The impact of robot-assisted language learning (RALL) on EFL students’ classroom engagement and willingness to attend classes (WTAC): A technology acceptance model (TAM) perspective

Recently, a surge of scholarly attention has been paid to the impacts of Artificial Intelligence (AI) tools on second/foreign language (L2) education. Nonetheless, there is a lack of evidence on the role of AI-assisted robots or robot-assisted language learning (RALL) in English as a foreign language (EFL) students’ psycho-emotional factors and academic behaviors. To address this gap, drawing on the technology acceptance model (TAM), the present study probed into the impact of robot-assisted L2 education on Chinese EFL students’ classroom engagement and willingness to attend classes (WTAC). Two questionnaires were filled out by a sample of 155 students at the start and end of a four-month period of intervention. The participants were randomly assigned to a control group ( n = 80) and an experimental group ( n = 75). Robot-assisted instruction was given to the experimental group. The results of the analysis of covariance indicated that both classroom engagement and WTAC significantly improved among experimental group students from pre-test to post-test due to the intervention. The results are discussed concerning the theoretical and empirical evidence, and practical implications are presented to EFL educators and policymakers regarding the utility of adopting AI robots in L2 education.

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Publication Details

Journal
Language Teaching Research
Published
2026-04-30
DOI
https://doi.org/10.1177/13621688261441862
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
29.41
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article

The impact of robot-assisted language learning (RALL) on EFL students’ classroom engagement and willingness to attend classes (WTAC): A technology acceptance model (TAM) perspective

Lili Qin, Ali Derakhshan
1 citations
Language Teaching Research
AI in Service Interactions
29.41
article

The impact of robot-assisted language learning (RALL) on EFL students’ classroom engagement and willingness to attend classes (WTAC): A technology acceptance model (TAM) perspective

Lili Qin, Ali Derakhshan
article en
1 citations

Abstract

Recently, a surge of scholarly attention has been paid to the impacts of Artificial Intelligence (AI) tools on second/foreign language (L2) education. Nonetheless, there is a lack of evidence on the role of AI-assisted robots or robot-assisted language learning (RALL) in English as a foreign language (EFL) students’ psycho-emotional factors and academic behaviors. To address this gap, drawing on the technology acceptance model (TAM), the present study probed into the impact of robot-assisted L2 education on Chinese EFL students’ classroom engagement and willingness to attend classes (WTAC). Two questionnaires were filled out by a sample of 155 students at the start and end of a four-month period of intervention. The participants were randomly assigned to a control group ( n = 80) and an experimental group ( n = 75). Robot-assisted instruction was given to the experimental group. The results of the analysis of covariance indicated that both classroom engagement and WTAC significantly improved among experimental group students from pre-test to post-test due to the intervention. The results are discussed concerning the theoretical and empirical evidence, and practical implications are presented to EFL educators and policymakers regarding the utility of adopting AI robots in L2 education.

Language Teaching Research
Center for Applied Linguistics (US), Guangdong University of Foreign Studies (CN), Golestan University (IR)
Quality Education
Openalex Percentile: Top 1%
AI in Service Interactions
29.41
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