Beyond tool use: how ecological coupling configures AI’s empowerment for language learning engagement

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Authors: Lingya Ge, Yun Xia, Chengfang Yang
Cited by: 1
References: 32

Abstract

This study develops and tests an AI-empowerment Configural Model to explain how artificial intelligence (AI) empowers language learning engagement. Grounded in ecological systems theory (EST) and ecological affordance theory (EAT), the model theorizes AI as an interactive agent within the learning ecosystem. A mixed-methods study of 475 Chinese university language learners demonstrates that AI'S effect on engagement is significantly mediated by the perceived quality of its ecological coupling with teachers, peers, and the environment. Latent profile analysis (LPA) further identifies three distinct learner configurations: low coupling-low engagement, moderate coupling-moderate engagement and high coupling-high engagement, which systematically differ in their coupling of AI. The model ultimately shifts the paradigm from tool implementation to strategic ecological governance, providing a practical basis for designing learning environments that leverage synergistic human-AI coupling to foster deeper, sustained engagement.

Fields of Study & Subjects

Innovative Teaching and Learning Methods EFL/ESL Teaching and Learning Second Language Learning and Teaching

Publication details

Journal / source
Frontiers in Psychology
Publisher
Frontiers Media SA
Volume
17
Pages
1747355–1747355
Publication date
22 January 2026
Language
EN