A1 Journal article (refereed)
Measuring self‐regulated learning in a junior high school mathematics classroom : Combining aptitude and event measures in digital learning materials (2023)


Zhidkikh, D., Saarela, M., & Kärkkäinen, T. (2023). Measuring self‐regulated learning in a junior high school mathematics classroom : Combining aptitude and event measures in digital learning materials. Journal of Computer Assisted Learning, 39(6), 1834-1851. https://doi.org/10.1111/jcal.12842


JYU authors or editors


Publication details

All authors or editors: Zhidkikh, Denis; Saarela, Mirka; Kärkkäinen, Tommi

Journal or series: Journal of Computer Assisted Learning

ISSN: 0266-4909

eISSN: 1365-2729

Publication year: 2023

Publication date: 15/06/2023

Volume: 39

Issue number: 6

Pages range: 1834-1851

Publisher: Wiley

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1111/jcal.12842

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/87918

Additional information: The article is based on a Master's thesis of the first author available from http://urn.fi/URN:NBN:fi:jyu-202106304100.


Abstract

Background
Measurement of students' self-regulation skills is an active topic in education research, as effective assessment helps devising support interventions to foster academic achievement. Measures based on event tracing usually require large amounts of data (e.g., MOOCs and large courses), while aptitude measures are often qualitative and need careful interpretation. Precise and interpretable evaluation of self-regulation skills in a normal K-12 classroom thus poses a challenge.

Objectives
The present study proposes and explores a learning analytics method of combining aptitude and event measures to evaluate student's self-regulation skills.

Methods
An explorative learning analytics study was conducted in a junior high school mathematics class (N = 20 students), using a three-lesson intervention with digital learning materials. Students first assessed their self-regulation skills with a self-report questionnaire, after which trace logs and observations of student behaviour were collected. Learning sessions were extracted from trace logs, clustered, and linked to learning strategies. Students were clustered by the self-report results and learning behaviour profiles. Session clusters, student behaviour clusters and assignment grades were also tested for association.

Results and Conclusions
The detected session and student behaviour types were linked to learning tactics and strategies found in prior studies. Additionally, association was found between self-reported self-regulation skills and the student behaviour obtained from trace logs.

Implications
The results demonstrate the feasibility of concurrently using aptitude and event measures on a classroom scale, providing teachers with a tool to evaluate and support self-regulated learning. Combined with further measures like predictive learning analytics, teachers can obtain an early and highly interpretable picture of at-risk students in their classes.


Keywords: learning; mathematics; self-regulation (psychology); upper comprehensive school; upper comprehensive school pupils; school children; measurement; evaluation; digital study material

Free keywords: aptitude measures; event measures; junior high school; learning analytics; mathematics; self-regulated learning


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2023

Preliminary JUFO rating: 2


Last updated on 2024-30-04 at 17:06