Clustering Students Based on Their Prior Knowledge [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (12th, Montreal, Canada, Jul 2-5, 2019).

Autor/inn/en	Khayi, Nisrine Ait; Rus, Vasile
Titel	Clustering Students Based on Their Prior Knowledge [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (12th, Montreal, Canada, Jul 2-5, 2019).
Quelle	(2019), (6 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	High School Students; Cluster Grouping; Prior Learning; Intelligent Tutoring Systems; Student Evaluation; Computation; Science Education; Scientific Concepts; Problem Solving; Physics; Science Tests; Force Concept Inventory + Suchen Sie Ihr Suchwort? High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Eingruppierung; Vorkenntnisse; Intelligentes Tutorsystem; Schulnote; Studentische Bewertung; Naturwissenschaftliche Bildung; Problemlösen; Physik
Abstract	In this paper, we applied a number of clustering algorithms on pretest data collected from 264 high-school students. Students took the pre-test at the beginning of a 5-week experiment in which they interacted with an intelligent tutoring system. The primary goal of this work is to identify clusters of students exhibiting similar knowledge patterns. In particular, we show that the DP-means clustering algorithm yields very good results using binary response data. Other clustering algorithms such as k-modes have demonstrated better results when using categorical response data. [For the full proceedings, see ED599096.] (As Provided).
Anmerkungen	International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01