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

Il Hyun Jo, Dongho Kim, Meehyun Yoon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

32 Scopus citations

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.

Original languageEnglish
Title of host publicationLAK 2014
Subtitle of host publication4th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages183-187
Number of pages5
ISBN (Print)1595930361, 9781595930361
DOIs
StatePublished - 2014
Event4th International Conference on Learning Analytics and Knowledge, LAK 2014 - Indianapolis, IN, United States
Duration: 24 Mar 201428 Mar 2014

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Learning Analytics and Knowledge, LAK 2014
Country/TerritoryUnited States
CityIndianapolis, IN
Period24/03/1428/03/14

Keywords

  • Adult education
  • Big-data mining
  • Learning analytics
  • Log data
  • Time management strategy

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