Work

From Theory to Practice: Integrating Generative AI ‐Powered Microlearning Into TESOL

Year: 2026

Type: article

Abstract: ABSTRACT This article offers practical strategies for integrating microlearning and generative artificial intelligence (GenAI) into TESOL instruction. It positions GenAI‐powered microlearning as a promising theory‐informed approach to meet the evolving demands of language teaching and learning in diverse global contexts. It also advances a conceptual framework that links second‐language acquisition (SLA), cognitive load theory, multimodal learning, and responsible implementation conditions such as teacher mediation, accessibility, transparency, and data protection. It argues that AI‐enhanced interactive tasks can support engagement, autonomy, and equitable access to knowledge when grounded in an integrated conceptual foundation of SLA, cognitive load theory, and multimodal learning. It introduces a design framework that stresses concision, interactivity, accessibility, and feedback and treats critical AI literacy and teacher–learner agency as constitutive design concerns rather than afterthoughts. In this framework, critical AI literacy functions as the evaluative mechanism through which teachers and learners question, revise, or reject AI‐generated input and feedback. Examples demonstrate how AI tools can support vocabulary, grammar, and pragmatics.

Source: TESOL Journal

DOI: 10.1002/tesj.70153

Author: Lucas Kohnke

Institution: Education University of Hong Kong

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $2,850