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Analyzing the log patterns of adult learners in LMS using learning analytics

Cited 0 time in Web of Science Cited 51 time in Scopus
Authors

Jo, Il-Hyun; Kim, Dongho; Yoon, Meehyun

Issue Date
2014
Publisher
Association for Computing Machinery
Citation
ACM International Conference Proceeding Series, pp.183-187
Abstract
In this paper, we describe a process of constructing proxy variables that represent adult learners' time management strategies in an online course. Based upon previous research, three values were selected from a data set. According to the result of empirical validation, an (ir)regularity of the learning interval was proven to be correlative with and predict learning performance. As indicated in previous research, regularity of learning is a strong indicator to explain learners' consistent endeavors. This study demonstrates the possibility of using learning analytics to address a learner's specific competence on the basis of a theoretical background. Implications for the learning analytics field seeking a pedagogical theory-driven approach are discussed. Copyright © 2014 by the Association for Computing Machinery, Inc.
URI
https://hdl.handle.net/10371/219145
DOI
https://doi.org/10.1145/2567574.2567616
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Related Researcher

  • College of Agriculture and Life Sciences
  • Department of Vocational Education and Workforce Development
Research Area AI-Human Interaction, People Analytics, Technology-Based Career Development

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