“To Use or Not to Use?” A Mixed-Methods Study on the Determinants of EFL College Learners’ Behavioral Intention to Use AI in the Distributed Learning Context

Summary

This mixed-methods study applied the technology acceptance model to examine what drives Chinese EFL learners' intention to use AI in distributed learning contexts. Contrary to classical TAM assumptions, the analysis revealed that perceived ease of use significantly predicts both perceived usefulness and attitude toward AI, with attitude mediating the relationship to behavioural intention, whilst perceived usefulness did not significantly predict either attitude or intention. Qualitative interviews with 15 learners provided contextual nuance to the statistical findings.

UK applicability

The findings may have limited direct applicability to UK EFL contexts, as the sample comprised Chinese college learners in a distributed learning environment with potentially distinct cultural, institutional, and technological factors. However, the methodological approach and the challenge to TAM assumptions could inform research on technology adoption in UK language education settings.

Key measures

Perceived ease of use; perceived usefulness; attitude toward AI; behavioural intention to use AI; structural equation modelling pathways; qualitative themes from semi-structured interviews

Outcomes reported

The study examined factors predicting behavioral intention to use AI among 464 Chinese EFL college learners using structural equation modelling and qualitative interviews. Key outcomes measured included perceived ease of use, perceived usefulness, attitude toward AI, and behavioural intention to use AI.

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