Unleashing the power of perceived enjoyment: exploring Chinese undergraduate EFL learners' intention to use ChatGPT for English learning

Abstract

Purpose

This study intends to extend the unified theory of acceptance and use of technology (UTAUT) model by integrating perceived enjoyment as an intrinsic motivation so as to investigate factors influencing Chinese undergraduate English as a Foreign Language (EFL) students' intention to use ChatGPT for English learning.

Design/methodology/approach

A cross-sectional quantitative survey method research design was used in this study. Data were collected from 432 undergraduate students at two Chinese universities. The data analysis was carried out using SmartPLS 4, a computer software that employs the partial least squares structural equation modelling (PLS-SEM) technique. The analysis of the model was performed in two stages, including the assessment of reflective measurement model and structural model. The PLS predict was utilized to assess the model’s predicting power.

Findings

Findings showed that effort expectancy, performance expectancy, social influence and perceived enjoyment were positively related to Chinese undergraduate EFL learners' intention to use ChatGPT for English learning. Perceived enjoyment mediated the relationships between effort expectancy, performance expectancy, social influence and intention to use ChatGPT for English learning respectively.

Originality/value

Through incorporating the perceived enjoyment as an intrinsic motivation into the UTAUT model to explore factors that impact Chinese undergraduate EFL learners' intention to use ChatGPT for English learning, this study has extended the applicability of the UTAUT model and provide insights into factors affecting students' intention to utilize ChatGPT or other AI-based technologies for English learning.

Citation

Xu, X. and Thien, L.M. (2024), "Unleashing the power of perceived enjoyment: exploring Chinese undergraduate EFL learners' intention to use ChatGPT for English learning", Journal of Applied Research in Higher Education, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JARHE-12-2023-0555