AI-assisted second-language teaching and learning in the Zone of Proximal Development
Bibliographic Data
| ID | 22225895 |
|---|---|
| Authors | Jue Hou (0000-0002-8441-8468), Anh-Duc Vu (0009-0005-1186-0510), Anisia Katinskaia (0000-0003-4137-6760), Roman Yangarber (0000-0001-5264-9870) |
| Year | 2025 |
| Volume | 14 |
| Issue | 2 |
| Pages | 92-122 |
| Publication date | 2025-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Studies in Language Assessment (JOURNAL) |
| Journal identifiers | ISSN: 2653-5335 • E-ISSN: 2653-5335 |
| Publisher | The Association for Language Testing and Assessment of Australia and New Zealand (PUBLISHER) |
| DOI | 10.58379/vchj2886 |
| OpenAlex | W4417348052 |
| Language | EN |
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
Correctness · Natural language · Upload · Educational and Psychological Assessments · Intelligent Tutoring Systems and Adaptive Learning · Language Development and Disorders
| Highly cited | No |
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