THE IMPACT OF AI-ENHANCED TASK-BASED LANGUAGE TEACHNG(TBLT) ONORAL FLUENCY IN HIGHER EDUCATION: A MIXEDMETHODS STUDYTuychiev Abror Khabibulla ugli
Keywords:
Task-Based Language Teaching (TBLT), Generative AI (GenAI), Oral Fluency, Digital Scaffolding, Higher Education, Learner Autonomy, ComputerAssisted Language Learning (CALL), Feedback Loops.Abstract
This study investigates the efficacy of integrating Generative AI (GenAI)
scaffolding within a Task-Based Language Teaching (TBLT) framework to improve English oral fluency among university students. While TBLT has long been established as a premier methodology for communicative competence, limited practice opportunities and delayed feedback often hinder progress. In this 16-week study involving 60 EFL (English as a Foreign Language) students, an "Intelligent-TBLT" model was employed, utilizing AI tools like ChatGPT-4 and ELSA Speak to provide immediate feedback and digital scaffolding. Results from a mixed-methods analysis
indicate significant improvements in speech rate, reduced hesitation, and increased learner confidence. The findings suggest that while AI cannot replace human social nuances, it serves as a critical "digital collaborator" that reduces cognitive load and fosters learner autonomy.
