A framework for the adoption and diffusion of Personal Learning Environments in commercial organisations: an exploratory study in the learning and development sector in the UK

This study presents an exploratory approach to identify the main factors of Personal Learning Environment (PLE) adoption and diffusion within commercial organisations. Utilising an inductive investigative approach via the use of Grounded Theory methodology, relevant adoption factors were identified and their resulting influence during various stages of the innovation diffusion process were proposed. Data was collected using semi-structured interviews followed by systematic analysis using a three-staged coding process. The results revealed 10 factors affecting the adoption of PLEs influencing the innovation diffusion process at various stages. Informed by the Technology Acceptance Model and Innovation Diffusion Theory, the proposed model could have important implications for key decision makers within commercial organisations, while adopting, rejecting and assimilating new technological innovations (e.g. PLE) for learning delivery.

[1]  Matthias Jarke,et al.  The future of e-learning: a shift to knowledge networking and social software , 2007, Int. J. Knowl. Learn..

[2]  A. Strauss,et al.  The discovery of grounded theory: strategies for qualitative research aldine de gruyter , 1968 .

[3]  Donald W. Hofmann,et al.  Internet-Based Distance Learning in Higher Education , 2002 .

[4]  B. Glaser Basics of Grounded Theory Analysis: Emergence Vs. Forcing , 1992 .

[5]  R. Reardon,et al.  The Impact of Learning Culture on Worker Response to New Technology. , 2010 .

[6]  Yi-Shun Wang,et al.  Investigating the determinants and age and gender differences in the acceptance of mobile learning , 2009, Br. J. Educ. Technol..

[7]  Terje Väljataga,et al.  Personal Learning Environments: Concept or Technology? , 2011, Int. J. Virtual Pers. Learn. Environ..

[8]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[9]  Richard P. Bagozzi,et al.  The Legacy of the Technology Acceptance Model and a Proposal for a Paradigm Shift , 2007, J. Assoc. Inf. Syst..

[10]  Vallabh Sambamurthy,et al.  Sources of Influence on Beliefs about Information Technolgoy Use: An Empirical Study of Knowledge Workers , 2003, MIS Q..

[11]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[12]  Yueh-Min Huang,et al.  A blog article recommendation generating mechanism using an SBACPSO algorithm , 2009, Expert Syst. Appl..

[13]  Matthew B. Miles,et al.  Qualitative Data Analysis: An Expanded Sourcebook , 1994 .

[14]  Raluca Bunduchi,et al.  Process Innovation Costs in Supply Networks: A Synthesis , 2010 .

[15]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[16]  William R. King,et al.  Impacts of End-User and Information Center Characteristics on End-User Computing Support , 1994, J. Manag. Inf. Syst..

[17]  Albert H. Segars,et al.  Re-examining perceived ease of use and usefulness , 1993 .

[18]  Anselm L. Strauss,et al.  Basics of qualitative research : techniques and procedures for developing grounded theory , 1998 .

[19]  Rajiv Kishore,et al.  How robust is the UTAUT instrument?: a multigroup invariance analysis in the context of acceptance and use of online community weblog systems , 2006, SIGMIS CPR '06.

[20]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[21]  M. Wetzels To accept or not to accept : is that the question? , 2003 .

[22]  E. Waarts,et al.  The dynamics of factors affecting the adoption of innovations , 2002 .

[23]  Scott Wilson,et al.  Patterns of Personal Learning Environments , 2008, Interact. Learn. Environ..

[24]  Patrick Y. K. Chau,et al.  An Empirical Assessment of a Modified Technology Acceptance Model , 1996, J. Manag. Inf. Syst..

[25]  Christer Carlsson,et al.  Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[26]  Margaret Tan,et al.  Factors Influencing the Adoption of Internet Banking , 2000, J. Assoc. Inf. Syst..

[27]  Eric T. G. Wang,et al.  Understanding Web-based learning continuance intention: The role of subjective task value , 2008, Inf. Manag..

[28]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[29]  Graham Attwell,et al.  Personal Learning Environments - the future of eLearning? , 2007 .

[30]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[31]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[32]  Graham Pervan,et al.  An investigation of factors affecting technology acceptance and use decisions by Australian allied health therapists , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[33]  D. Francis Review of Basics of Qualitative Research Techniques and Procedures for Developing Grounded Theory (2nd edition) , 1999 .

[34]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[35]  Magid Igbaria,et al.  End-user computing effectiveness: A structural equation model , 1990 .