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- Nora'ayu Ahmad Uzir
- School of Informatics The University of Edinburgh Edinburgh UK
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- Dragan Gašević
- Faculty of Information Technology Monash University Clayton Victoria Australia
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- Wannisa Matcha
- School of Informatics The University of Edinburgh Edinburgh UK
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- Jelena Jovanović
- School of Business Administration University of Belgrade Belgrade Serbia
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- Abelardo Pardo
- Division of Information Technology, Engineering and the Environment University of South Australia Adelaide South Australia Australia
抄録
<jats:title>Abstract</jats:title><jats:p>This paper aims to explore time management strategies followed by students in a flipped classroom through the analysis of trace data. Specifically, an exploratory study was conducted on the dataset collected in three consecutive offerings of an undergraduate computer engineering course (<jats:italic>N</jats:italic> = 1,134). Trace data about activities were initially coded for the timeliness of activity completion. Such data were then analysed using agglomerative hierarchical clustering based on Ward's algorithm, first order Markov chains, and inferential statistics to (a) detect time management tactics and strategies from students' learning activities and (b) analyse the effects of personalized analytics‐based feedback on time management. The results indicate that meaningful and theoretically relevant time management patterns can be detected from trace data as manifestations of students' tactics and strategies. The study also showed that time management tactics had significant associations with academic performance and were associated with different interventions in personalized analytics‐based feedback.</jats:p>
収録刊行物
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- Journal of Computer Assisted Learning
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Journal of Computer Assisted Learning 36 (1), 70-88, 2019-10-10
Wiley
