoint™ and email - and thus will be unable to take advantage of learner engagement through the pedagogical affordances both of virtual learning environments (VLEs) and of Web 2.0. Institutions increasingly require staff to adopt basic engagement with VLEs, but that is as far it goes with many teachers. Rather than just have to put up with this situation, or make people participate despite their personal views, we should seek to understand better what causes such resistance, what underlying personal pedagogies are driving this perspective, and how best to accommodate strongly held personal pedagogic diversity amongst teaching staff. The application of a recent marketing model to the adoption of digital technology helps us to understand both the negative force of resistance and the potential positives we might find useful. The research discussed in this paper analyses initial qualitative unstructured interviews with staff, selected for their reluctance to explore the possible learning and teaching affordances of ICTs. Results from this initial study have been discussed in relation to current thinking on change management discussions of resistance (Waddell and Sohal, 1998, Ford et al., 2008), and the application of a business marketing model which focusses on customer centrality has then been applied to guide our thinking and offer some tentative recommendations on how this phenomenon may be further studied and how institutions wishing to develop staff adoption of ICTs in learning and teaching may proceed. .KeywordsTechnology Enhanced Learning. Resistance To Change. Pedagogies.
  • Using marketing models to review academic staff acceptance v2

    1. 1. USING MARKETING MODELS TO REVIEW ACADEMIC STAFF ACCEPTANCE OF DIGITAL TECHNOLOGY TO ENHANCE LEARNING IN HIGHER EDUCATIONDr Sue GreenerS.L.Greener@ brighton.ac. ukBrighton Busin ess School, University ofBrighton, UK
    2. 2. INTRODUCTION http://www.brighton.ac.uk/bbs/
    3. 3. 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)
    4. 4. 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 • Extent to which the innovation meets Acceptability user expectations • Ability and willingness to pay (not just Affordability money but time) • Availability and convenience of Accessibility innovation • Knowledge of products, features, Awareness applications
    5. 5. RESPONSES TO USING LEARNING TECHNOLOGIES• MOST FULFILLING?• “fun”, “access anytime”, “learning with students”, “real time interaction”, “creative process”, “empowering students”  The self-professed early• LEAST FULFILLING? adopters focussed more on technical software• “unreliable access”, “clumsy issues of adoption operation”, “extra  The mainstream group workload”, “not enough focussed more on time time to experiment”, “not and workload issues knowing how”, “colleague inertia”
    6. 6. 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
    7. 7. Staff unlikely to adopt TEL: Themes arising from unstructured interviews1.Lack of interest and curiosity with regard to learning technologies2.Difficulties with navigation on web and VLEs3.Persuaded of view that uploading materials would decrease class attendance4.Focussed on the learning value of face to face interaction in the classroom5.Focussed on the learning value of face to face interaction in the classroom6.Strong core pedagogic beliefs, often drawing on personal experiences of learning7.Unhappy about sharing materials on web or VLE8.Association of web usage with surface learning for students9.Aiming to reproduce face to face teaching paradigm online10.Belief that they are lazier than those who use learning technologies, justifying this on time grounds11.Often last minute preparation of teaching
    8. 8. Hypothesized factors differentiating academic Themes arising from unstructured interviews population in relation to learning technologies adoption 1.Lack of interest and curiosity with Internet usage, teacher role? self-efficacy?regard to learning technologies 2.Difficulties with navigation on web and Digital skill setVLEs 3.Persuaded of view that uploading Teaching beliefsmaterials would decrease class attendance 4.Focussed on the learning value of face Teaching beliefsto face interaction in the classroom 5.Focussed on the learning value of face Teaching beliefsto face interaction in the classroom 6.Strong core pedagogic beliefs, often Subject sub-disciplines, teaching beliefsdrawing on personal experiences of learning 7.Unhappy about sharing materials on Internet usage, teacher role?web or VLE 8.Association of web usage with surface Teaching beliefslearning for students 9.Aiming to reproduce face to face Teaching beliefs / digital skill setsteaching paradigm online 10.Belief that they are lazier than those Digital skill setwho use learning technologies, justifying thison time grounds 11.Often last minute preparation of Teaching beliefs, teacher role?teaching
    9. 9. Hypothesized factors differentiating academic population in Sheth and Sisodia model (2012) dimensions Themes arising from unstructured interviews relation to learning technologies implicated adoption 1.Lack of interest and curiosity with Internet usage, teacher role? Awareness: product knowledgeregard to learning technologies self-efficacy? Acceptability: psychological acceptability 2.Difficulties with navigation on web and Digital skill set Awareness: product knowledgeVLEs Acceptability: functional acceptability 3.Persuaded of view that uploading Teaching beliefs Awareness: product knowledgematerials would decrease class attendance 4.Focussed on the learning value of face Teaching beliefs Acceptability: psychological acceptabilityto face interaction in the classroom 5.Focussed on the learning value of face Teaching beliefs Acceptability: psychological acceptabilityto face interaction in the classroom 6.Strong core pedagogic beliefs, often Subject sub-disciplines, Acceptability: psychological acceptabilitydrawing on personal experiences of learning teaching beliefs 7.Unhappy about sharing materials on Internet usage, teacher role? Acceptability: functional acceptabilityweb or VLE 8.Association of web usage with surface Teaching beliefs Acceptability: functional acceptabilitylearning for students 9.Aiming to reproduce face to face Teaching beliefs / digital skill Accessibility: convenienceteaching paradigm online sets 10.Belief that they are lazier than those Digital skill set Affordability: psychological affordabilitywho use learning technologies, justifying thison time grounds 11.Often last minute preparation of Teaching beliefs, teacher Affordability: psychological affordabilityteaching role?
    10. 10. 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?
    11. 11. • REFERENCES Bovey, W. H. & Hede, A. (2001) Resistance to organisational • Greener S. & Rospigliosi, A. (2009) Tread softly: Making secure steps change: The role of defence mechanisms. Journal of towards wider adoption of pedagogically-focussed e-learning at Managerial Psychology, 16, 534-548. brighton business school. In Blackey, H., Jefferies A., Masterman, L. & Whalley, B. (Eds.) In dreams begins responsibility - choice, evidence and• Davis, F. D. (1989) Perceived usefulness, perceived ease of change. . University of Manchester, England, UK, The 16th Association for use and user acceptance of information technology. MIS Learning Technology Conference (ALT-C 2009). Held 8-10 September Quarterly, 13, 319-340. 2009.• Drent, M. & Meelissen, M. (2008) Which factors obstruct or • Janis, I. (1983) Groupthink: Psychological studies of policy decisions and stimulate teacher educators to use ict innovatively? fiascoes., Boston, Houghton Mifflin. Computers & Education, 51, 187-199. • Liao, H.-L. & Lu, H.-P. (2008) The role of experience and innovation• Eynon, R. (2009) Mapping young peoples use of new characteristics in the adoption and continued use of e-learning websites. Computers & Education, 51, 1405-1416. technologies for learning. Implications for policy and practice. British Educational Research Association Annual • Moore, G. (1991) Crossing the chasm: Marketing and selling technology products to mainstream customers, Oxford, Harper Business. Conference (BERA 2009). Manchester, UK. • Morris, H. & Rippin, A. (2002) E-learning in business and management:• Fishbein, M., and Ajzen, I. (1975) Belief, Attitude, Intention and The current state of play. BEST 2002 Supporting the Teacher, Challenging Behavior: An Introduction to Theory and Research, Addison- the Learner. Edinburgh, BEST. Wesley, Reading, MA,. • Rogers, E. M. (1962) Diffusion of innovations (1st ed.). , New York, Free• Flowers, S., Newton, B. & Paine, C. (1998) Creating a faculty Press. intranet: A case study in change. Education and Training, 40, • Sheth, J.N. & Sisodia, R.S. (2012) The 4As of Marketing: Creating Value 340-346. for Customers, Companies and Society. Oxon.: Routledge.• Ford, J. D., Ford, L. W. & Damelio, A. (2008) Resistance to • Trowler, P. (2009) Beyond epistemological essentialism: Academic tribes change: The rest of the story. Academy of Management in the 21st century. IN Kreber, C. (Ed.) The university and its disciplines : Review, 33, 362-377. Teaching and learning within and beyond disciplinary boundaries.• Greener S., Rospigliosi, A. & Shurville, S. (2007) Engaging from London, Routledge. the inside: Reflections on the value of social cognitive theory • Van Deursen, A. J. A. M. & Van Dijk, J. A. G. M. (2009) Using the internet: for learning in online discussions. International Conference on Skill related problems in users online behavior Interacting with E-Learning (ICEL) 2007. New York. Computers, in press.• Greener S. (2008) Identity crisis: Who is teaching whom • Venkatesh, V.; Morris, M.G.; Davis, G.B. & Davis ,F.D. (2003), "User online? European Conference on E-Learning (ECEL) 2009. Acceptance of Information Technology: Toward a Unified View", MIS Agia Napa, Cyprus. Quarterly, 27, pp. 425–478 • Waddell, D. & Sohal, A. S. (1998) Resistance: A constructive tool for change management. Management Decision, 36, 543-548.
    12. 12. USING MARKETING MODELS TO REVIEW ACADEMIC STAFF ACCEPTANCE OF DIGITAL TECHNOLOGY TO ENHANCE LEARNING IN HIGHER EDUCATIONDr Sue GreenerS.L.Greener@ brighton.ac. ukBrighton Busin ess School, University ofBrighton, UK

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