Exploring Students Digital Activities and Performances through Their Activities Logged in Learning Management System Using Educational Data Mining Approach

Autor/inn/en	Bessadok, Adel; Abouzinadah, Ehab; Rabie, Osama
Titel	Exploring Students Digital Activities and Performances through Their Activities Logged in Learning Management System Using Educational Data Mining Approach
Quelle	In: Interactive Technology and Smart Education, 20 (2023) 1, S.58-72 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1741-5659
DOI	10.1108/ITSE-08-2021-0148
Schlagwörter	Learning Activities; Academic Achievement; Learning Management Systems; Data Analysis; Profiles; Foreign Countries; Undergraduate Students; Online Courses; Electronic Learning; Student Behavior; Saudi Arabia + Suchen Sie Ihr Suchwort? Lernaktivität; Schulleistung; Auswertung; Charakterisierung; Profilanalyse; Ausland; Online course; Online-Kurs; Student behaviour; Schülerverhalten; Saudi-Arabien
Abstract	Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the significance of the relationship between these profiles and the associated academic performance was tested statistically. Design/methodology/approach: The LMS delivers E-learning courses and keeps track of the students' activities. Investigating these students' digital activities became a real challenge. The diversity of students' involvement in the learning process was proven through the LMS which characterize students' specific profiles. The Educational Data Mining (EDM) approach was used to discover students' learning profiles and associated academic performances, where the activity log file exemplified their activities hosted in the LMS. The sample study data is from an undergraduate e-course hosted on the platform of Blackboard LMS offered at a Saudi University during the first semester of the 2019-2020 academic year. The chosen undergraduate course had 25 sections, and the students attending came from science, technology, engineering and math background. Findings: Results show three clusters based on the digital activities of the students. The correlation test shows the statistical significance and proves the effect of the student's profile on his academic performance. The data analysis shows that students with different profiles can still get similar academic performance using LMS. Originality/value: This empirical study emphasizes the importance of the EDM approach using clustering techniques which can help the instructor understand how students use the provided LMS content to learn and then can deliver them the best educational experience. (As Provided).
Anmerkungen	Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01