Published February 6, 2026 | Version v1
Publication Open

DESIGNING AI-SUPPORTED LANGUAGE TASKS TO FOSTER COGNITIVE ENGAGEMENT

Authors/Creators

Description

Artificial intelligence is making language production easier, but it does not automatically make language learning deeper. When learners can generate sentences, essays, or ideas instantly, the risk is that thinking may be shortened while output becomes longer. This article approaches AI-supported language tasks from a linguo-cognitive perspective and asks a different question: not how AI helps students produce language, but how it can make them think through language. The paper argues that cognitive engagement emerges when learners question, reshape, and negotiate AI-generated content rather than consume it. AI is viewed not as a source of answers but as a stimulus for decision-making, reflection, and reasoning. Drawing on recent research in AI-assisted language learning and task-based pedagogy, the article highlights prompt design, adaptation of AI output, and iterative interaction as key pedagogical moves. AI-supported tasks become cognitively valuable when they slow learners down, require choices, and make reasoning visible. The article concludes that the real innovation of AI in language education lies not in automation, but in designing tasks where thinking cannot be outsourced.

Files

Ilm-fan 0809.pdf

Files (669.1 kB)

Name Size Download all
md5:db7f2434c050d4a9c52eab4d104a4f5e
669.1 kB Preview Download