A systematic review of conversational AI in language education: focusing on the collaboration with human teachers
Abstract
Despite the increasing use of conversational artificial intelligence (AI) in language learning, few studies explored how to develop collaborative partnership between AIs and humans. This systematic review examines empirical evidence of human-computer collaboration from 24 studies conducted in an AI-integrated language learning environment and published between 2015 and 2021. The roles of conversational AIs and teachers in each language learning phase with challenges of and suggestions for conversational AI-integrated language learning were identified. Although limited evidence for collaboration between conversational AIs and human teachers was found, future language education should integrate conversational AIs to promote intelligence amplification and decrease human teachers’ workload through classroom orchestration. The study concludes with guidelines and recommendations for teachers and AI researchers.
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“The field of AI ethics focuses on fairness, accountability, and societal impact, addresses the surge in ethical challenges posed by AI's increasing complexity and potential misalignment with human values, and requires ethical governance frameworks, multidisciplinary collaborations, and technological solutions [214], [235], [15], [236].”
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Cites
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.006 · Cited by 10,578 · see citing works
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · cited 1× · see citing works
“Since Turing (1950) explored the mathematical possibility of AI by suggesting the Turing Machines, the development of AI and research on learning and educational applications have experienced rises and falls.”
BackgroundZawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242 · cited 4× · see citing works
“…the advancement of AI technology, such as machine learning, neural network, natural language processing (NLP) with automatic speech recognition (ASR), and advanced image processing (Zawacki-Richter et al., 2019) and increased access to commercially available AI devices and mobile applications.”
BackgroundInfluentialArtificial Intelligence in Education: A Review
Chen, L., Chen, P., & Lin, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2988510 · Cited by 4,133 · cited 2× · see citing works
“This was supported by a significant increase in the number of papers on this topic published since 2015 (Chen et al., 2020).”
BackgroundChatbots: History, technology, and applications
Adamopoulou, E., & Moussiades, L. (2020) · Machine Learning with Applications · doi:10.1016/j.mlwa.2020.100006 · Cited by 1,090 · see citing works
Chatbots for learning: A review of educational chatbots for the Facebook Messenger
Smutny, P., & Schreiberova, P. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103862 · Cited by 770 · see citing works
Kim, J., Lee, H., & Cho, Y. H. (2022) · Education and Information Technologies · doi:10.1007/s10639-021-10831-6 · Cited by 669 · cited 10× · see citing works
“Compared to many promises that AI-enabled technologies could bring to language learning settings, few guidelines are available for teachers on how they utilize AI technologies for enhancing student learning (Kim et al., 2022).”
BackgroundResultInfluentialStupid tutoring systems, intelligent humans
Baker, R. S. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0105-0 · Cited by 425 · see citing works
The Motion of Emotion: Idiodynamic Case Studies of Learners' Foreign Language Anxiety
Gregersen, T., Macintyre, P. D., & Meza, M. D. (2014) · The Modern Language Journal · doi:10.1111/modl.12084 · Cited by 335 · see citing works
The impact of Google Assistant on adolescent EFL learners’ willingness to communicate
Tai, T.-Y., & Chen, H. H.-J. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2020.1841801 · Cited by 302 · see citing works
Chatbot-assisted dynamic assessment (CA-DA) for L2 vocabulary learning and diagnosis
Jeon, J. (2023) · Computer Assisted Language Learning · doi:10.1080/09588221.2021.1987272 · Cited by 202 · see citing works
A Conceptual Framework for Human–AI Hybrid Adaptivity in Education
Holstein, K., Aleven, V., & Rummel, N. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-52237-7_20 · Cited by 168 · see citing works
Classroom Orchestration: Synthesis
Roschelle, J., Dimitriadis, Y., & Hoppe, U. (2013) · Computers & Education · doi:10.1016/j.compedu.2013.04.010 · Cited by 150 · see citing works
AI and the Future of Learning: Expert Panel Report
Roschelle, J., Lester, J., & Fusco, J. (2020) · doi:10.51388/20.500.12265/106 · Cited by 76 · see citing works
Bao, M. (2019) · Arab World English Journal · doi:10.24093/awej/call5.3 · Cited by 70 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · see citing works
“…review on conversational AI in language education, the authors found that there are five main applications of conversational AI during teaching [22], the most common one being the use of large language models as a conversational partner in a written or oral form, e.g., in the context of a…”
BackgroundWalter, Y. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00448-3 · Cited by 1,113 · see citing works
“However, the many precious possibilities in positively transforming the education systems through AI also comes with some downsides. can be summarized in several points (Adiguzel et al., 2023; Ji et al., 2023; Ng et al., 2023a, 2023b, 2023c; Ng et al., 2023a, 2023b, 2023c): 1.”
Jeon, J., & Lee, S. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11834-1 · Cited by 696 · see citing works
Promises and challenges of generative artificial intelligence for human learning
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02004-5 · Cited by 499 · see citing works
Leading teachers' perspective on teacher-AI collaboration in education
Kim, J. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12109-5 · Cited by 376 · see citing works
Cain, W. (2024) · TechTrends · doi:10.1007/s11528-023-00896-0 · Cited by 232 · see citing works
Lee, S. J., & Kwon, K. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100211 · Cited by 169 · see citing works
Ibrahim, H., Liu, F., Asim, R., Battu, B., Benabderrahmane, S., Alhafni, B., Adnan, W., Alhanai, T., AlShebli, B., Baghdadi, R., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-38964-3 · Cited by 154 · see citing works
Derakhshan, A. (2025) · Learning and Motivation · doi:10.1016/j.lmot.2025.102114 · Cited by 151 · see citing works
Cheah, Y. H., Lu, J., & Kim, J. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100363 · Cited by 134 · see citing works
Lan, Y. (2024) · Teaching and Teacher Education · doi:10.1016/j.tate.2024.104736 · Cited by 124 · see citing works
Cultivating writing skills: The role of ChatGPT as a learning assistant—A case study
Punar Özçelik, N., & Yangın Ekşi, G. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00296-8 · Cited by 115 · see citing works
Fan, G., Liu, D., Zhang, R., & Pan, L. (2025) · International Journal of STEM Education · doi:10.1186/s40594-025-00537-3 · Cited by 109 · see citing works
“Specifically, there is limited understanding of how AI-assisted pair programming influences student motivation, programming anxiety, and perceptions of collaboration and social interaction compared to traditional human–human pair programming (Ji et al., 2023).”
McIntosh, T. R., Susnjak, T., Liu, T., Watters, P., Xu, D., Liu, D., & Halgamuge, M. N. (2025) · Technologies · doi:10.3390/technologies13020051 · Cited by 102 · see citing works
“• Conversational AI : This subdomain is dedicated to developing AI systems capable of smooth, natural, and context-aware human-computer interactions, by focusing on dialogue modeling, question answering, user intent recognition, and multi-turn context tracking [204], [205], [206], [207].”
BackgroundZhang, C., Liu, X., Ziska, K., Jeon, S., Yu, C.-L., & Xu, Y. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642647 · Cited by 96 · see citing works
Chen, C., & Gong, Y. (. (2025) · Education Sciences · doi:10.3390/educsci15020141 · Cited by 90 · see citing works
Artificial Intelligence Integration: Pedagogical Strategies and Policies at Leading Universities
Alqahtani, N., & Wafula, Z. (2025) · Innovative Higher Education · doi:10.1007/s10755-024-09749-x · Cited by 84 · see citing works
Bewersdorff, A., Seßler, K., Baur, A., Kasneci, E., & Nerdel, C. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100177 · Cited by 76 · see citing works
Does ChatGPT Argue Like Students? Bundles in Argumentative Essays
Jiang, F. (., & Hyland, K. (2025) · Applied Linguistics · doi:10.1093/applin/amae052 · Cited by 76 · see citing works
Wang, F., Cheung, A. C. K., Neitzel, A. J., & Chai, C. S. (2025) · Review of Educational Research · doi:10.3102/00346543241255621 · Cited by 64 · see citing works
Creative Use of OpenAI in Education: Case Studies from Game Development
French, F., Levi, D., Maczo, C., Simonaityte, A., Triantafyllidis, S., & Varda, G. (2023) · Multimodal Technologies and Interaction · doi:10.3390/mti7080081 · Cited by 64 · see citing works
Zheng, S. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100271 · Cited by 58 · see citing works
My teammate is AI: understanding students’ perceptions of student-AI collaboration in drawing tasks
Kim, J., & Cho, Y. H. (2025) · Asia Pacific Journal of Education · doi:10.1080/02188791.2023.2286206 · Cited by 50 · see citing works
Almanea, M. (2026) · Computer Assisted Language Learning · doi:10.1080/09588221.2024.2410158 · Cited by 40 · see citing works
Cheng, A. Y., Guo, M., Ran, M., Ranasaria, A., Sharma, A., Xie, A., Le, K. N., Vinaithirthan, B., Luan, S. (., Wright, D. T. H., et al. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642041 · Cited by 37 · see citing works
Tan, M., & Subramonyam, H. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642592 · Cited by 40 · see citing works
Li, Y., Wu, Y., & Chiu, T. K. F. (2026) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2493942 · Cited by 19 · see citing works
“There were some overlaps with teacher presence (roles) in a non-GenAI context, such as knowledge presenter, course organizer, and feedback provider (Ji et al., 2023), confirming that teacher presence (roles) in traditional learning could be supported and enhanced in a GenAI context and indicating…”
Integrating AI technology into corpus-based language learning through <i>ChatAI</i>
Anthony, L. (2025) · Computer Assisted Language Learning · doi:10.1080/09588221.2025.2589747 · Cited by 7 · see citing works
Being Brave in a New World: Leveraging ChatGPT in Signal Processing Classes
Banavar, M. K., Shri, L., Sparks, N., & Cohen, A. (2023) · 2023 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie58773.2023.10342917 · Cited by 4 · see citing works
- Authors
- Ji, H., Han, I., & Ko, Y.
- Affiliations
- Temple University (US)
- Korea University (KR)
- Hanyang Cyber University (KR)
- Corresponding author
- Han, Insook
- Venue
- Journal of Research on Technology in Education
- Publisher
- Informa UK Limited
- Published
- 2022-11-30
- Volume
- 55
- Issue
- 1
- Pages
- 48-63
- ISSN
- 1539-1523 (ISSN-L)
- 1945-0818
- OpenAlex
- W4310436400
- Semantic Scholar
- 1c78adbec0fd2975d2d4b5e70b64f1e02ad4533a
- Cited by
- 394
- References
- 15
- Citations by year
- 2026: 100 · 2025: 157 · 2024: 102 · 2023: 35
- FWCI
- 9.27
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Research on Technology in Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Keywords
- conversational AI, language teaching, human-computer collaboration, teacher workload, classroom orchestration, intelligence amplification
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