Discovering Time Management Strategies in Learning Processes Using Process Mining Techniques

This paper reports the findings of a study that proposed a novel learning analytic methodology that combines process mining with cluster analysis to study time management in the context of blended and online learning. The study was conducted with first-year students (N = 241) who were enrolled in bl...

全面介紹

書目詳細資料
發表在:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
主要作者: Ahmad Uzir N.; Gašević D.; Matcha W.; Jovanović J.; Pardo A.; Lim L.-A.; Gentili S.
格式: Conference paper
語言:English
出版: Springer Verlag 2019
在線閱讀:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072948958&doi=10.1007%2f978-3-030-29736-7_41&partnerID=40&md5=bd41f41c3e2bb645a45f2e71c460c5c7
實物特徵
總結:This paper reports the findings of a study that proposed a novel learning analytic methodology that combines process mining with cluster analysis to study time management in the context of blended and online learning. The study was conducted with first-year students (N = 241) who were enrolled in blended learning of a health science course. The study identified four distinct time management tactics and three strategies. The tactics and strategies were interpreted according to the established theoretical framework of self-regulated learning in terms of student decisions about what to study, how long to study, and how to study. The study also identified significant differences in academic performance among students who followed different time management strategies. © 2019, Springer Nature Switzerland AG.
ISSN:3029743
DOI:10.1007/978-3-030-29736-7_41