A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents
This review analyzed the trends in conversational AI tools in ELT from January 2013 to November 2023. The study examined 32 papers, focusing on publication trends, tool types, research methods, learning outcomes, and factors influencing their use. Findings revealed a gradual increase in publications...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Computers and Education: Artificial Intelligence |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666920X24000948 |
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| author | Wan Yee Winsy Lai Ju Seong Lee |
| author_facet | Wan Yee Winsy Lai Ju Seong Lee |
| author_sort | Wan Yee Winsy Lai |
| collection | DOAJ |
| description | This review analyzed the trends in conversational AI tools in ELT from January 2013 to November 2023. The study examined 32 papers, focusing on publication trends, tool types, research methods, learning outcomes, and factors influencing their use. Findings revealed a gradual increase in publications, with 4 (12%) from 2013 to 2021, 13 (41%) in 2022, and 15 (47%) in 2023. All studies (100%) were conducted in Asian EFL contexts. Among the AI chatbots, Google Assistant (25%) was the most widely used. Quasi-experimental (45%) and cross-section (41%) research designs were commonly employed. Mixed-method (50%) approaches were prevalent for data collection and analysis. Conversational AI yielded positive outcomes in affective (43%) and cognitive skills (41%). The main factors influencing user perceptions or behaviors were individual (47%) and microsystem layers (31%). Future studies should (a) include diverse contexts beyond Asia, (b) consider the use of up-to-date tools (e.g., ChatGPT), (c) employ rigorous experimental designs, (d) explore behavioral learning outcomes, and (e) investigate broader environmental factors. The systematic review enhances current knowledge of recent research trends, identifies environmental factors influencing conversational AI tools concentrating in ELT, and provides insights for future research and practice in this rapidly evolving field. |
| format | Article |
| id | doaj-art-ea3c88c69c7d43bbb83f3ca06d799892 |
| institution | Kabale University |
| issn | 2666-920X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers and Education: Artificial Intelligence |
| spelling | doaj-art-ea3c88c69c7d43bbb83f3ca06d7998922024-12-19T11:01:30ZengElsevierComputers and Education: Artificial Intelligence2666-920X2024-12-017100291A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedentsWan Yee Winsy Lai0Ju Seong Lee1The Education University of Hong Kong, Hong KongCorresponding author. Department of English Language Education, 10 Lo Ping Road, Tai Po, New Territories, Hong Kong.; The Education University of Hong Kong, Hong KongThis review analyzed the trends in conversational AI tools in ELT from January 2013 to November 2023. The study examined 32 papers, focusing on publication trends, tool types, research methods, learning outcomes, and factors influencing their use. Findings revealed a gradual increase in publications, with 4 (12%) from 2013 to 2021, 13 (41%) in 2022, and 15 (47%) in 2023. All studies (100%) were conducted in Asian EFL contexts. Among the AI chatbots, Google Assistant (25%) was the most widely used. Quasi-experimental (45%) and cross-section (41%) research designs were commonly employed. Mixed-method (50%) approaches were prevalent for data collection and analysis. Conversational AI yielded positive outcomes in affective (43%) and cognitive skills (41%). The main factors influencing user perceptions or behaviors were individual (47%) and microsystem layers (31%). Future studies should (a) include diverse contexts beyond Asia, (b) consider the use of up-to-date tools (e.g., ChatGPT), (c) employ rigorous experimental designs, (d) explore behavioral learning outcomes, and (e) investigate broader environmental factors. The systematic review enhances current knowledge of recent research trends, identifies environmental factors influencing conversational AI tools concentrating in ELT, and provides insights for future research and practice in this rapidly evolving field.http://www.sciencedirect.com/science/article/pii/S2666920X24000948Conversational AIAI chatbotAI-assisted language learningELTEnglish as a foreign languageEcological system theory |
| spellingShingle | Wan Yee Winsy Lai Ju Seong Lee A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents Computers and Education: Artificial Intelligence Conversational AI AI chatbot AI-assisted language learning ELT English as a foreign language Ecological system theory |
| title | A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents |
| title_full | A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents |
| title_fullStr | A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents |
| title_full_unstemmed | A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents |
| title_short | A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents |
| title_sort | systematic review of conversational ai tools in elt publication trends tools research methods learning outcomes and antecedents |
| topic | Conversational AI AI chatbot AI-assisted language learning ELT English as a foreign language Ecological system theory |
| url | http://www.sciencedirect.com/science/article/pii/S2666920X24000948 |
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