Modelling Within-Person Idiographic Variance Could Help Explain and Individualize Learning

Autor/in	Saqr, Mohammed
Titel	Modelling Within-Person Idiographic Variance Could Help Explain and Individualize Learning
Quelle	In: British Journal of Educational Technology, 54 (2023) 5, S.1077-1094 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Saqr, Mohammed)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.13309
Schlagwörter	Learning Analytics; Generalizability Theory; Models; Grades (Scholastic); Individual Differences; Predictor Variables + Suchen Sie Ihr Suchwort? Analogiemodell; Notenspiegel; Individueller Unterschied; Prädiktor
Abstract	Learning analytics is a fast-growing discipline. Institutions and countries alike are racing to harness the power of using data to support students, teachers and stakeholders. Research in the field has proven that predicting and supporting underachieving students is worthwhile. Nonetheless, challenges remain unresolved, for example, lack of generalizability, portability and failure to advance our understanding of students' behaviour. Recently, interest has grown in modelling individual or within-person behaviour, that is, understanding the person-specific changes. This study applies a novel method that combines within-person with between-person variance to better understand how changes unfolding at the individual level can explain students' final grades. By modelling the within-person variance, we directly model where the process takes place, that is the student. Our study finds that combining within- and between-person variance offers a better explanatory power and a better guidance of the variables that could be targeted for intervention at the personal and group levels. Furthermore, using within-person variance opens the door for person-specific idiographic models that work on individual student data and offer students support based on their own insights. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01