AI-SUPPORTED FEEDBACK AND PROGRESS ASSESSMENT IN ELF: PEDAGOGICAL POSSIBILITIES AND CHALLENGES

2026

Closed access Metadata (CSL-JSON)
DOI 10.51889/2959-5657.2026.95.1.013
Data confidence 70 medium
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Abstract

The fast advancement of artificial intelligence (AI) has opened up new avenues for improving evaluation and feedback procedures in the teaching of English as a foreign language (EFL). Using new empirical data and theoretical viewpoints from second language acquisition, this article explores how AI-based technologies can help with feedback providing and progress evaluation. Artificial Intelligence technology, including speech recognition software, natural language processing, and automated writing evaluation, allow for continuous, data-driven monitoring of learners’ progress across language skills as well as instantaneous, personalized feedback. The article also discusses the ethical and pedagogical issues surrounding the incorporation of AI, including the difficulties in evaluating higher-order communication skills, the dangers of learners becoming overly dependent, and issues with algorithmic bias and data privacy. The results imply that although AI technologies can increase productivity, consistency, and learner autonomy, careful pedagogical application and ongoing instructor participation are necessary for them to be effective. The best methods for teaching EFL are hybrid models that combine human experience with AI-supported evaluation.