Examining Students' Course Trajectories Using Data Mining and Visualization Approaches

Autor/inn/en	Maqsood, Rabia; Ceravolo, Paolo; Ahmad, Muhammad; Sarfraz, Muhammad Shahzad
Titel	Examining Students' Course Trajectories Using Data Mining and Visualization Approaches
Quelle	In: International Journal of Educational Technology in Higher Education, 20 (2023), Artikel 55 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Maqsood, Rabia)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
DOI	10.1186/s41239-023-00423-4
Schlagwörter	Foreign Countries; Computer Science; Undergraduate Students; Private Colleges; Information Retrieval; Data Analysis; Pattern Recognition; Learning Trajectories; Pakistan + Suchen Sie Ihr Suchwort? Ausland; Informatik; Privathochschule; Auswertung; Mustererkennung
Abstract	The heterogeneous data acquired by educational institutes about students' careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of students' performances, and rare attempts are made at the domain level that may benefit the educational institutes at large to gauge and improve their institutional effectiveness. Our work aims to fill this gap by examining students' transcripts data for identifying similar groups of students and patterns that might associate with these different cohorts of students based on: (a) difficulty level of a course category, (b) formation of course trajectories, and, (c) transitioning of students between different performance groups. We have exploited descriptive data mining and visualization methods to analyze transcript data of 1398 undergraduate Computer Science students of a private university in Pakistan. The dataset includes students' transcript data of 124 courses from nine distinct course categories. In the end, we have discussed our findings in detail, challenges, and, future work directions. (As Provided).
Anmerkungen	BioMed Central, Ltd. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://www.springer.com/gp/biomedical-sciences
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01