Effect of GenAI on EFL Learners’ Engagement and Motivation: A Systematic Review
The integration of generative artificial intelligence (GenAI) in English as a foreign language (EFL) learning and teaching has attracted considerable research attention. However, few reviews focused on the impact of GenAI on learners’ engagement and motivation, a crucial aspect of language learning. Therefore, this systematic review addresses this gap by examining 21 empirical studies published between January 2023 and July 2025, focusing on research design, research focus, and the roles and affecting factors of GenAI in EFL learning. Findings show an unbalanced distribution in research setting, educational level, intervention duration, GenAI tools, research method, data source and learning subjects. Tertiary education in China is the dominant setting. Most studies employed ChatGPT with short-term and intermediate-term intervention. Research data mainly came from questionnaires and interviews, and a mixed method design was adopted in most studies. The primary focus of the reviewed studies is writing skills, with a few examining other skills such as speaking and reading. GenAI played four roles in enhancing students’ engagement and motivation, namely, evaluator, resource provider, feedback provider, and conversation partner. The review suggests that future research can extend to secondary education, diversify the research tools and focus, and employ longitudinal studies.
Authors
- Yingliang Liu (ORCID: https://orcid.org/0000-0002-0538-2752)
- Yinuo Sun
Institutions
- Minzu University of China (CN)
- South Central Minzu University (CN)
- Wuhan University of Technology (CN)
Publication Details
- Journal
- Studies of Applied Linguistics in Asia
- Published
- 2026-09-18
- DOI
- https://doi.org/10.53941/sala.2026.100013
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00