Educational Data Mining for Discovering Hidden Browsing Patterns Using Non-Negative Matrix Factorization

Autor/inn/en	Mouri, Kousuke; Suzuki, Fumiya; Shimada, Atsushi; Uosaki, Noriko; Yin, Chengjiu; Kaneko, Keiichi; Ogata, Hiroaki
Titel	Educational Data Mining for Discovering Hidden Browsing Patterns Using Non-Negative Matrix Factorization
Quelle	In: Interactive Learning Environments, 29 (2021) 7, S.1176-1188 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Mouri, Kousuke) ORCID (Suzuki, Fumiya) ORCID (Shimada, Atsushi) ORCID (Yin, Chengjiu) ORCID (Kaneko, Keiichi) ORCID (Ogata, Hiroaki)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2019.1619594
Schlagwörter	Data Analysis; Textbooks; Electronic Publishing; Data Collection; Eye Movements; Behavior Patterns; Learning Analytics; College Freshmen; Foreign Countries; Japan (Tokyo) + Suchen Sie Ihr Suchwort? Auswertung; Textbook; Text book; Schulbuch; Lehrbuch; Elektronisches Publizieren; Data capture; Datensammlung; Augenbewegung; Studienanfänger; Ausland
Abstract	This paper describes a method to collect data of which section of pages learners were browsing in digital textbooks without eye-tracking technologies. In previous researches on digital textbook systems, it was difficult to collect such data without using eye-tackers. However, eye-trackers cost a massive budget. Our proposed system automatically hides the texts in the digital textbooks with mask processing before the learners browse the texts in the digital textbooks. If they click the hidden texts, the system gets rid of the masks and the texts appear letter by letter. We used NMF to discover learners' browsing patterns from the collected logs. Evaluation experiments were conducted to examine the effectiveness of our system in terms of fascination, understandableness and enhancement of thinking and to discover learners' browsing patterns. It was found that our method could enhance thinking skills. A browsing pattern of diligent learners with high learning achievements was also found. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01