Applying Generative Artificial Intelligence to Task-based Language Teaching and Learning: A Systematic Review and Meta-analysis

• In Event: Teaching and Learning with GenAI

Abstract

Generative artificial intelligence (GenAI) is increasingly recognized for its impact on student language performance, yet few meta-analyses have examined instructional factors. This study employs task-based language teaching (TBLT) to explore how task-based variables and learner factors influence language learning in GenAI contexts. Analyzing 25 empirical studies with 2,431 participants, we confirm GenAI's positive effect on language learning and identify three moderators: student AI literacy, task planning, and task assessors. The findings suggest that teachers should engage more in language learning with GenAI and that language-specific GenAI tools need to be developed, guiding institutions in AI-era instruction planning.

Authors

• Yan LI, The Education University of Hong Kong

• Rustam Shadiev, Zhejiang University

• Thomas K.F. Chiu, The Chinese University of Hong Kong