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Autor/inn/enSun, Di; Cheng, Gang; Xu, Pengfei; Zheng, Qinhua; Chen, Li
TitelUsing HMM to Compare Interaction Activity Patterns of Student Groups with Different Achievements in MPOCs
QuelleIn: Interactive Learning Environments, 27 (2019) 5-6, S.766-781 (16 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Sun, Di)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1049-4820
DOI10.1080/10494820.2019.1610780
SchlagwörterIntegrated Learning Systems; Online Courses; Educational Technology; Technology Uses in Education; Interaction; Large Group Instruction; Private Education; Open Universities; Foreign Countries; High Achievement; Low Achievement; Data Collection; Data Analysis; Learning Activities; China
AbstractWith the development of online learning, LMSs accumulated huge amounts of students' interaction data. Unfortunately, with the support of LMSs data, few researchers put a sight on interaction research in MPOCs. Particularly, comparing interaction activity patterns of different achievement student groups and in different course processes in MPOCs has been paid less attention. This paper generates hidden Markov models to identify frequently occurring interaction activity sequence patterns of High/Low achievement groups in the Learning/Exam processes under MPOCs settings. The results demonstrate that High-achievement students especially focused on content learning, assignments, and quizzes to consolidate their knowledge construction in both Learning and Exam processes, while Low-achievement students extremely did not perform the same. Further, High-achievement students adjusted their learning strategies based on the goals of different course processes; Low-achievement students were inactive in the learning process and opportunistic in the exam process. In sum, the comparative analysis implies that certain interaction patterns may distinguish the High-achievement students from the Low-achievement ones, and students change their patterns more or less based on different course processes. It is also helpful for students, instructors to adjust their strategies and make decisions, and for developers, and administrators to build recommendation systems based on objective and comprehensive information. (As Provided).
AnmerkungenRoutledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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