Consistency of Students' Pace in Online Learning [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, Jul 1-3, 2009).

Autor/inn/en	Hershkovitz, Arnon; Nachmias, Rafi
Institution	International Working Group on Educational Data Mining
Titel	Consistency of Students' Pace in Online Learning [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, Jul 1-3, 2009).
Quelle	(2009), (10 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Foreign Countries; Psychometrics; Comparative Analysis; Correlation; Electronic Learning; Online Courses; Test Preparation; Secondary School Students; Learning Strategies; Web Based Instruction; Data; Information Retrieval; Data Analysis; Educational Strategies; Pacing; Time Factors (Learning); Semitic Languages; College Entrance Examinations; Israel + Suchen Sie Ihr Suchwort? Ausland; Psychometry; Psychometrie; Korrelation; Online course; Online-Kurs; Sekundarschüler; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Web Based Training; Daten; Auswertung; Lehrstrategie; Lerntempo; Arabisch; Hebräisch; Aufnahmeprüfung
Abstract	The purpose of this study is to investigate the consistency of students' behavior regarding their pace of actions over sessions within an online course. Pace in a session is defined as the number of logged actions divided by session length (in minutes). Log files of 6,112 students were collected, and datasets were constructed for examining pace rank consistency in three main situations: day/night sessions, beginning/end (for both situations, sessions of the same learning mode were taken), and a comparison between sessions from different learning modes. For each dataset, students were ranked twice, according to their pace in the two sub-groups, and these ranks were correlated. Results obtained with this study's data suggest that pace is sometimes not consistent, hence might not be considered as a characterizing measure for the whole learning period. A discussion of this study and further research is provided. (Contains 1 figure and 5 tables.) [For the complete proceedings, "Proceedings of the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, July 1-3, 2009)," see ED539041.] (As Provided).
Anmerkungen	International Working Group on Educational Data Mining. Available from: 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	2017/4/10