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Volume 14, Numéro 1, Pages 298-316
2025-12-12

Empathy-based Tutoring With Generative Ai For Personalized Support In Efl Speaking Classrooms



Authors : Rogti Maroua .

Abstract

One of the hardest things for EFL students to do is learn how to speak. Speaking skills are very important for learning a language, but they are often not developed enough, which means that students cannot fully benefit from the language learning process. Because of this, teachers are always looking for new and better techniques to improve students' speaking skills. One of the most interesting things in the 21st century education is the use of AI in language teaching. This study examines an empathy-driven teaching methodology utilizing generative AI to improve speaking proficiency and provide tailored emotional support in EFL contexts. The proposed methodology incorporates affective computing to assess learners' emotional engagement and utilizes large language models (LLMs) for empathic conversational answers and personalized feedback. A quasi-experimental approach will be utilized with a sample of forty EFL undergraduate students, contrasting an experimental group utilizing the empathy-enabled AI tutor ELSA with a control group engaged in traditional AI-based speaking practice. Quantitative data will undergo statistical analysis. The results indicate that AI-driven affective tutoring models can provide valuable insights for enhancing speaking proficiency and fostering emotional engagement through sympathetic AI tutors. Implications are suggested to incorporate practices for integrating emotional social intelligence into AI-powered EFL pedagogy.

Keywords

empathetic support ; AI tutoring systems ; EFL students ; speaking proficiency ; personalized support

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