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Journal Issue
Volume 12 Issue 4 / Jul 2014  pp313‑410

Editor: Dr Rikke Ørngreen, Dr Karin Tweddell Levinsen

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iSELF: The development of an Internet‑Tool for Self‑Evaluation and Learner Feedback  pp313‑325

Nicolet Theunissen, Hester Stubb

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Improving Virtual Collaborative Learning through Canonical Action Research  pp326‑338

Peter Weber, Christian Lehr, Martin Gersch

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Social media, Collaboration and Social Learning … a Case‑study of Foreign Language Learning  pp339‑352

Margrethe Mondahl, Liana Razmerita

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Pilot Program of Online Learning in Three Small High Schools: Considerations of Learning Styles  pp353‑366

Abigail Garthwait

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Impact of Multi‑media Tutorials in a Computer Science Laboratory Course … An Empirical Study  pp367‑375

Medha Dalal

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Student Online Readiness Assessment Tools: A Systematic Review Approach  pp376‑384

Farid Alem, Michel Plaisent, Prosper Bernard, Okoli Chitu

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ENTEL: A Case Study on Knowledge Networks and the Impact of Web 2.0 Technologies  pp385‑395

Paul Griffiths, Teresita Arenas

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Impact of Learner's Characteristics and Learning Behaviour on Learning Performance during a Fully Online Course  pp396‑410

Minoru Nakayama, Kouichi Mutsuura, Hiroh Yamamoto

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Abstract

Abstract: A fully online learning environment requires effective learning management in order to promote pro‑active education. Since students notes are a reflection of the progress of their education, analysis of notes taken can be used to track the lear ning process of students who participate in fully online courses. This paper presents the causal relationships between students characteristics, note‑taking behaviour, learning experience, note assessment and test scores while the relationships between t hese metrics is examined. A fully online course for undergraduate students in Economics was conducted. Participants were asked to study each course module and present their notes to the lecturer every week. The students learning performance was then meas ured using online tests, weekly confirmation tests, and a final exam. The total number of valid participants in the courses was 53. Three factors of note‑taking behaviour were extracted according to the survey, and their relationships with other metrics w ere calculated. A structural equation modeling technique was used to track students learning activity as note‑taking occurred, using the scores of their metrics. The results of this modeling technique suggest that key factors and their contributions to t est scores can be measured. Also, the factors which contribute to note‑taking behaviour were examined. 

 

Keywords: Keywords: Note taking, Fully online course, Learning assessment, Causal analysis

 

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