SETTING THE BOUNDARIES BETWEEN AUTOMATED AND HUMAN-CREATED TEXTS IN EFL TEACHING AND LEARNING IN THE ERA OF ARTIFICIAL INTELLIGENCE
The rise of artificial intelligence (AI) technology raises crucial questions in the field ofteaching and learning English as a foreign language. This study aims to show the impactof AI use on the development of EFL learners’ writing skills. This mixed-method basedresearch was a field research. 20 EFL teachers, 200 EFL learners and 02 AI experts wereembarked on the project. The research instruments deployed were questionnaires forteachers and learners, and a semi-structured interview with AI experts duringexperimental workshops where participants used AI tools to create literary texts. Theresults show that AI tools such as ChatGPT, Grammarly, Slick Write, and Ginger areprimarily perceived as facilitative tools for writing and correcting effectively, contributingto the improvement of EFL learners' grammatical and lexical skills. However, thesetechnologies raise concerns about a possible reduction in creativity and an increaseddependence on automated tools. The analysis of AI-generated texts revealed that, whiletechnically correct, they often lacked emotional depth and nuance compared to human-produced works. In fact, though AI offers significant advantages for teaching and learningEnglish as a foreign language, particularly in terms of accuracy and efficiency, it is essentialto preserve the creative dimension of writing. To face these challenges, AI tools should beintegrated in a way that complements traditional teaching methods, thus fostering abalanced approach that values both linguistic skills and the literary creativity of EFLlearners. Further research could explore long-term impacts, broadening the scope of AItools, and developing strategies for balanced integration to optimize language learningoutcomes.
Institutions
- Université d'Abomey-Calavi (BJ)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-09-16
- DOI
- https://doi.org/10.5281/zenodo.17128962
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00