Improving L2 vocabulary retention and learning engagement through L1 traditional stories in review activities using ChatGPT-generated questions

This study investigates the effects of incorporating first language (L1) traditional stories into second language (L2) vocabulary review activities on vocabulary retention and learning engagement, with the use of ChatGPT as a tool to assist the teacher in generating review materials. A total of 79 freshmen majoring in Computer Science participated, with 41 in the experimental group and 38 in the control group. In both groups, ChatGPT was used by the teacher to generate multiple-choice questions for the vocabulary review activities, with the experimental group incorporating Chinese traditional stories into the questions, while the control group used questions generated without these stories. This approach helped reduce the teacher’s workload while maintaining their central role in guiding the learning process. Research instruments included a pretest and a posttest to assess vocabulary retention, a questionnaire to measure behavioral, emotional, and cognitive dimensions of learning engagement, and online interviews to explore students’ attitudes towards the use of traditional stories. The results reveal that integrating Chinese traditional stories significantly enhanced students’ behavioral and emotional engagement and improved vocabulary retention. However, it did not significantly affect cognitive engagement, which remained high across both groups. The study also examines the correlations between engagement dimensions and provides insights into potential explanations for these findings, suggesting areas for future research to further optimize L2 vocabulary learning experiences.

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Publication Details

Journal
Language Teaching Research
Published
2026-02-16
DOI
https://doi.org/10.1177/13621688251413650
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Improving L2 vocabulary retention and learning engagement through L1 traditional stories in review activities using ChatGPT-generated questions

Zi-Gang Ge, Zi-Huan Qi
Language Teaching Research
Intelligent Tutoring Systems and Adaptive Learning
article

Improving L2 vocabulary retention and learning engagement through L1 traditional stories in review activities using ChatGPT-generated questions

Zi-Gang Ge, Zi-Huan Qi
article en

Abstract

This study investigates the effects of incorporating first language (L1) traditional stories into second language (L2) vocabulary review activities on vocabulary retention and learning engagement, with the use of ChatGPT as a tool to assist the teacher in generating review materials. A total of 79 freshmen majoring in Computer Science participated, with 41 in the experimental group and 38 in the control group. In both groups, ChatGPT was used by the teacher to generate multiple-choice questions for the vocabulary review activities, with the experimental group incorporating Chinese traditional stories into the questions, while the control group used questions generated without these stories. This approach helped reduce the teacher’s workload while maintaining their central role in guiding the learning process. Research instruments included a pretest and a posttest to assess vocabulary retention, a questionnaire to measure behavioral, emotional, and cognitive dimensions of learning engagement, and online interviews to explore students’ attitudes towards the use of traditional stories. The results reveal that integrating Chinese traditional stories significantly enhanced students’ behavioral and emotional engagement and improved vocabulary retention. However, it did not significantly affect cognitive engagement, which remained high across both groups. The study also examines the correlations between engagement dimensions and provides insights into potential explanations for these findings, suggesting areas for future research to further optimize L2 vocabulary learning experiences.

Language Teaching Research
Beijing University of Posts and Telecommunications (CN), Hebei University (CN)
Quality Education
Openalex Percentile: Top 56%
Intelligent Tutoring Systems and Adaptive Learning
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