A Clustering Methodology of Web Log Data for Learning Management Systems

Autor/inn/en	Valsamidis, Stavros; Kontogiannis, Sotirios; Kazanidis, Ioannis; Theodosiou, Theodosios; Karakos, Alexandros
Titel	A Clustering Methodology of Web Log Data for Learning Management Systems
Quelle	In: Educational Technology & Society, 15 (2012) 2, S.154-167 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1436-4522
Schlagwörter	Foreign Countries; Electronic Learning; College Mathematics; Integrated Learning Systems; Data Collection; Curriculum Evaluation; Internet; Pattern Recognition; Client Server Architecture; Data Processing; Data Analysis; Greece + Suchen Sie Ihr Suchwort? Ausland; Data capture; Datensammlung; Curriculum; Evaluation; Curriculumevaluation; Lehrplan; Rahmenplan; Evaluierung; Mustererkennung; Datenverarbeitung; Auswertung; Griechenland
Abstract	Learning Management Systems (LMS) collect large amounts of data. Data mining techniques can be applied to analyse their web data log files. The instructors may use this data for assessing and measuring their courses. In this respect, we have proposed a methodology for analysing LMS courses and students' activity. This methodology uses a Markov CLustering (MCL) algorithm for clustering the students' activity and a SimpleKMeans algorithm for clustering the courses. Additionally we provide a visualisation of the results using scatter plots and 3D graphs. We propose specific metrics for the assessment of the courses based on the course usage. These metrics applied to data originated from the LMS log files of the Information Management Department of the TEI of Kavala. The results show that these metrics, if combined properly, can quantify quality characteristics of the courses. Furthermore, the application of the MCL algorithm to students' activities provides useful insights to their usage of the LMS platform. (Contains 2 tables and 8 figures.) (As Provided).
Anmerkungen	International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10