Integrating ‘ <scp>GPT</scp> ‐4o’ as an <scp>AI</scp> Tool Into K‐12 Contexts: Assessing Its Long‐Term Effects on Students' Self‐Regulated Learning ( <scp>SRL</scp> ) and Task Engagement Through Latent Growth Curve Modelling

ABSTRACT Grounded in self‐determination theory (SDT), this longitudinal study examined the potential of GPT‐4o, an artificial intelligence (AI) tool, in K‐12 school contexts by assessing its long‐term impact on high school students' self‐regulated learning (SRL) and task engagement. Furthermore, the study tracked the developmental trajectory of these constructs over the course of a semester through latent growth curve modelling (LGCM). In doing so, a total of 165 high school students, assigned to either a treatment group ( n = 100) or a control group ( n = 65), took part in this research. Students' SRL skills and task engagement were assessed at three separate intervals using two reliable questionnaires. The LGCM findings revealed a continuous upward trajectory in the outcomes of both treatment and control groups. The results derived from a ‘multivariate analysis of variance’ (MANOVA) further indicated that students in the treatment group showed significantly greater improvements in both SRL and task engagement. Our study contributes to the growing body of literature supporting the integration of AI tools in K‐12 school contexts to optimise students' learning outcomes.

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Publication Details

Journal
European Journal of Education
Published
2025-11-14
DOI
https://doi.org/10.1111/ejed.70329
Citations
16
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
55.12
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article

Integrating ‘ GPT ‐4o’ as an AI Tool Into K‐12 Contexts: Assessing Its Long‐Term Effects on Students' Self‐Regulated Learning ( SRL ) and Task Engagement Through Latent Growth Curve Modelling

Ali Derakhshan, Jie Zhang
16 citations
European Journal of Education
Innovative Teaching and Learning Methods
55.12
article

Integrating ‘ GPT ‐4o’ as an AI Tool Into K‐12 Contexts: Assessing Its Long‐Term Effects on Students' Self‐Regulated Learning ( SRL ) and Task Engagement Through Latent Growth Curve Modelling

Ali Derakhshan, Jie Zhang
article en
16 citations

Abstract

ABSTRACT Grounded in self‐determination theory (SDT), this longitudinal study examined the potential of GPT‐4o, an artificial intelligence (AI) tool, in K‐12 school contexts by assessing its long‐term impact on high school students' self‐regulated learning (SRL) and task engagement. Furthermore, the study tracked the developmental trajectory of these constructs over the course of a semester through latent growth curve modelling (LGCM). In doing so, a total of 165 high school students, assigned to either a treatment group ( n = 100) or a control group ( n = 65), took part in this research. Students' SRL skills and task engagement were assessed at three separate intervals using two reliable questionnaires. The LGCM findings revealed a continuous upward trajectory in the outcomes of both treatment and control groups. The results derived from a ‘multivariate analysis of variance’ (MANOVA) further indicated that students in the treatment group showed significantly greater improvements in both SRL and task engagement. Our study contributes to the growing body of literature supporting the integration of AI tools in K‐12 school contexts to optimise students' learning outcomes.

European Journal of EducationVol. 60(4)
North China University of Water Resources and Electric Power (CN), Golestan University (IR)
Openalex Percentile: Top 0%
Innovative Teaching and Learning Methods
55.12
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