Chatbot-based learning of logical fallacies in EFL writing: perceived effectiveness in improving target knowledge and learner motivation

聊天机器人 心理学 数学教育 计算机科学 自然语言处理
作者
Ruofei Zhang,Di Zou,Gary Cheng
出处
期刊:Interactive Learning Environments [Informa]
卷期号:32 (9): 5552-5569 被引量:54
标识
DOI:10.1080/10494820.2023.2220374
摘要

Chatbots have been increasingly applied for EFL education and demonstrated overall usefulness in improving knowledge and motivation, while this technology has yet to be used for learning logical fallacies (i.e. errors in reasoning) in EFL writing. However, knowledge of logical fallacies is essential, with which learners can avoid fallacies in EFL writing and have enhanced writing quality. To fill in the gap, this study investigated the perceived effectiveness of chatbots in developing knowledge of logical fallacy in EFL writing and enhancing learner motivation. Features of this learning method were also explored based on the comparison against website-based learning. Two groups of 15 Chinese EFL learners engaged in five-week autonomous, out-of-class, out-of-class learning of logical fallacies in EFL writing using a chatbot or a website. Semi-structured interviews, pre-post tests of fallacy knowledge and pre-post motivation questionnaires were conducted. The results showed that the chatbot was perceived as slightly less effective than the website in developing target knowledge but more effective in improving motivation. Compared to the website, chatbots were advantageous in high-quality human-computer interactions, study plan making, and high accessibility. Based on the research results, we discussed how this technology might influence fallacy learning based on the self-regulated learning framework.
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