Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-22T14:49:53.429Z Has data issue: false hasContentIssue false
  • English
  • Français

Implementation of an AI chatbot as an English conversation partner in EFL speaking classes

Published online by Cambridge University Press:  13 April 2022

Hyejin Yang Open the ORCID record for Hyejin Yang [Opens in a new window] ,
Heyoung Kim Open the ORCID record for Heyoung Kim [Opens in a new window] ,
Jang Ho Lee Open the ORCID record for Jang Ho Lee [Opens in a new window]  and
Dongkwang Shin Open the ORCID record for Dongkwang Shin [Opens in a new window]
Hyejin Yang
Affiliation:
Chung-Ang University, Republic of Korea ([email protected])
Heyoung Kim
Affiliation:
Chung-Ang University, Republic of Korea ([email protected])
Jang Ho Lee
Affiliation:
Chung-Ang University, Republic of Korea ([email protected])
Dongkwang Shin
Affiliation:
Gwangju National University of Education, Republic of Korea ([email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

With the growth of chatbots, concerns about implementing artificial intelligence (AI) chatbots in educational settings have consistently arisen, especially for the purpose of language learning. This study introduced a task-based voice chatbot called “Ellie”, newly developed by the researchers, and examined the appropriateness of its task design and performance as an English conversation partner and students’ perceptions on using it in EFL class. Korean EFL learners (N = 314) aged 10–15 years performed three speaking tasks with Ellie in their school classroom. The participants took 9.63 turns per session on average using the first 1,000-word band, indicating that the chatbot highly encouraged students to engage in conversation, which rarely occurs in general EFL classes in Korea. The high task success rates (88.3%) showed the design appropriateness of both L2 tasks and operational intents in terms of users’ successful understanding and completeness of the given chatbot tasks. The participants’ responses to the survey not only supported the positive potential of the chatbot in EFL settings but also revealed limitations to be resolved. Future suggestions for advancing and implementing AI chatbots in EFL classrooms are discussed.

Keywords

artificial intelligenceEnglish as a foreign languagevoice chatbotspeaking taskssecond language learning chatbot
Type
Research Article
Information
ReCALL , Volume 34 , Issue 3 , September 2022 , pp. 327 - 343
Check for updates
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of European Association for Computer Assisted Language Learning

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Atwell, E. (1999) The language machine: The impact of speech and language technologies on English language teaching. London: The British Council.Google Scholar
Berns, A., Mota, J. M., Ruiz-Rube, I. & Dodero, J. M. (2018) Exploring the potential of a 360° video application for foreign language learning. In García-Peñalvo, F. J. (ed.), TEEM’18: Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality. New York: Association for Computing Machinery, 776–780. https://doi.org/10.1145/3284179.3284309 CrossRefGoogle Scholar
Chang, C.-W., Lee, J.-H., Chao, P.-Y., Wang, C.-Y. & Chen, G.-D. (2010) Exploring the possibility of using humanoid robots as instructional tools for teaching a second language in primary school. Educational Technology & Society, 13(2): 13–24. http://www.jstor.org/stable/jeductechsoci.13.2.13 Google Scholar
Chapelle, C. (2001) Computer applications in second language acquisition. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Chiu, T.-L., Liou, H.-C. & Yeh, Y. (2007) A study of web-based oral activities enhanced by automatic speech recognition for EFL college learning. Computer Assisted Language Learning, 20(3): 209–234. https://doi.org/10.1080/09588220701489374 CrossRefGoogle Scholar
Choi, S.-K., Kwon, O.-W., Lee, K., Roh, Y.-H., Huang, J.-X. & Kim, Y.-G. (2017) English tutoring system using chatbot and dialog system. In Korea Information Processing Society (ed.), Proceedings of the Korea Information Processing Society Conference. Seoul National University of Science and Technology, 3–4 November, 958–959. https://doi.org/10.3745/PKIPS.Y2017M04A.958 CrossRefGoogle Scholar
Coniam, D. (2008) Evaluating the language resources of chatbots for their potential in English as a second Language. ReCALL, 20(1): 98–116. https://doi.org/10.1017/S0958344008000815 CrossRefGoogle Scholar
Creswell, J. W. & Plano Clark, V. L. (2011) Designing and conducting mixed methods research (2nd ed.). Thousand Oaks: SAGE.Google Scholar
De Jong, N. H., Steinel, M. P., Florijn, A., Schoonen, R. & Hulstijn, J. H. (2012) The effect of task complexity on functional adequacy, fluency and lexical diversity in speaking performances of native and non-native speakers. In Housen, A., Kuiken, F. & Vedder, I. (eds.), Dimensions of L2 performance and proficiency: Complexity, accuracy and fluency in SLA. Amsterdam: John Benjamins, 121–142. https://doi.org/10.1075/lllt.32.06jon CrossRefGoogle Scholar
Ellis, R. (2003) Task-based language learning and teaching. Oxford: Oxford University Press.Google Scholar
Fryer, L. & Carpenter, R. (2006) Bots as language learning tools. Language Learning & Technology, 10(3): 8–14. https://doi.org/10125/44068 Google Scholar
Fryer, L. K., Ainley, M., Thompson, A., Gibson, A. & Sherlock, Z. (2017) Stimulating and sustaining interest in a language course: An experimental comparison of chatbot and human task partners. Computers in Human Behavior, 75: 461–468. https://doi.org/10.1016/j.chb.2017.05.045 CrossRefGoogle Scholar
Gallacher, A., Thompson, A. & Howarth, M. (2018) “My robot is an idiot!” – Students’ perceptions of AI in the L2 classroom. In Taalas, P., Jalkanen, J., Bradley, L. & Thouësny, S. (eds.), Future-proof CALL: Language learning as exploration and encounters: Short papers from EUROCALL 2018. Voillans: Research-publishing.net, 70–76. https://doi.org/10.14705/rpnet.2018.26.815 CrossRefGoogle Scholar
Hu, Y. (2019) Do people want to message chatbots? Developing and comparing the usability of a conversational vs. menu-based chatbot in context of new hire onboarding. Aalto University, unpublished master’s thesis.Google Scholar
Janarthanam, S. (2017) Hands-on chatbots and conversational UI development: Build chatbots and voice user interfaces with Chatfuel, Dialogflow, Microsoft Bot Framework, Twilio, and Alexa Skills. Birmingham: Packt.Google Scholar
Jeon, J.-H., Lee, J.-Y. & Kim, J.-R. (2018) Development of survey to inquire learners’ awareness of language competence based on CEFR basic user level. Asia-Pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 8(3): 199–210.Google Scholar
Jia, J. & Chen, W. (2008) Motivate the learners to practice English through playing with chatbot CSIEC. In Pan, Z., Zhang, X., El Rhalibi, A., Woo, W. & Li, Y. (eds.), Technologies for e-learning and digital entertainment: Edutainment 2008: Vol. 5093: Lecture notes in computer science. Berlin: Springer, 180–191. https://doi.org/10.1007/978-3-540-69736-7_20 Google Scholar
Jia, J. & Ruan, M. (2008) Use chatbot CSIEC to facilitate the individual learning in English instruction: A case study. In Woolf, B. P., Aïmeur, E., Nkambou, R. & Lajoie, S. (eds.), Intelligent tutoring systems: ITS 2008: Vol. 5091: Lecture notes in computer science. Berlin: Springer, 706–708. https://doi.org/10.1007/978-3-540-69132-7_84 Google Scholar
Joo, H. W. (2008) A corpus-based analysis of vocabulary in the BEWL and the CSAT. Seoul: Korea University, unpublished master’s thesis.Google Scholar
Kamphaug, Å., Granmo, O.-C., Goodwin, M. & Zadorozhny, V. I. (2018) Towards open domain chatbots—A GRU architecture for data driven conversations. In Diplaris, S., Satsiou, A., Følstad, A., Vafopoulos, M. & Vilarinho, T. (eds.), Internet science: INSCI 2017: Vol. 10750: Lecture notes in computer science. Cham: Springer, 213–222. https://doi.org/10.1007/978-3-319-77547-0_16 Google Scholar
Kanda, T. & Ishiguro, H. (2005) Communication robots for elementary schools. In AISB’05: Proceedings of the Symposium on Robot Companions: Hard Problems and Open Challenges in Robot-Human Interaction. Brighton: The Society for the Study of Artificial Intelligence and the Simulation of Behaviour, 54–63.Google Scholar
Kim, H., Shin, D. K., Yang, H. & Lee, J. H. (2019) A study of AI chatbot as an assistant tool for school English curriculum. Journal of Learner-Centered Curriculum and Instruction, 19(1): 89–110. https://doi.org/10.22251/jlcci.2019.19.1.89 Google Scholar
Kim, N. (2017) Effects of types of voice-based chat on EFL students’ negotiation of meaning according to proficiency levels. English Teaching, 72(1): 159–181. https://doi.org/10.18095/meeso.2017.18.1.03 CrossRefGoogle Scholar
Kim, N., Cha, Y. & Kim, H. (2019) Future English learning: Chatbots and artificial intelligence. Multimedia-Assisted Language Learning, 22(3): 32–53.Google Scholar
Kötter, M. (2001) Developing distance language learners’ interactive competence—Can synchronous audio do the trick? International Journal of Educational Telecommunications, 7(4): 327–353.Google Scholar
Lee, L. (2001) Online interaction: Negotiation of meaning and strategies used among learners of Spanish. ReCALL, 13(2): 232–244. https://doi.org/10.1017/S0958344001000829a CrossRefGoogle Scholar
Lobo, J. (2017) What is a decision tree and why should my chatbot use it? https://www.inbenta.com/en/blog/decition-tree-chatbot/ Google Scholar
Nakahama, Y., Tyler, A. & Van Lier, L. (2001) Negotiation of meaning in conversational and information gap activities: A comparative discourse analysis. TESOL Quarterly, 35(3): 377–405. https://doi.org/10.2307/3588028 CrossRefGoogle Scholar
Nation, I. S. P. (2006) How large a vocabulary is needed for reading and listening? The Canadian Modern Language Review, 63(1): 59–82. https://doi.org/10.3138/cmlr.63.1.59 CrossRefGoogle Scholar
Nation, I. S. P. (2012) The BNC-COCA word family lists. http://www.victoria.ac.nz/lals/about/staff/publications/BNC_COCA_25000.zip Google Scholar
Robinson, P. (2001) Task complexity, task difficulty, and task production: Exploring interactions in a componential framework. Applied Linguistics, 22(1): 27–57. https://doi.org/10.1093/applin/22.1.27 CrossRefGoogle Scholar
Rosell-Aguilar, F. (2005) Task design for audiographic conferencing: Promoting beginner oral interaction in distance language learning. Computer Assisted Language Learning, 18(5): 417–442. https://doi.org/10.1080/09588220500442772 CrossRefGoogle Scholar
Saldaña, J. (2016) The coding manual for qualitative researchers. Thousand Oaks: SAGE.Google Scholar
Shah, A., Jain, B., Agrawal, B., Jain, S. & Shim, S. (2018) Problem solving chatbot for data structures. In Proceedings of 2018 IEEE 8th Annual Computing and Communication Workshop and Conference. Las Vegas, 8–10 January, 184–189. https://doi.org/10.1109/CCWC.2018.8301734 CrossRefGoogle Scholar
Shum, H., He, X. & Li, D. (2018) From Eliza to XiaoIce: Challenges and opportunities with social chatbots. Frontiers of Information Technology & Electronic Engineering, 19(1): 10–26. https://doi.org/10.1631/FITEE.1700826 CrossRefGoogle Scholar
Skehan, P. (1998) A cognitive approach to language learning. Oxford: Oxford University Press.Google Scholar
Stockwell, G. (2004) Communication breakdown in asynchronous computer-mediated communication (CMC). Australian Language and Literacy Matters, 1(3): 7–10, 31.Google Scholar
Torrey, L., Johnson, K., Sondergard, S., Ponce, P. & Desmond, L. (2016) The turing test in the classroom. In Leake, D. (ed.), Proceedings of the Sixth Symposium on Educational Advances in Artificial Intelligence. Palo Alto: AAAI Press, 4113–4118.Google Scholar
Wang, Y. F. & Petrina, S. (2013) Using learning analytics to understand the design of an intelligent language tutor–chatbot Lucy. International Journal of Advanced Computer Science and Applications, 4(11): 124–131. https://doi.org/10.14569/IJACSA.2013.041117 Google Scholar
Weizenbaum, J. (1966) ELIZA—A computer program for the study of natural language communication between man and machine. Communications of the Association for Computing Machinery, 9(1): 36–45. https://doi.org/10.1145/365153.365168 CrossRefGoogle Scholar
Willis, D. & Willis, J. (2001) Task-based language learning. In Carter, R. & Nunan, D. (eds.), The Cambridge guide to teaching English to speakers of other languages. Cambridge: Cambridge University Press, 173–179. https://doi.org/10.1017/CBO9780511667206.026 CrossRefGoogle Scholar
Willis, J. (1996) The framework for task-based learning. Harlow: Longman.Google Scholar
Supplementary material: File

Yang et al. supplementary material

Yang et al. supplementary material

Download Yang et al. supplementary material(File)
File 19.1 KB