Integrating LLM-based tutor into digital game-based learning for Chinese as a foreign language: impacts on language acquisition, motivation, and learning behaviours

Although Digital Game-Based Learning (DGBL) has been widely recognized as an effective approach for foreign language learning, its feedback mechanisms are often predefined and limited in adaptivity. Recent advances in large language models (LLMs) offer new opportunities to provide adaptive support within DGBL environments. This study investigates the impact of integrating an LLM-based tutor into a DGBL environment for Chinese as a foreign language (CFL) learning, focusing on language acquisition, motivation, and process-oriented learning behaviours.

A quasi-experimental study was conducted with 66 CFL learners, who were randomly assigned to either a DGBL + LLM-based tutor group or a DGBL-only group. Participants completed six 20-minute gameplay sessions across a two-week intervention. The LLM-based tutor provided real-time corrective feedback, metalinguistic explanations, and free-form Q&A.

Results showed that, after controlling for baseline performance, learners in the DGBL + LLM-based tutor group achieved significantly higher discourse comprehension and motivational intensity than those in the DGBL-only group. Within the LLM-based tutor group, learners also showed significant improvements in extrinsic motivation, intrinsic motivation, and self-confidence over the intervention. Behavioral sequence analysis further showed that learners in the DGBL + LLM-based tutor group were more likely to transition from error correction to subsequent correct responses, exhibited fewer voluntary gameplay interruptions, and alternated between asking questions and reviewing previous tutor explanations.

Together, these findings suggest that integrating an LLM-based tutor into DGBL can strengthen discourse learning while supporting learner motivation and more adaptive learning behaviours in CFL learning. This study was supported by " Research on Key Integration Pathways and Mechanisms of Digital and Intelligent Technologies for Chinese as a Second Language (CSL) Discourse Comprehension" 2024 China National Social Science Fund Youth Project, 24CYY085. School of Humanities, Beijing University of Posts and Telecommunications, Beijing, China Department of Human Development, Columbia University, New York, NY, USA College of International Studies, Southwest University, Chongqing, China Department of Curriculum and Instruction, University of Victoria, Victoria, BC, Canada Faculty of Informatics, Shizuoka University, Shizuoka, Japan Correspondence to Lu Fang or Yuhan Huang.

The authors declare no competing interests. All procedures performed in studies involving human participants were conducted in accordance with the ethical standards of the Institutional Review Board of Peking University and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Approval was granted by the Peking University Institutional Review Board in August 2024 (IRB approval number: 00001052-24082).

Informed consent was obtained in writing from all individual participants included in the study. Participants were fully informed of the purpose and procedures prior to data collection. Consent also covered the use of anonymized data for scholarly publication.