{"title":"Online learners’ self-regulated learning skills regarding LMS interactions: a profiling study","authors":"","doi":"10.1007/s12528-024-09397-2","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>This profiling study deals with the self-regulated learning skills of online learners based on their interaction behaviors on the learning management system. The learners were profiled through their interaction behaviors via cluster analysis. Following a correlational model with the interaction data of learners, the post-test questionnaire data were used to determine self-regulated learning skills scores during the learning process. Regarding the scores, the clusters were named through the prominent interactions of the learners yielding three clusters; actively engaged (Cluster1), assessment-oriented (Cluster2), and passively-oriented (Cluster3), respectively. The profiles in the clusters indicate that assessments were mostly used by the learners in Cluster2, while the frequency of the content tools was high in Cluster1. Surprisingly, some tools such as glossary, survey, and chat did not play a prominent role in discriminating the clusters. Suggestions for future implementations of self-regulated learning and effective online learning in learning management systems are also included.</p>","PeriodicalId":15404,"journal":{"name":"Journal of Computing in Higher Education","volume":"145 1","pages":""},"PeriodicalIF":4.5000,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computing in Higher Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1007/s12528-024-09397-2","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
This profiling study deals with the self-regulated learning skills of online learners based on their interaction behaviors on the learning management system. The learners were profiled through their interaction behaviors via cluster analysis. Following a correlational model with the interaction data of learners, the post-test questionnaire data were used to determine self-regulated learning skills scores during the learning process. Regarding the scores, the clusters were named through the prominent interactions of the learners yielding three clusters; actively engaged (Cluster1), assessment-oriented (Cluster2), and passively-oriented (Cluster3), respectively. The profiles in the clusters indicate that assessments were mostly used by the learners in Cluster2, while the frequency of the content tools was high in Cluster1. Surprisingly, some tools such as glossary, survey, and chat did not play a prominent role in discriminating the clusters. Suggestions for future implementations of self-regulated learning and effective online learning in learning management systems are also included.
期刊介绍：
Journal of Computing in Higher Education (JCHE) contributes to our understanding of the design, development, and implementation of instructional processes and technologies in higher education. JCHE publishes original research, literature reviews, implementation and evaluation studies, and theoretical, conceptual, and policy papers that provide perspectives on instructional technology’s role in improving access, affordability, and outcomes of postsecondary education. Priority is given to well-documented original papers that demonstrate a strong grounding in learning theory and/or rigorous educational research design.
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