Conversation with a Chatbot before an Online EFL Group Discussion and the Effects on Critical Thinking

Goda, Yoshiko; Yamada, Masanori; Matsukawa, Hideya; Hata, Kojiro; Yasunami, Seisuke

doi:10.12937/ejsise.13.1

Cited by 69 publications

(47 citation statements)

References 1 publication

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“…Consistent with much of the intelligent tutor research (Johnson & Lester, 2016), students have reported motivational benefits with Chatbots during a classroom task (Fryer, 2006). This early text-based study suggested that many students were more comfortable trying a new language with a Chatbot than with a Human partner.…”

Section: Technology For Enhancing Interest and Learningsupporting

confidence: 52%

“…It draws on past interactions to determine future questions and answers. Based on previous studies, Cleverbot is useful for motivating foreign language students (Fryer, 2006), as well as general users (Hill et al 2015), to communicate. Analysis of Cleverbot's interactions (Conaim, 2008) has also demonstrated that it is a grammatically clear conversationalist.…”

Section: Current Studymentioning

confidence: 99%

“…Based on past research (Fryer, 2006), we predicted that initially students would be more interested in spoken language learning tasks with an unfamiliar Chatbot partner than with a Human partner. Hence, to reduce the novelty of the Chatbot we gave all participating students a familiarizing experience with the Chatbot prior to the study.…”

Section: Aimsmentioning

confidence: 99%

“…Recently, research attention both in the area of language learning and general education, has focused on the potential of technological tools to enhance classroom motivation and thereby learning. One technology that has been suggested as a potentially powerful tool for enhancing students' language learning efforts is the area of Chatbots (Goda, et al, 2014;Stickler & Hampel, 2015;Fryer, 2006;Fryer & Nakao 2008;Conaim, 2008). Chatbots are software avatars with limited, but growing capability for conversation with human beings.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners

Fryer

Ainley

Thompson

et al. 2017

Computers in Human Behavior

253

119

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This is the accepted version prior to journal formatting. The official version can found at:https://authors.elsevier.com/a/1V8wS2f~UW0xXp-->FREE COPY the end of JULY 2017. Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners AbstractNovel technology can be a powerful tool for enhancing students' interest in many learning domains. However, the sustainability and overall impact of such interest is unclear. This study tests the longer-term effects of technology on students' task and course interest. The experimental study was conducted with students in foreign language classes (n=122): a 12-week experimental trial that included pre-and post-course interest, and a sequence of task interest measures. Employing a counterbalanced design, at three week intervals students engaged in separate speaking tasks with each of a Human and "Chatbot" partner. Students' interest in successive tasks and in the course (pre-post), were used to assess differential partner effects and course interest development trajectories. Comparisons of task interest under different partner conditions over time indicated a significant drop in students' task interest with the Chatbot but not Human partner. After accounting for initial course interest, Structural Equation Modelling indicated that only task interest with the Human partner contributed to developing course interest. While Human partner task interest predicted future course interest, task interest under Chatbot partner conditions did not. Under Chatbot partner conditions there was a drop in task interest after the first task: a novelty effect. Implications for theory and practice are discussed.

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Section: Technology For Enhancing Interest and Learningsupporting

confidence: 52%

Section: Current Studymentioning

confidence: 99%

Section: Aimsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners

Fryer

Ainley

Thompson

et al. 2017

Computers in Human Behavior

253

119

View full text Add to dashboard Cite

show abstract

“…In this sense, WebCL is a subset of CSCL. It includes E-mail, multimedia conference system, collaborative document editing, remote collaborative learning system, etc [6,7]. The inter-university collaborative learning based on network is a realization of CSCL on network platform, so that the theory and principles of CSCL can completely guide the practice of the present study.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

Wen-hui

Wang

2017

Open Physics

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Abstract:Learning evaluation is an e ective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are dicult to t the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

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How to Design and Deliver Courses for Higher Education in the AI Era?

Wazan,

Taj,

Shoufan

et al. 2024

General Aspects of Applying Generative AI in Higher Education

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Conversation with a Chatbot before an Online EFL Group Discussion and the Effects on Critical Thinking

Cited by 69 publications

References 1 publication

Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners

Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners

Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

How to Design and Deliver Courses for Higher Education in the AI Era?

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