Effects of Generative AI on Student Engagement in PBL-Based EFL Learning

This study examined the effects of generative AI-integrated project-based learning (PBL) on student engagement in an English as a foreign language (EFL) context. Adopting a mixed-methods design, the study investigated whether engagement differed by English proficiency level and gender during an AI-supported book-making project using ChatGPT. Quantitative data were collected through pre- and post-intervention questionnaires measuring four dimensions of student engagement: behavioral, emotional, cognitive, and agentic. Qualitative data were obtained from open-ended survey responses. Participants were 38 undergraduate students enrolled in a general English course. The results revealed that although high-proficiency students initially reported higher behavioral, emotional, and cognitive engagement, these differences were no longer significant at the post-test. Paired-samples analyses indicated that statistically significant gains across all four engagement dimensions occurred only among lowproficiency students, suggesting that AI-integrated PBL functioned as an equalizing instructional approach. Genderbased analyses showed no significant post-test differences across engagement dimensions, despite significant within-group gains among female students. Qualitative findings supported the quantitative results, demonstrating that AI tools reduced linguistic anxiety, supported strategic learning, and promoted active learner participation. Overall, the findings suggest that AI-integrated PBL can enhance multidimensional student engagement in EFL classrooms, particularly by supporting learners who face linguistic and affective challenges.

Authors

Publication Details

Journal
STEM Journal
Published
2026-02-28
DOI
https://doi.org/10.16875/stem.2026.27.1.38
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00
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article

Effects of Generative AI on Student Engagement in PBL-Based EFL Learning

Yoonjung Cha, Na-Young Kim
STEM Journal
Artificial Intelligence in Healthcare and Education
article

Effects of Generative AI on Student Engagement in PBL-Based EFL Learning

Yoonjung Cha, Na-Young Kim
article en

Abstract

This study examined the effects of generative AI-integrated project-based learning (PBL) on student engagement in an English as a foreign language (EFL) context. Adopting a mixed-methods design, the study investigated whether engagement differed by English proficiency level and gender during an AI-supported book-making project using ChatGPT. Quantitative data were collected through pre- and post-intervention questionnaires measuring four dimensions of student engagement: behavioral, emotional, cognitive, and agentic. Qualitative data were obtained from open-ended survey responses. Participants were 38 undergraduate students enrolled in a general English course. The results revealed that although high-proficiency students initially reported higher behavioral, emotional, and cognitive engagement, these differences were no longer significant at the post-test. Paired-samples analyses indicated that statistically significant gains across all four engagement dimensions occurred only among lowproficiency students, suggesting that AI-integrated PBL functioned as an equalizing instructional approach. Genderbased analyses showed no significant post-test differences across engagement dimensions, despite significant within-group gains among female students. Qualitative findings supported the quantitative results, demonstrating that AI tools reduced linguistic anxiety, supported strategic learning, and promoted active learner participation. Overall, the findings suggest that AI-integrated PBL can enhance multidimensional student engagement in EFL classrooms, particularly by supporting learners who face linguistic and affective challenges.

STEM JournalVol. 27(1)
Quality Education
Openalex Percentile: Top 27%
Artificial Intelligence in Healthcare and Education
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