PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
November 9, 2025European Journal of Education4 citationsOpen Access

The Contribution of Artificial Intelligence ( AI ) Tools to Chinese Junior Middle School Students' Self‐Regulated Learning ( SRL ): An Interventional Mixed‐Methods Study

View Full Paper
ZXZhang XiaohuanYWYongliang Wang

Key Points

  • Self-regulated learning scores improved significantly in the experimental group post-intervention, demonstrating AI's positive impact on education.
  • Thematic analysis revealed AI contributed to enhanced classroom engagement and personalized learning paths among students.
  • Interventional mixed-methods research showed clear benefits of integrating AI tools within junior middle school education, highlighting the need for future studies.
  • Effective AI deployment in learning environments may require careful consideration of psycho-affective factors influencing student behavior.

Abstract

ABSTRACT Recently, the use of artificial intelligence (AI) technologies has developed many aspects of education, as reported by several studies. However, little research has been done on the impact of AI‐mediated education on junior middle school students' psycho‐affective factors and behaviours. To fill the gaps, this study took an interventional mixed‐methods research design to find out the contributions of AI tools to students' self‐regulated learning (SRL). A sample of 78 Chinese junior middle school students completed a questionnaire on SRL before and after an intervention period powered by AI tools. They were assigned to control ( n = 39) and experimental ( n = 39) groups. The results of the t‐test indicated a significant increase in the SRL mean score of the experimental group from pre‐test to post‐test, suggesting the efficacy of the intervention. Moreover, the results of thematic analysis, in the qualitative phase, revealed that AI technologies had contributed to Chinese junior middle school students' SRL by ‘enhancing classroom engagement’, ‘providing personalised learning path’, ‘offering real‐time and adaptive feedback’, and ‘encouraging an autonomous reflection on learning’. The findings are distinctly discussed, and implications are provided for the theory and practice of AI in junior middle school education. Directions are also provided for different stakeholders to encourage an AI‐powered education that takes learner psychology into account.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Xiaohuan et al. (2025) studied this question.

synapsesocial.com/papers/690fdce2f60c54d04ea38356https://doi.org/10.1111/ejed.70322
Ask AI
Helpful
Bookmark
Share
View Full Paper