Adoption of a Social Learning Platform in Higher Education: An Extended UTAUT Model Implementation

The aim of this research is to investigate the factors influencing the adoption of a social learning platform called PairForm using an extended unified theory of acceptance and use of technology (UTAUT) model. The UTAUT extension consists of adding three personal characteristics of students, namely autonomy, anxiety, and attitude. Data obtained from 85 Frenchspeaking students and 14 English-speaking students at the Skema Business School, a higher education institution, showed good reliability coefficients and satisfactory convergent and discriminant validities. Regression analysis suggests the facilitating conditions construct is the main predictor of behavioral intention to use and behavioral use of PairForm. Attitude is the only personal characteristic that explains behavioral intention to use. In the light of these results, we propose recommendations that, if implemented, could create more favorable conditions for the use of social learning technologies.

[1]  David W. Gerbing,et al.  An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment , 1988 .

[2]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[3]  H. Celik Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework , 2016 .

[4]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[5]  Miroslava Raspopovic,et al.  The Effects of Integrating Social Learning Environment with Online Learning , 2017 .

[6]  Hager Khechine,et al.  UTAUT Model for Blended Learning: The Role of Gender and Age in the Intention to Use Webinars. , 2014 .

[7]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[8]  Ainin Sulaiman,et al.  Social media as a complementary learning tool for teaching and learning: The case of youtube , 2018 .

[9]  S. Thompson Social Learning Theory , 2008 .

[10]  Olabode Olatubosun,et al.  Direct Determinants of User Acceptance and Usage behavior of eLearning System in Nigerian Tertiary Institution of Learning , 2014 .

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

[12]  Emad AbuShanab,et al.  Internet Banking and Customers' Acceptance in Jordan: The Unified Model's Perspective , 2010, Commun. Assoc. Inf. Syst..

[13]  Amanda Langley Experiential learning, e-learning and social learning: the EES approach to developing blended learning , 2007 .

[14]  Suha AlAwadhi,et al.  The Use of the UTAUT Model in the Adoption of E-Government Services in Kuwait , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[15]  Hager Khechine,et al.  Student behavioural intentions to use desktop video conferencing in a distance course: integration of autonomy to the UTAUT model , 2013, J. Comput. High. Educ..

[16]  Yeoh Sok Foon,et al.  Internet Banking Adoption in Kuala Lumpur: An Application of UTAUT Model , 2011 .

[17]  Xiaojun Zhang,et al.  'Just What the Doctor Ordered': A Revised UTAUT for EMR System Adoption and Use by Doctors , 2011, 2011 44th Hawaii International Conference on System Sciences.

[18]  Curtis J. Bonk,et al.  The Future of Online Teaching and Learning in Higher Education: The Survey Says... , 2006 .

[19]  Lukas Furst,et al.  Multivariate Data Analysis With Readings , 2016 .

[20]  T. Thomas,et al.  The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana , 2013 .

[21]  Sawsen Lakhal,et al.  Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students' Outcomes Considering Personal Characteristics , 2018, J. Inf. Technol. Educ. Res..

[22]  R. J. Repique Digital Natives, Digital Immigrants , 2013, Journal of the American Psychiatric Nurses Association.

[23]  Marie Glenn,et al.  The future of higher education: How technology will shape learning , 2008 .

[24]  Xiaojun Zhang,et al.  "Doctors Do Too Little Technology": A Longitudinal Field Study of an Electronic Healthcare System Implementation , 2011, Inf. Syst. Res..

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

[26]  Nikos Bozionelos,et al.  Socio-economic background and computer use: the role of computer anxiety and computer experience in their relationship , 2004, Int. J. Hum. Comput. Stud..

[27]  Ken Kwong-Kay Wong,et al.  Partial Least Squares Structural Equation Modeling (PLS-SEM) Techniques Using SmartPLS , 2013 .

[28]  Anthony J. Onwuegbuzie,et al.  Typology of Analytical and Interpretational Errors in Quantitative and Qualitative Educational Research , 2003 .

[29]  Norman Vaughan,et al.  Teaching in Blended Learning Environments: Creating and Sustaining Communities of Inquiry , 2013 .

[30]  Il Im,et al.  The effects of perceived risk and technology type on users' acceptance of technologies , 2008, Inf. Manag..

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

[32]  J. W. Hutchinson,et al.  Dimensions of Consumer Expertise , 1987 .

[33]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[34]  Ayankunle A. Taiwo,et al.  THE THEORY OF USER ACCEPTANCE AND USE OF TECHNOLOGY ( UTAUT ) : A META-ANALYTIC REVIEW OF EMPIRICAL FINDINGS 1 , 2013 .

[35]  G. Johns The Essential Impact of Context on Organizational Behavior , 2006 .

[36]  Mark Moran,et al.  Students' Acceptance of Tablet PCs and Implications for Educational Institutions , 2011, J. Educ. Technol. Soc..

[37]  Hager Khechine,et al.  Relating personality (Big Five) to the core constructs of the Unified Theory of Acceptance and Use of Technology , 2017 .