AI-POWERED ADAPTIVE FEEDBACK IN BLENDED ENGLISH WRITING COURSES: A MULTIMODAL CORPUS ANALYSIS

Yusupova, Munzira

Қўқон ДПИ. Илмий хабарлар · 2026-yil

Annotatsiya

This paper puts forward a conceptual model for designing AI-based feedback systems capable of adapting to individual learners' needs. Two core ideas are advanced: a multimodal corpus architecture that brings together text, audio, video, and colour-coded annotation, and an Adaptive Feedback Alignment Index (AFAI) that measures how well feedback matches a given learner. A quasi-experimental research design and a set of measurement tools have been developed to test the model, and a worked example is provided to illustrate how the index would operate in practice. The paper closes with a set of hypotheses for testing at a later stage.

Maqola ma’lumotlari
MualliflarYusupova, Munzira
JurnalҚўқон ДПИ. Илмий хабарлар
Nashr sanasi2026-08-08
Jild8
Son7
Betlar510-516
TilIngliz
DOI10.70728/b.series.fil.v08.i07.079

Kalit so‘zlar

artificial intelligence, adaptive feedback, blended learning, academic writing, multimodal corpus, corpus linguistics, AFAI index, research design.

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