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Journal Issue
Volume 13 Issue 6, ICEL 2015 / Dec 2015  pp429‑474

Editor: Pandora Johnson

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Editorial  pp429‑430

Pandora Johnson

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Social Media for Learning and Teaching Undergraduate Sciences: Good Practice Guidelines from Intervention  pp431‑441

Jyothi Thalluri, Joy Penman

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

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

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Abstract

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

 

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Visualisation and Gamification of e‑Learning and Programming Education  pp452‑465

Marie Olsson, Peter Mozelius, Jonas Collin

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Online Continuing Education for Health Professionals: Does Sticky Design Promote Practice‑relevance?  pp466‑474

Roxanne Ward Zaghab, Carlos Maldonado, Dongsook Whitehead, Felicia Bartlett, Magaly Rodriguez de Bittner

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