Work

Acceptance and Engagement in Artificial Intelligence–Supported Reading Among Primary School Learners of English as a Foreign Language

Year: 2026

Type: article

Abstract: ABSTRACT Artificial intelligence (AI) is increasingly used to support language learning, yet little is known about how younger learners accept and engage with AI‐assisted reading. This study investigates primary school students’ acceptance of and engagement with an AI‐supported adaptive reading application for English as a Foreign Language (EFL). Guided by the Motivational Technology Acceptance and Engagement Model (MTAEM), which integrates the Technology Acceptance Model and Self‐Determination Theory, the study examines how psychological needs shape technology acceptance and learner engagement. Data were collected from 631 pupils in China through structured questionnaires after using an AI reading app that provides personalised text recommendations and automated feedback during reading activities. Structural equation modelling showed that autonomy, competence, and relatedness support predicted psychological needs satisfaction, which in turn influenced perceived ease of use, perceived usefulness, and behavioural intention. Acceptance constructs also contributed to behavioural, emotional, cognitive, and agentic engagement. The findings highlight the importance of motivationally supportive AI design for fostering young learners’ engagement in EFL reading.

Source: International Journal of Applied Linguistics

DOI: 10.1111/ijal.70204

Authors: Mi Tang, Kunjie Jia, Huimin He, Chenghao Wang, Bin Zou, Yiran Du

Institutions: Chinese University of Hong Kong, Xi’an Jiaotong-Liverpool University, University of Cambridge

Language: English

Topic: EFL/ESL Teaching and Learning

Subfield: Language and Linguistics

Field: Arts and Humanities

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,240