Empowering Students with Innovative AI-Language Learning Tools and Pedagogy to Master Speaking Skills

Document Type : Research Paper

Authors

1 Department of English, Islamic Azad University, Tabriz Branch, Tabriz, Iran

2 Department of English Language, Malayer Branch, Islamic Azad University, Malayer, Iran

Abstract

Artificial Intelligence (AI) is increasingly transforming the landscape of education, particularly within the domain of language learning, as evidenced by a growing body of research published in computer-assisted language learning (CALL) journals. These studies have examined the application of various AI technologies, including natural language processing (NLP), AI-driven educational platforms, automatic speech recognition, and chatbots, in facilitating language acquisition. The present study investigated the perceptions of 386 Iranian high school EFL students, utilizing the Students’ Perceived EFL Teacher Support Scale to evaluate the impact of AI-powered speaking assistance technologies, educational level, and learning setting on perceived teacher support. The findings revealed a tri-factorial structure underlying EFL teacher support, highlighting the compatibility of AI technologies with traditional pedagogical methods. This suggests that the integration of AI-powered tools into classroom instruction can enhance the overall effectiveness of language teaching and learning. To ensure optimal outcomes, educators are encouraged to strategically incorporate AI within pedagogically sound frameworks that maintain human-centered support. The study offers important implications for sustaining and enhancing teacher support in technology-enriched learning environments and underscores the need for further empirical research in this evolving area of applied linguistics and educational technology.

Keywords

References

  1. Aljundi, R., Kelchtermans, K., & Tuytelaars, T. (2019). “Task-free continual learning,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (Long Beach, CA), 11254–11263. https://www.unite.ai/10-best-ai-tools-for-education/

    Brusilovsky, P., & Miller, P. (2001). Course delivery systems for the virtual university. In T. Tschang, & T. Della Senta (Eds.) Access to knowledge: New information technologies and the emergence of the virtual university, (pp. 167-206.). Elsevier Science.

                http://www2.sis.pitt.edu/~peterb/papers/UNU.html

    Brusilovsky, P., & Peylo, C. (2003). Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence in Education, 13(2003), 156–169. https://blakeelias.medium.com/the-case-for-open-ended-ai-f75828cba046

    Baker, T., & Smith, L. (2019). Educ-AI-Tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Nesta.

                https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_WEB. pdf

    Bai, L., & Hu, G. (2017). In the face of fallible awe feedback: How do students respond?. Educational Psychology. 37, 67–81. https://doi.org/10.1080/01443410.2016.1223275

    Campbell, W. M., Singer, E., Torres-Carrasquillo, P. A., & Reynolds, D. A. (2004). “Language recognition with support vector machines,” in ODYSSEY04-The Speaker and Language Recognition Workshop (Toledo).

    Chan, C. K. Y. (2023). Is AI changing the rules of academic misconduct?. An in-depth look at students’ perceptions of ’AI-giarism’.  arXiv Preprint. https://arxiv.org/abs/2306.03358

    Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education 20 (1), 43. https://doi.org/10.48550/arXiv.2305.00290

    Chan, C. K. Y., & Chen, S. (2023). Student partnership in assessment in higher education: A systematic review. Assessment & Evaluation in Higher Education, 48(8), 1402-1414. https://doi.org/10.1080/02602938.2023.2224948

    Chan, C. K. Y., & Tsi, L. H. Y. (2023). The AI Revolution in Education: Will AI replace or assist teachers in higher education? [Preprint]. arxiv:2305.01185.

                 https://talkpal.ai/the-impact-of-ai-on-language-learning-and-teaching/

    Chan, C. K. Y., & Zhou, W. (2023). Deconstructing student perceptions of generative AI (GenAI) through an Expectancy Value Theory (EVT)-based Instrument [Preprint]. arxiv:2305.01186

    Du, Y., & Gao, H. (2022). Determinants affecting teachers’ adoption of ai-based applications in EFL context: An analysis of analytic hierarchy process. Education and Information Technology. 27, 9357–9384. https://doi.org/10.1007/s10639-022-11001-y

    Dong, S., Wang, P., & Abbas, K. (2021). A survey on deep learning and its applications. Computer Science Review. 40, 100379. https://doi.org/10.1016/j.cosrev.2021.100379

    Engel, F., Keary, A., Berwind, K., Bornschlegl, M. X., & Hemmje, M. (2017). “The role of reproducibility in affective computing,” in 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (Kansas City, MO: IEEE), 2008–2014.

    Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.

     https://belitsoft.com/custom-elearning-development/ai-in-education/ai-in-language-learning

    Gao, J. (2021). Exploring the feedback quality of an automated writing evaluation system pigai. International Journal of Emerging Technologies in Learning. 16, 322–330.

            https://doi.org/10.3991/ijet. v16i11.19657

    Holstein, K., McLaren, B. M., and Aleven, V. (2017). “Spackle: investigating learning across virtual and physical spaces using spatial replays,” in Proceedings of the Seventh International Learning Analytics and Knowledge Conference (Vancouver, CA), 358–367. https://doi.org/10.1145/3027385.3027450

    Haristiani, N. (2019). Artificial Intelligence (AI) chatbot as language learning medium: An inquiry. In Journal of Physics: Conference Series (Vol. 1387, No. 1, p. 012020). IOP Publishing. https://www.britishcouncil.fr/blog/shaping-future-artificial-intelligence-english-language-teaching

    Hong, Z.-W., Huang, Y.-M., Hsu, M., & Shen, W.-W. (2016). Authoring robot-assisted instructional materials for improving learning performance and motivation in EFL classrooms. Educational Technology and Society. 19, 337–349.

    Kannan, J., & Munday, P. (2018). New trends in second language learning and teaching through the lens of ICT, networked learning, and artificial intelligence. In Fernández Juncal, C. & Hernández Muñoz, N. (Eds.), Vías de transformación en la enseñanza de lenguas con mediación tecnológica. Círculo de Lingüística Aplicada a la Comunicación, 76, 13-30. https://dx.doi.org/10.5209/CLAC.62495

    Kim, N.-Y., Cha, Y., & Kim, H.-S. (2019). Future English learning: Chatbots and artificial intelligence. Multimedia-Assisted Language Learning. 22, 32–53.

                 http://journal.kamall.or.kr/wp-content/uploads/2019/10/KimChaKim_ 22_3_02. pd

    Lotze, N. (2018). Goodbye to classroom teaching. Artificial intelligence in language learning. Translation: Chris Cave. Copyright: Goethe-Institute e. V., Redaction Magazine Sprache. https://www.goethe.de/en/spr/mag/dsk/ 21290629.html

    Liu, H., & Song, X. (2021). Exploring “Flow” in young Chinese EFL learners’ online English learning activities. System, 96, Article 102425. https://doi.org/10.1016/j. system.2020.102425

    Ma, Y. C., & Lin, H.-C.-K. (2017). “The development of an affective tutoring system for Japanese language learners,” in International Symposium on Emerging Technologies for Education (Cape Town: Springer), 363–371. https://doi.org/10.1007/978-3-319-71084-641

    Mikolov, T., Kombrink, S., Burget, L., Cernock y, J., & Khudanpur, S. (2011). “Extensions of recurrent neural network language model,” in 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Prague: IEEE), 5528–5531.

    O’Brien, R. G., & Kaiser, M. K. (1985). MANOVA method for analyzing repeated measures designs: An extensive primer. Psychological Bulletin, 97(2), 316.

                 https://www.hurix.com/top-6-benefits-of-using-ai-in-language-learning-apps/

    Plonsky, L., & Gonulal, T. (2015). Methodological synthesis in quantitative L2 research: A review of reviews and a case study of exploratory factor analysis. Language Learning, 65(1), 9–36. https://doi.org/10.1111/lang.12111

    Russell, S. J. (2010). Artificial intelligence a modern approach. Hoboken: Prentice Hall (Pearson Education, Inc.).

                https://elearningindustry.com/how-ai-driven-platforms-are-empowering-language-learning

    Rau, P.-L. P., Zheng, J., Guo, Z., & Li, J. (2018). Speed reading on virtual reality and augmented reality. Computer and Education. 125, 240–245.

                https://doi.org/ 10.1016/j.compedu.2018.06.016

    Sumakul, D. T. Y., Hamied, F. A., & Sukyadi, D. (2022). Artificial intelligence in EFL classrooms: friend or foe?. LEARN Journal: Language Education and Acquisition Research Network. 15, 232–256. https://so04.tci-thaijo.org/index.php/LEARN/article/view/256723/174228

    Shvetsova, N., Chen, B., Rouditchenko, A., Thomas, S., Kingsbury, B., Feris, R. S., et al. (2022).         “Everything at once-multi-modal fusion transformer for video retrieval,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (New Orleans), 20020–20029.

    Schoneveld, L., Othmani, A., & Abdelkawy, H. (2021). Leveraging recent advances in deep learning for audio-visual emotion recognition. Pattern Recognition Letters. 146, 1–7. https://doi.org/10.1016/j.patrec.2021.03.007

    Schulze, M. (2008). AI in CALL—Artificially Inflated or Almost Imminent?. CALICO Journal, 25(3), 510-527.

    Tafazoli, D. (2021). CALL teachers’ professional development amid the COVID-19 outbreak: A qualitative study. CALL-EJ, 22(2), 4-13. http://callej.org/journal/22- 2/Tafazoli2021.pdf

    1. H., Alharbi (2022). The affordances of augmented reality technology in the English for specific purposes classroom: It’s impact on vocabulary learning and students’ motivation in a Saudi higher education institution. Journal of Positive School Psychology, 6(3), 6588–6602.

               https://elearningindustry.com/how-ai-driven-platforms-are-empowering-language-learning

    Wu, C.-H., Huang, Y. M., & Hwang, J.-P. (2016a). Review of affective computing in education/learning: Trends and challenges. British Journal of Educational Technology. 47, 1304–1323. https://doi.org/10.1111/bjet.12324.

    Wang, Y. F., & Petrina, S. (2013). Using learning analytics to understand the design of an intelligent language tutor-chatbot lucy. Editorial Preface 4, 124–131.

                https://doi.org/ 10.14569/IJACSA.2013.041117

    Yau, C., & Chan, K. (2023, February 17). University of Hong Kong temporarily bans students from using ChatGPT, other AI-based tools in coursework. South China Morning Post. https://www.scmp.com/news/hong-kong/education/article/32106

    Zitouni, K. S. (2022). New trends in EFL online learning and teaching through the lens of artificial intelligence. Almuqadimah of Human and Social Studies Journal. 7, 1065–1080.    https://www.asjp.cerist.dz/en/downArticle/662/7/ 1/193260

Iranian Journal of Applied Language Studies
Volume 17, Issue 1
March 2025
Pages 197-220

Files

Share

How to cite

Statistics