ChatGPT as cognitive scaffolding in 5E-based science instruction: Effects on middle school students’ problem-solving competence
Nguyen Chi Le 1 , Ha Thi Nguyen 1 * , Quynh Thi Thuy Nguyen 1 , Lan Phu Hoang Nguyen 1 , The Van Tran 1 , Tu Anh Tran 2 , Quynh Viet Pham 3 , Giang Thi Nguyen 1
More Detail
1 University of Education – Vietnam National University, Hanoi, VIETNAM2 Nghe An University, Nghe An, VIETNAM3 Hanoi Metropolitan University, Hanoi, VIETNAM* Corresponding Author

Abstract

Problem-solving competence (PSC) is a central objective of contemporary science education; however, many students continue to experience difficulties when engaging in inquiry-based learning activities that require reasoning, reflection and solution refinement. This study investigated the effects of selective ChatGPT scaffolding embedded within the 5E instructional model—engage, explore, explain, elaborate, and evaluate—on middle school students’ PSC. A quasi-experimental design was conducted with 80 grade 9 students, including an experimental group receiving ChatGPT-supported 5E instruction and a control group receiving conventional 5E instruction. Unlike continuous AI integration, ChatGPT support was selectively provided during the explore and elaborate phases to facilitate inquiry reasoning, solution generation and reflective evaluation. PSC was assessed across three dimensions: problem understanding (PU), solution planning and implementation (SPI), and evaluation and improvement (EI). Baseline equivalence between groups was confirmed using independent-samples t-tests. Analysis of covariance results revealed a significant positive effect of the intervention on overall PSC, F (1, 77) = 6.080, p = .0159, partial η² = .073. Significant improvement was also observed for EI, F (1, 77) = 4.901, p = .0298, partial η² = .060, while SPI showed a positive trend, F (1, 77) = 2.953, p = .0898. No significant effect was observed on PU. The findings suggest that selective ChatGPT scaffolding is particularly effective in supporting reflective reasoning, evidence evaluation, and solution refinement in inquiry-based science learning environments.

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 22, Issue 8, August 2026, Article No: em2886

https://doi.org/10.29333/ejmste/19030

Publication date: 29 Jul 2026

Article Views: 18

Article Downloads: 8

Open Access References How to cite this article