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      Investigation of the Influence of Artificial Intelligence Markup Language-Based LINE ChatBot in Contextual English Learning

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          Abstract

          This study is intended to create an innovative contextual English learning environment making use of the widely used communication software, LINE ChatBot, based on the Artificial Intelligence Markup Language (AIML), in order to improve speaking and listening ability among learners. A total of 73 students were invited to participate in learning activities involving a 4-week English conversation exercise including both speaking and listening. Additionally, in order to explore the influence of competition on language acquisition, we added competition characteristics to the learning activities in the experimental group to enhance learning motivation and learning outcomes. The results showed that with the help of the LINE ChatBot contextual learning environment, the performance of both groups of students was slightly enhanced, but no significant differences were found. Meanwhile, extrinsic motivation in both the experimental and control group was improved if they spoke anonymously. That is, the contextual learning environment based on the LINE ChatBot significantly improved the learners’ English speaking and listening ability. In addition, the results showed that the addition of a competition element effectively enhanced the learners’ intrinsic motivation to learn English on the LINE ChatBot.

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          Most cited references35

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          Personalized mobile English vocabulary learning system based on item response theory and learning memory cycle

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            Acceptance and usage of mobile assisted language learning by higher education students

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              Review of Studies on Technology-Enhanced Language Learning and Teaching

              In this study, we reviewed articles on technology-enhanced language learning and teaching. We aimed to summarize the content of reviewed articles in the following categories: (1) the number of articles published by journals and by year; (2) languages and skills; (3) technology used; (4) promising technologies. We reviewed 398 research articles. The highest number of articles was published in 2017 (n = 80), whereas the lowest number was published in 2014 (n = 53). The Computer Assisted Language Learning journal published the highest number of articles (n = 100), whereas the lowest number of published articles appeared in IEEE Transactions on Learning Technologies (n = 3). The most common target language was English (n = 267). Writing, speaking, and vocabulary gained the most attention in published articles. Twenty-three different technologies were identified and they were used 406 times. Based on our results, we made several implications and suggestions for future studies. This review study can serve as a guide for teaching and research communities who plan on designing language learning and teaching activities supported by technologies.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                07 April 2022
                2022
                : 13
                : 785752
                Affiliations
                [1] 1Department of Engineering Science, National Cheng Kung University , Tainan, Taiwan
                [2] 2Graduate School of Technological and Vocational Education, National Yunlin University of Science and Technology , Yunlin, Taiwan
                Author notes

                Edited by: Chia-Chen Chen, National Chung Hsing University, Taiwan

                Reviewed by: Yu-Sheng Su, National Taiwan Ocean University, Taiwan; Shih-Yeh Chen, National Taitung University, Taiwan

                *Correspondence: Yueh-Min Huang, huang@ 123456mail.ncku.edu.tw

                This article was submitted to Educational Psychology, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2022.785752
                9022657
                0961a988-be28-4136-a29c-d7d06a61966d
                Copyright © 2022 Chien, Wu, Lai and Huang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 September 2021
                : 19 January 2022
                Page count
                Figures: 3, Tables: 2, Equations: 2, References: 36, Pages: 8, Words: 5187
                Categories
                Psychology
                Brief Research Report

                Clinical Psychology & Psychiatry
                line chatbot,artificial intelligence markup language (aiml),competitive strategy,english learning,contextual learning

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