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

February 28, 2016

Online_Learner_01 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 approaches 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 undergraduate 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 equation 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 classes. 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 large 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 collaborative 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.

The Electronic Journal of e-Learning