Tóm tắt
AI voice chatbots (AVCs) have been increasingly integrated in teaching and learning speaking due to their potential benefits for language learning. Current studies have mainly examined the impacts of AVCs on learners’ speaking performance and affective factors. Research on learner satisfaction with chatbot-integrated learning experiences remains scarce. This study aims to explore Vietnamese university students’ satisfaction with chatbot-human interaction across three dimensions, including language experience (LEX), design experience (DEX), and user experience (UEX) as guided by the chatbot-human interaction satisfaction model (CHISM). A quantitative research design was conducted with 80 EFL students who engaged in conversations with ChatGPT as a speaking partner over 8 weeks in a classroom setting. Data were collected through a questionnaire, and descriptive and inferential statistical analyses were employed using SPSS. The findings revealed that learners were highly satisfied with the chatbot-generated language, chatbot design, and overall learning experience. In addition, Pearson correlation results indicate a strong, positive association among the dimensions. The study contributes empirical evidence to the body of literature on learner satisfaction with chatbot-human interaction in speaking practice.
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