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Chou, Chien; Peng, Hsinyi; Chang, Chun-Yu – Computers & Education, 2010
This study explores the interactivity of course-management systems (CMSs). First, this study reviews the concepts of interactivity, interactivity dimension, and interaction type on the basis of related theories and studies. Second, this study analyzes the interactive functions attributable to the six major CMSs in Taiwan colleges and universities,…
Descriptors: Electronic Learning, Instructional Design, Student Attitudes, Interaction
Lorenzo, Carlos-Miguel; Sicilia, Miguel Angel; Sanchez, Salvador – Computers & Education, 2012
Massively Multiuser On-line Learning (MMOL) Platforms, often called "virtual learning worlds", constitute a still unexplored context for communication-enhanced learning, where synchronous communication skills in an explicit social setting enhance the potential of effective collaboration. In this paper, we report on an experimental study of…
Descriptors: Educational Technology, Evaluation Methods, Student Participation, Interaction
Huang, Chenn-Jung; Wang, Yu-Wu; Huang, Tz-Hau; Chen, Ying-Chen; Chen, Heng-Ming; Chang, Shun-Chih – Computers & Education, 2011
Recent research indicated that students' ability to construct evidence-based explanations in classrooms through scientific inquiry is critical to successful science education. Structured argumentation support environments have been built and used in scientific discourse in the literature. To the best of our knowledge, no research work in the…
Descriptors: Electronic Learning, Feedback (Response), Persuasive Discourse, Teaching Load
Ozkan, Sevgi; Koseler, Refika – Computers & Education, 2009
There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a…
Descriptors: Content Validity, Predictive Validity, Factor Analysis, Internet
Macfadyen, Leah P.; Dawson, Shane – Computers & Education, 2010
Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…
Descriptors: Network Analysis, Academic Achievement, At Risk Students, Prediction

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