How institutions make decisions to accept or reject technology innovation has been explored by academics with the assistance of the Technology Acceptance Model (TAM). Scenarios involving successful delivery of online learning from degree granting universities guide this literature review. It examines decision processes influenced by TAM methods combined with dominant research perspectives such as Self-efficacy Theory and Universal Technology Adoption and Use Theory. This paper analyzes which variables determine perceptions of usefulness, attitude and preferences and become frequent factors to influence typical TAM results. It identifies patterns about reliable predictors of outcomes (behaviors, aligning IT and preferences) for educational investments in learning environments, content delivery and teacher preferences. Adoption of technology is a complex, inherently social process guided by perceptions or misperception of value and ease of use. Thus, facilitating a decision to adopt devices, software or processes must address emotional, cognitive, and contextual concerns of all stakeholders.
Prepared for TCC conference, 2011
1. Technology Acceptance Model for Online Adult Education Weds April 13 13:30 (11113) Barbara Lauridsen, MBA Core Adjunct Faculty, National University Learner, PhD Information Technology Education, Capella University [email_address] www.barbaralauridsen.com TCC Online Conference    Emerging Technologies, Making it Work
4. Technology Zone (Design) ... two way interactive, dialogical teaching and learning, ⊠multiple ways (networked, multi-conversational learning) ⊠medium allows for the message to be one way, monological teaching collaboration on single documents or blog >>> >>> allows multiple networked communication
5. Some Emerging Technologies BLOG IT, TAG IT, SHARE IT! http://www.flickr.com/photos/habibmi/222296001/sizes/o/
10. Basic Concept Basic Concept Underlying User Acceptable Models (Hart et al. 2007, p. 108)
11. Technology Acceptance Model (TAM), an initial construct model Figure 2 Technology Acceptance Model (TAM) (Davis et al., 1989)
12. Technology Acceptance Model (TAM) Figure 2 Technology Acceptance Model (TAM) (Davis et al., 1989) Perceived Usefulness of Technology (PU) Perceived Ease of Use of Technology (PEOU) Attitude toward Using Technology (ATUT) Intention to Use Technology (IU)
13. TAM Framework - Research plan for Virtual Communities (VC) Figure 3 Theoretical Framework Virtual Communities (Hsiu-Fen, 2008, Figure 1, p. 139) This simple graphic model shows outcome using path significance as a data analysis method to measure VC loyalty.
14. TAM Framework - Research plan for Virtual Communities (VC) Figure 3 Theoretical Framework Virtual Communities (Hsiu-Fen, 2008, Figure 1, p. 139) Slide 13+ Perceived Usefulness of Technology (PU)
15. TAM Framework - Research plan for Virtual Communities (VT) Figure 3 Theoretical Framework Virtual Communities (Hsiu-Fen, 2008, Figure 1, p. 139) (PU) Perceived Ease of Use of Technology (PEOU)
16. TAM Framework - Research plan for Virtual Communities (VC) Figure 3 Theoretical Framework Virtual Communities (Hsiu-Fen, 2008, Figure 1, p. 139) (PU) (PEOU) Attitude toward Using Technology (ATUT) Intention to Use Technology (IU)
17. TAM Framework - Research plan for Virtual Communities (VC) Figure 3 Theoretical Framework Virtual Communities (Hsiu-Fen, 2008, Figure 1, p. 139) The authorâs self evident conclusion is that to âsustain a successful VC, tool providers need to focus on designing both useful and easy-to-use Web sites (2008, p. 143). (PU) (PEOU) (ATUT) (IU)
18. TAM Framework - Research plan for Virtual Communities (VC) Figure 4 Results of TAM Path Significance (Hsiu-Fen, 2008, Figure 2, p. 141) Resulting statistics for TAM are typical illustrations of a construct model overlaid with summary statistics from the opinion surveys. (ATUT) (IU) (PEOU) (PU)
19. TAM - Faculty & Technical Support (plan) Figure 5 TAM Framework including Faculty and Technical Support (Baker-Eveleth et al., 2006, p. 414) External Variables >> (ATUT) (IU) (PEOU) (PU)
20. collect data to predict ease of use Table 1 Questions to Predict Ease of Use (Gibson et al., 2008, Table 1, p. 357)
21. TAM - Faculty & Technical Support (results) Figure 6 TAM Estimate Acceptance, Standardized Path Coefficients (Baker-Eveleth et al., 2006, p. 418)
22. TAM2 (IU) (PEOU) (PU) * Figure 7 Integrated Conceptual TAM Constructs (Davis & Wong, 2007, Figure 1, p. 207) Figure 6 Integrated Conceptual TAM Constructs (Davis & Wong, 2007, Figure 1, p. 207) (ATUT)
24. Analysis quadrant Figure 7 Resource-based Implications for Disciplinary Strategy (Grover et al., 2009, p. 322) Artifact referenced in ârecognition of the transactional aspect of knowledge, and an appreciation of the concepts outlined in the resource-based modelâ ⊠behaviors rather than merely opinions .
25. Research Hypotheses (generic construct model diagram) Figure 8 Hypotheses mapped on TAM Framework (SĂĄnchez-Franco & RoldĂĄn, 2005, Figure 2)
26. threshold to the diffusion curve Figure 12 How Individual Adoptions Compose Diffusion (Straub, 2009, Figure 1, p. 627).
27. diffusion curve / innovations Diiffusion of Innovation Curve (Value Based Management)
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30. User Acceptance of I.T. (Unified View) Extension of the TAM (based on Venkatesh & Davis, 2000, p. 188)
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33. User Acceptance of I.T. (Unified View) Constructs for UTAUT (Vankatesh et al. 2003)
Mentis, M. (2008) âNavigating the e-Learning terrain: Aligning technology, pedagogy and context.â The Electronic Journal of e-Learning Volume 6 Issue 3. Retrieved from www.ejel.org
Mentis, M. (2008) âNavigating the e-Learning terrain: Aligning technology, pedagogy and context.â The Electronic Journal of e-Learning Volume 6 Issue 3. Retrieved from www.ejel.org
Mentis, M. (2008) âNavigating the e-Learning terrain: Aligning technology, pedagogy and context.â The Electronic Journal of e-Learning Volume 6 Issue 3. Retrieved from www.ejel.org
Title: LIBRARIES, SOCIAL SOFTWARE AND DISTANCE LEARNERS: BLOG IT, TAG IT, SHARE IT! Authors: Secker, Jane Price, Gwyneth Source: New Review of Information Networking; May2007, Vol. 13 Issue 1, p39-52, 14p Social software â has been called Web 2.0 and for libraries has been called Library 2.0 Michael Habibâs image of Library 2.0 which is where social and academic places overlap Definition taken from Paul Millerâs Ariadne article in October 2005 Miller, Paul "Web 2.0: Building the New Libraryâ Ariadne Issue 45 30 Oct 2005 Available at: http://www.ariadne.ac.uk/issue45/miller/intro.html Paul Millerâs article also points out the dangers of libraries not getting involved: â "user's will bypass processes and institutions that they perceive to be slow unresponsive, unappealing and irrelevant" Need to compete with the likes of Amazon who make available RSS feeds of new books in different subject areas â academics could add these to their courses. But Library 2.0 in controversial â and there has been a reaction to it.
www.cerlim.ac.uk/conf/lww7/slides/SeckerPrice.ppt http://t1.ftcdn.net/jpg/00/10/05/64/110_F_10056459_BuHHVd3shz5jlhYCAmcyqaDEy6xjclBe.jpg Social software â explosion of web-based services that are based around participation & communication. Includes blogs (Blogger), wikis (wikipedia), social networking (facebook), media sharing (flickr) and clearly much much more. Social software is one aspect of web2.0, which has many descriptions but one writer describes it as encompassing six big and related, perhaps overlapping ideas â user generated content, Power of the crowd, data on an epic scale, architecture of participation, network effects and openness. A more simple definition is that Web1.0 was the read-only Web while Web2.0 is the read-write web and social software are the services that enable this. Itâs about: Blogs, Wikis Social networking tools Social bookmarking tools Resource sharing sites: Flickr, YouTube RSS technology underlies much of this
Source of banner: http://shiftingtheparadigm.org/
Source of image: http://www.cultivate-int.org/issue8/handscape/index.html Ask: When fragments of learning seems to be too scattered, how do you pull them together?
The quadrant illustrates reputation (y axis) against heterogeneity (x axis) with the four cells labeled primary (for high-high), illusionary (high-low), concealed (low-high) and submissive (low-low). Grover et al (2009) articulate a perspective that resource allocation for knowledge markets, such as universities, needs to consider behaviors rather than merely opinions.
Figure 12 illustrates individuals making a decision to adopt early, mid-late in a graphic showing a threshold to the diffusion curve.
Figure 12 illustrates individuals making a decision to adopt early, mid-late in a graphic showing a threshold to the diffusion curve.
As an exercise for learners, the TAM approach still has much to offer as a structure and a process for worthwhile exercises in designing a scholarly research study.
As an exercise for learners, the TAM approach still has much to offer as a structure and a process for worthwhile exercises in designing a scholarly research study.
As an exercise for learners, the TAM approach still has much to offer as a structure and a process for worthwhile exercises in designing a scholarly research study.
As an exercise for learners, the TAM approach still has much to offer as a structure and a process for worthwhile exercises in designing a scholarly research study.
Source of image: http://www.nyrealestatelawblog.com/j0438753.jpg