Which Log Variables Significantly Predict Academic Achievement? A Systematic Review and Meta-Analysis

Autor/inn/en	Wang, Qin; Mousavi, Amin
Titel	Which Log Variables Significantly Predict Academic Achievement? A Systematic Review and Meta-Analysis
Quelle	In: British Journal of Educational Technology, 54 (2023) 1, S.142-191 (50 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Mousavi, Amin)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.13282
Schlagwörter	Predictor Variables; Academic Achievement; Literature Reviews; Meta Analysis; Learning Analytics; Data Analysis + Suchen Sie Ihr Suchwort? Prädiktor; Schulleistung; Meta-analysis; Metaanalyse; Auswertung
Abstract	Technologies and teaching practices can provide a rich log data, which enables learning analytics (LA) to bring new insights into the learning process for ultimately enhancing student success. This type of data has been used to discover student online learning patterns, relationships between online learning behaviors and assessment performance. Previous studies have provided empirical evidence that not all log variables were significantly associated with student academic achievement and the relationships varied across courses. Therefore, this study employs a systematic review with meta-analysis method to provide a comprehensive review of the log variables that have an impact on student academic achievement. We searched six databases and reviewed 88 relevant empirical studies published from 2010 to 2021 for an in-depth analysis. The results show different types of log variables and the learning contexts investigated in the reviewed studies. We also included four moderating factors to do moderator analyses. A further significance test was performed to test the difference of effect size among different types of log variables. Limitations and future research expectations are provided subsequently. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01