Li, N., Zhang, L., Lau, K. L., & & Liang, Y. (2024). Predicting Chinese Language Learners' ChatGPT Acceptance in Oral Language Practices: The Role of Learning Motivation and Willingness to Communicate. Journal of Technology and Chinese Language Teaching, 15(1), 25-48.
[李诺恩, 张岚, 刘洁玲, & 梁宇. (2024). 预测中文学习者在口语练习中对ChatGPT的接受度：学习动机和交流意愿的作用. 科技与中文教学 (Journal of Technology and Chinese Language Teaching), 15(1), 25-48.]
Abstract/摘要：
Despite an increased interest in the potential benefits of ChatGPT for foreign language education, learners' intentions to use ChatGPT as a learning tool have so far received little research attention. This study aims at exploring Chinese language learners' acceptance of ChatGPT in oral language practices and its influencing factors based on the technology acceptance model (TAM). Data were collected from 375 Mongolian learners who learned Chinese as a foreign language (CFL) and analyzed by means of partial least squares structural equation modeling (PLS-SEM). The results indicated that learning motivation and willingness to communicate are critical antecedents of ChatGPT acceptance, and willingness to communicate has a critical mediating role on the link between the three motivational determinants (self-efficacy, utility value, and attainment value) and TAM variables. Prediction-oriented segmentation (POS) was further carried out and found unobserved heterogeneity among CFL learners' formation of ChatGPT acceptance rooted in the years of Chinese learning. The findings suggest the theoretical strengths of TAM in explaining CFL learners' adoption of AI-assisted language practices. Meanwhile, it underlies the importance to understand learners' psychological attributes before introducing technology-assisted speaking practices. Pedagogical insights into how to enhance ChatGPT acceptance among different learner populations were also offered. 尽管ChatGPT在外语教育中的潜在优势逐渐成为热点话题，但学习者将ChatGPT作为学习工具的意愿至今未受到充分的研究关注。本研究旨在基于技术接受模型（TAM），探究中文学习者在口语练习中对ChatGPT的接受度及其影响因素。研究数据收集自375名蒙古中文学习者，并采用偏最小二乘结构方程模型（PLS-SEM）进行分析。结果表明，学习动机和交流意愿是影响ChatGPT接受度的关键前因，而交流意愿在三个动机因素（自我效能、实用价值与成就价值）与TAM变量之间的关联路径中发挥着重要的中介作用。预测导向分割（POS）分析进一步揭示了不同学习年限的中文学习者在ChatGPT接受度形成机制中存在异质性。上述研究结果证实了TAM在解释中文学习者采纳AI辅助语言实践方面的理论优势。同时，这也强调在引入技术辅助中文口语练习活动前了解学习者心理的重要性。此外，本文针对如何增强ChatGPT在不同学习者群体中的接受度提出了教学建议。
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