The Electronic Journal of e-Learning provides perspectives on topics relevant to the study, implementation and management of e-Learning initiatives
For general enquiries email
Click here to see other Scholarly Electronic Journals published by API
For a range of research text books on this and complimentary topics visit the Academic Bookshop

Information about the current European Conference on e-Learning is available here

For infomation on the European Conference on Games Based Learning clickhere

SCImago Journal & Country Rank

Journal Article

Synthesizing Technology Adoption and Learners Approaches Towards Active Learning in Higher Education  pp442-451

Kevin Chan, George Cheung, Kelvin Wan, Ian Brown, Green Luk

© Dec 2015 Volume 13 Issue 6, ICEL 2015, Editor: Pandora Johnson, pp429 - 474

Look inside Download PDF (free)


Abstract: In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners variations, particularly regarding their styles and a pproaches to learning, on intention and use of learning technologies. This study contributes to further examine a working model for learning outcomes in higher education with the Unified Theory of Acceptance and Use of Technology (UTAUT) on SRS adoption attitude, and the Study Process Questionnaire (SPQ) on students approach to learning. Adopting a cross‑section observational design, the current study featured an online survey incorporating items UTAUT and SPQ. The survey was administered to 1627 und ergraduate students at a large comprehensive university in Hong Kong. Relationships between SRS adoption attitude, learning approaches, and learning outcomes in higher‑order thinking & learning and collaborative learning were analyzed with a structural eq uation model (SEM). A total of 3 latent factors, including four factors from UTAUT in Performance Expectancy, Effort Expectancy, and Deep Learning Approach from the SPQ, were identified in the structural model on students intention to adopt SRS in clas ses. Current results suggested that a model of active learning outcomes comprising both UTAUT constructs and deep learning approach. Model presented in the present study supported the UTAUT in predicting both behavioral intention and in adopting SRS in la rge classes of undergraduate education. Specifically, positive attitudes towards SRS use measured with the UTAUT, via a learning approach towards deep learning, accounted for variation on high‑impact learning including higher‑order thinking and collaborat ive learning. Results demonstrated that the process of technology adoption should be conceptualized in conjunction with learners diversity for explaining variation in adoption of technologies in the higher education context.


Keywords: Keywords: Technology adoption, Learning Approaches, Students Response System, SRS, Higher Education


Share |