a methodology for choosing

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Technology Adoption A methodology for choosing between good, better and best

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Page 1: A Methodology for Choosing

Technology AdoptionA methodology for choosing between good, better and best

Page 2: A Methodology for Choosing

Innovations

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COHERE 2013A methodology for choosing between good, better and bestRichard Rush

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Introduction

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Innovation Adoption

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What do we care about adoption?

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Stages of Adoption

Knowledge

Persuasion

Decision

Implementation

Confirmation

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Adopter “Cohorts”

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Governance for Ed Tech

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Why Governance?

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Forms of Governan

ce

Committees and

Councils

Distributed Decisions

Independent UsersCentral

Directed

Cascade

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Cascade ModelBoard of Governors

Institutional Strategic Plans

Executive Priorities

Academic Priorities

Ed Tech Steering Committee

Project Team Execution

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Models of IdentificationKnowledge Stage

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Three common inputs

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Problem looking for a solution

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Solution looking for a problem

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Isomorphism

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Models of EvaluationPersuasion Stage

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Persuasion

IF TO ADOPT WHICH TO ADOPT

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Trial and Error

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Specifications Match

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Isomorphism – Part 2

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Models of SelectionDecision Stage

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Mandated Model

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Request for Proposal

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Isomorphism – Part 3

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Considerations for Implementation

Implementation Stage

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Project Management

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Orientation

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Training

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Cultural

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Lesson’s LearnedConfirmation Stage

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References Barak, M. (2010). Motivating self-regulated learning in technology education. International Journal of Technology & Design Education, 20(4), 381-401.

Beath, C. M. (1991). Supporting the information technology champion. MIS Quarterly, 15(3), 355-372.

Benamati, J., & Lederer, A. L. (2001). Rapid information technology change, coping mechanisms, and the emerging technologies group. Journal of Management Information Systems, 17(4), 183-202.

Cheney, P. H., Mann, R. I., & Amoroso, D. L. (1986). Organizational factors affecting the success of end-user computing. Journal of Management Information Systems, 3(1), 65-80.

Devaraj, S., & Kohli, R. (2003). Performance impacts of information technology: Is actual usage the missing link? Management Science, 49(3), 273-289.

Hartwick, J., & Barki, H. (1994). Explaining the role of user participation in information system use. Management Science, 40(4), 440.

Jasperson, J. (Sean), Carter, P. E., & Zmud, R. W. (2005). a comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems1. MIS Quarterly, 29(3), 525-557.

Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.

Karuppan, Corinne M. & Karuppan, Muthu. (2008). Resilience of super users' mental models of enterprise-wide systems. European Journal of Information Systems, 17(1), 29-46.

Lee, G., & Xia, W. (2005). The ability of information systems development project teams to respond to business and technology changes: A study of flexibility measures. European Journal of Information Systems, 14(1), 75.

Leonard-Barton, D. (1988). Implementation as mutual adaptation of technology and organization. Research Policy, 17(5), 251.

Moore, G. (2001). Crossing the Chasm (ePub. ed.), HarperCollins e-books.

Odhabi, H. (2007). Investigating the impact of laptops on students’ learning using bloom's learning taxonomy. British Journal of Educational Technology, 38(6), 1126-1131.

Palvia, S. C. (2000). Effectiveness of asynchronous and synchronous modes for learning computer software for end users: An experimental investigation. The Journal of Computer Information Systems, 41(2), 99.

Rogers, Everett M. (2003). Diffusion of Innovations (5th ed.), New York, NY: Free Press.

Tyre, M. J., & Orlikowski, W. J. (1993). Exploiting opportunities for technological improvement in organizations. Sloan Management Review, 35(1), 13.

Note: Logos and trademarks are owned by their respective organizations. All unlabeled images from Microsoft office collection of clipart or SmartArt, except image of author.

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