Chatbot learning partners: Connecting learning experiences, interest and competence

聊天机器人 对话 能力(人力资源) 语言习得 计算机科学 心理学 万维网 数学教育 社会心理学 沟通
作者
Luke K. Fryer,Kaori Nakao,Andrew Thompson
出处
期刊:Computers in Human Behavior [Elsevier]
卷期号:93: 279-289 被引量:239
标识
DOI:10.1016/j.chb.2018.12.023
摘要

Conversation practice, while paramount for all language learners, can be difficult to get enough of and very expensive. In this mobile age, chatbots are an obvious means of filling this gap, but have yet to realize their potential as practice partners. The current study was undertaken to examine why chatbots are not yet a substantial instrument for language learning engagement/practice, and to provide direction for future practice and chatbot development. To this end, building on a recent experimental study examining chatbot novelty effects, students undertook a pair of conversation activities: human and human-chatbot (via speech-to-text software). Immediately following the practice conversations, students' interest in the two partners was surveyed and open-ended textual feedback was collected. With these data sources and prior standardised test results, regression and content analysis of the data was undertaken. Findings indicated: 1) prior interest in human conversation partners was the best single predictor of future interest in chatbot conversations; 2) prior language competency was more strongly linked to interest in chatbot than human conversations; 3) that the qualitative experience of having “learned more” with the chatbot was strongly connected to task interest, even when reporting communication difficulties. Implications for practicing languages with currently available chatbots, for chatbots and related educational technology as sources of student interest and directions for chatbots future development are discussed.
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