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Toward evidence-based learning analytics: Using proxy variables to improve asynchronous online discussion environments

Title
Toward evidence-based learning analytics: Using proxy variables to improve asynchronous online discussion environments
Authors
Kim, DonghoPark, YeonjeongYoon, MeehyunJo, Il-Hyun
Ewha Authors
조일현박연정
SCOPUS Author ID
조일현scopus; 박연정scopus
Issue Date
2016
Journal Title
INTERNET AND HIGHER EDUCATION
ISSN
1096-7516JCR Link1873-5525JCR Link
Citation
vol. 30, pp. 30 - 43
Keywords
Learning analyticsAsynchronous online discussionProxy variableEducational data miningLearner online behavior
Publisher
ELSEVIER SCIENCE INC
Indexed
SSCI; SCOPUS WOS scopus
Abstract
Although asynchronous online discussion (AOD) is increasingly used as a main activity for blended learning, many students find it difficult to engage in discussions and report low achievement. Early prediction and timely intervention can help potential low achievers get back on track as early as possible. This study presented a data mining process to construct proxy variables that reflect theoretical and empirical evidence and measured the accuracy of a prediction model that incorporated all of the variables for validation. For the empirical study, data were obtained from 105 university students who were enrolled in two blended learning courses that used AOD as their main activity. The results indicated the high accuracy of the prediction model as well as the possibility of early detection and timely interventions. In addition, we examined participants' learning behaviors in the two courses using the proxy variables and provided suggestions for practice. The implications of this study for education data mining and learning analytics are discussed. (C) 2016 Elsevier Inc. All rights reserved.
DOI
10.1016/j.iheduc.2016.03.002
Appears in Collections:
사범대학 > 교육공학과 > Journal papers
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