AI-assisted second-language teaching and learning in the Zone of Proximal Development
Jue Hou, Anh-Duc Vu, Anisia Katinskaia & Roman Yangarber, University of Helsinki, Finland
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https://doi.org/10.58379/VCHJ2886
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Volume 14, Issue 2, 2025
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Abstract: This paper presents the integration of AI features into the language-teaching platform, Revita. The system is an intelligent online tutor, developed to support learners from lower-intermediate toward advanced levels, in several languages. Target skills currently include grammar, vocabulary, aural comprehension, and pronunciation. Based on authentic texts uploaded by the learners themselves, the system creates a rich variety of exercises that are tailored to the individual learner’s level of proficiency. Revita’s main guiding principle is personalization, motivated by current theories from educational science, notably Vygotsky’s concept of the Zone of Proximal Development and dynamic assessment, as well as the principles of diagnostic assessment. The linguistic foundation for the system comes from Construction Grammar, the goal being to build a complete inventory of constructions in the target language, as the basis for judging the correctness of the learners’ responses to the exercises. Revita is enhanced with AI tools from natural language processing, machine learning, and educational data mining.
Keywords: personalized language teaching, artificial intelligence, computer-aided language learning, construction grammar, grammatical error correction, learning analytics