AI or not to AI in Resource-Constrained Contexts? Exploring the Impact of AI-Mediated Feedback on the EFL Speaking Proficiency of Bangladeshi Undergraduate Learners
Keywords:
AI-generated feedback; EFL speaking; speaking proficiency; learner perception; BangladeshAbstract
Developing English-speaking proficiency remains challenging in Bangladesh because teacher-centred instruction, large class sizes, and limited opportunities for individualised feedback constrain the speaking practice of learners. Although AI-mediated feedback has shown promise for supporting language learning, its effectiveness in resource-constrained English as a Foreign Language (EFL) context remains underexplored. This study investigated the impact of SmallTalk2Me, an AI-mediated speaking platform, on the speaking proficiency, fluency, and perceptions of Bangladeshi tertiary-level EFL learners. Using a one-group pretest–posttest pre-experimental design, 28 undergraduate students completed IELTS speaking tests before and after a three-week intervention, while speaking fluency was measured using words per minute (WPM) and the perceptions of learners were examined through a post-intervention survey. The findings showed significant improvements in IELTS speaking scores (5.75–6.38, p <.001, d = 0.93) and speaking fluency (84.50–93.10 WPM, p <.001, d = 1.15), alongside positive perceptions of AI-mediated feedback. However, variation in learning outcomes, concerns regarding feedback reliability, and the lack of human interaction suggest that AI-mediated feedback is most effective when integrated with contextualised learning opportunities and teacher support. The study contributes empirical evidence from a resource-constrained EFL context and highlights the potential of AI as a complementary tool for speaking development rather than a replacement for teachers.
https://doi.org/10.26803/ijlter.25.9.16
References
Akter, M., Akter, M., & Ali, Md. M. (2026). Impact of digital learning on primary education in Bangladesh. Global Mainstream Journal of Arts Literature History & Education, 2(1). https://doi.org/10.62304/alhe.v4i01.245
Alhalangy, A., & AbdAlgane, M. (2023). Exploring the impact of AI on The EFL context: A case study of Saudi universities. Journal of Intercultural Communication, 23(2), 41–49. https://doi.org/10.36923/jicc.v23i2.125
Al-husban, N. (2025). The impact of AI- assisted language learning tools on augmenting university EFL students’ speaking skills in Jordan. Journal of Applied Learning & Teaching, 8(1), 116–127. https://doi.org/10.37074/jalt.2025.8.1.13
Al-Shallakh, M. A. (2024). Embedding artificial intelligent applications in higher educational institutions to improve students’ pronunciation performance. Theory and Practice in Language Studies, 14(6), 1897–1906. https://doi.org/10.17507/tpls.1406.31
Bashori, M., Van Hout, R., Strik, H., & Cucchiarini, C. (2020). Web-based language learning and speaking anxiety. Computer Assisted Language Learning, 35(5-6), 1058–1089. https://doi.org/10.1080/09588221.2020.1770293
Bashori, M., Van Hout, R., Strik, H., & Cucchiarini, C. (2021). Effects of ASR-based websites on EFL learners’ vocabulary, speaking anxiety, and language enjoyment. Data Archiving and Networked Services (DANS), 99, 102496–102496. https://doi.org/10.1016/j.system.2021.102496
Betal, A. K. (2023). Enhancing second language acquisition through artificial intelligence (AI): Current insights and future directions. Journal for Research Scholars and Professionals of English Language Teaching, 7(39). https://doi.org/10.54850/jrspelt.7.39.003
Bhar, S. K. (2026). Artificial intelligence in EFL speaking instruction: A systematic review of pedagogical design, affective conditions and instructional input. Encyclopedia, 6(4), 74–74. https://doi.org/10.3390/encyclopedia6040074
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Çelik, ?., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
Cogo, A., Patsko, L., & Szoke, J. (2024). Generative artificial intelligence and ELT. ELT Journal, 78(4), 373–377. https://doi.org/10.1093/elt/ccae051
Creswell, J. W., & Creswell, J.D. (2017). Research design Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage.
Cruz, R., de Lourdes M., Villanueva, M. S., & Pluvinet, D. (2023). Mediation in autonomous practices among novice language teachers while discussing conflicts in their teaching practice. Colombian Applied Linguistics Journal, 25(2), 44–57. https://doi.org/10.14483/22487085.18736
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Ding, D., & Yusof, A. M. (2025). Investigating the role of AI-powered conversation bots in enhancing L2 speaking skills and reducing speaking anxiety: A mixed methods study. Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-05550-z
Estaji, M., Mirfendereski, Y., & Marian, K. S. (2026). Artificial intelligence as a catalyst for transformation: EFL learners’ perceptions of AI-powered language tools in delivering effective oral and written corrective feedback. Research and Practice in Technology Enhanced Learning, 22, 14–14. https://doi.org/10.58459/rptel.2027.22014
Etikan, ?., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–1. https://doi.org/10.11648/j.ajtas.20160501.11
Evenddy, S. S. (2024). Investigating AI’s automated feedback in English language learning. FLIP Foreign Language Instruction Probe, 3(1), 76–87. https://doi.org/10.54213/flip.v3i1.401
Farooqi, S.-H. (2025). Efficacy of AI-generated feedback by SmallTalk2Me for improving speaking skill of Saudi EFL learners. Forum for Linguistic Studies, 7(3), 714–772. https://doi.org/10.30564/fls.v7i3.8294
Field, A. (2018). Discovering statistics using IBM SPSS statistics. Sage.
Gyawali, Y. P., & Mehandroo, M. (2022). Artificial intelligence in English language teaching: Navigating the future with emerging perspectives. Journal of Language and Linguistics in Society, 26, 21–27. https://doi.org/10.55529/jlls.26.21.27
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
Islam, M. S., & Stapa, M. (2021). Students’ low proficiency in spoken English in private universities in Bangladesh: Reasons and remedies. Language Testing in Asia, 11(1), 22. https://doi.org/10.1186/s40468-021-00139-0
Islam, Md. S., & Roy, S. (2024). Challenges in developing learners’ English-speaking skills at the tertiary level in the EFL context: Teachers’ and learners’ perceptions. In Research Square. https://doi.org/10.21203/rs.3.rs-4491944/v1
Islam, S., & -E-Jannat, B. (2025). English language learning challenges in Bangladeshi secondary schools. International Journal of Advanced Multidisciplinary Research and Studies, 5(4), 450–454. https://doi.org/10.62225/2583049x.2025.5.4.4613
Julious, S. A. (2005). Sample size of 12 per group rule of thumb for a pilot study. Pharmaceutical Statistics, 4(4), 287–291. https://doi.org/10.1002/pst.185
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274–102274. https://doi.org/10.1016/j.lindif.2023.102274
Kim, J., Lee, H.-K., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069–6104. https://doi.org/10.1007/s10639-021-10831-6
Krashen, S. (1982). Principles and practice in second language acquisition. 168–168. https://doi.org/10.2307/328293
Kristiawan, D., Bashar, K., & Pradana, D. A. (2024). Artificial Intelligence in English language learning: A systematic review of AI tools, applications, and pedagogical outcomes. The Art of Teaching English as a Foreign Language, 5(2), 207–218. https://doi.org/10.36663/tatefl.v5i2.912
Lantolf, J. P. (2006). Sociocultural theory and L2: State of the art. Studies in Second Language Acquisition, 28(1), 67–109. https://doi.org/10.1017/s0272263106060037
Lestari, N. (2019). Improving the speaking skill by vlog (video blog) as learning media: The EFL students’ perspective. International Journal of Academic Research in Business and Social Sciences, 9(1). https://doi.org/10.6007/ijarbss/v9-i1/5490
Liu, G., Darvin, R., & Ma, C. (2024). Exploring AI-mediated informal digital learning of English (AI-IDLE): A mixed-method investigation of Chinese EFL learners’ AI adoption and experiences. Computer Assisted Language Learning, 38(7), 1632–1660. https://doi.org/10.1080/09588221.2024.2310288
Loewen, S., Isbell, D. R., & Sporn, Z. (2020). The effectiveness of app?based language instruction for developing receptive linguistic knowledge and oral communicative ability. Foreign Language Annals, 53(2), 209–233. https://doi.org/10.1111/flan.12454
Manggiasih, L. A., Loreana, Y. R., Azizah, A., & Nurjati, N. (2023). Strengths and limitations of SmallTalk2Me App in English language proficiency evaluation. Tell Teaching of English Language and Literature Journal, 11(2). https://doi.org/10.30651/tell.v11i2.19560
Moussalli, S., & Cardoso, W. (2019). Intelligent personal assistants: Can they understand and be understood by accented L2 learners? Computer Assisted Language Learning, 33(8), 865–890. https://doi.org/10.1080/09588221.2019.1595664
Mridha, Md. M., & Muniruzzaman, S. Md. (2020). Developing English speaking skills: Barriers faced by the Bangladeshi EFL learners. Englisia Journal of Language Education and Humanities, 7(2), 118–118. https://doi.org/10.22373/ej.v7i2.6257
Murtiningsih, S. R., Darmanto, F. M. I., & Hidayatulloh, S. M. M. (2023). Students’ psychological state degree and their speaking ability: To what extent is the link? Voices of English Language Education Society, 7(2), 210–220. https://doi.org/10.29408/veles.v7i2.14815
Nazaretsky, T., Mejia?Domenzain, P., Swamy, V., Frej, J., & Käser, T. (2025). The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions. Computers and Education Artificial Intelligence, 8, 100368–100368. https://doi.org/10.1016/j.caeai.2025.100368
Nguyen, H. A. (2024). Harnessing AI-based tools for enhancing English speaking proficiency: Impacts, challenges, and long-term engagement. International Journal of AI in Language Education, 1(2), 18–29. https://doi.org/10.54855/ijaile.24122
Nh?t, N. Q., V?, L. H., & Trúc, N. T. T. (2025). The impact of AI-supported speaking practice on EFL learners’ confidence in Vietnam. International Journal of Advanced Multidisciplinary Research and Studies, 5(5), 384–393. https://doi.org/10.62225/2583049x.2025.5.5.4924
Okoye, K., Haruna, H., Arrona?Palacios, A., Quintero, H. N., Ortega, L. O. P., Sanchez, A. L., Ortiz, E. A., Escamilla, J., & Hosseini, S. (2022). Impact of digital technologies upon teaching and learning in higher education in Latin America: An outlook on the reach, barriers, and bottlenecks. Education and Information Technologies, 28(2), 2291–2360. https://doi.org/10.1007/s10639-022-11214-1
Otero, L. C., Catalá, A., Fernández-Morante, C., Taboada, M., López, B. C., & Barro, S. (2023). AI literacy in K-12: a systematic literature review. International Journal of STEM Education, 10(1). https://doi.org/10.1186/s40594-023-00418-7
Pallant, J. (2020). SPSS Survival Manual. Routledge. https://doi.org/10.4324/9781003117452
Permatasari, I. R., Wulandari, R. M., Palupi, D., Faizin, H. A., & Adji, B. P. W. (2025). Examining Students’ Perceptions of a Smalltalk2Me powered conversation assistant in the speaking class. Educational Dynamics International Journal of Education and Social Sciences, 2(4), 16–23. https://doi.org/10.70062/educationaldynamics.v2i4.243
Petri?, B., & Czárl, B. (2003). Validating a writing strategy questionnaire. System, 31(2), 187–215. https://doi.org/10.1016/s0346-251x(03)00020-4
Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1255594
Raoofi, S., Miri, A., Gharibi, J., & Malaki, B. (2017). Assessing and validating a writing strategy scale for undergraduate students. Journal of Language Teaching and Research, 8(3), 624–624. https://doi.org/10.17507/jltr.0803.23
Salameh, W. A. K. (2024). The dual role of AI in personalized learning: Enhancements and hindrances for diverse learners. International Journal of Science and Research Archive, 13(2), 62–67. https://doi.org/10.30574/ijsra.2024.13.2.2057
Seraj, P. M. I., Habil, H., & Hasan, Md. K. (2020). Investigating EFL learners’ readiness of using smartphone and problems for learning oral English communication skills at tertiary level in an EFL Context. International Journal of Interactive Mobile Technologies, 14(14), 148–148. https://doi.org/10.3991/ijim.v14i14.14759
Seraj, P. M. I., Habil, H., & Hasan, Md. K. (2021). Investigating the problems of teaching oral English communication skills in an EFL context at the tertiary level. International Journal of Instruction, 14(2), 501–516. https://doi.org/10.29333/iji.2021.14228a
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Quasi-experiments: interrupted time-series designs. Experimental and Quasi-Experimental Designs for Generalized Causal Inference, 1, 171–205. Houghton-Mifflin.
Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52, 591–611. https://doi.org/10.1093/biomet/52.3-4.591
Swain, M. (1985). Communicative competence: Some roles of comprehensible input and comprehensible output in its development. Input in Second Language Acquisition, 15, 165–179.
Viberg, O., Wasson, B., & Kukulska?Hulme, A. (2020). Mobile-assisted language learning through learning analytics for self-regulated learning (MALLAS): A conceptual framework. Australasian Journal of Educational Technology, 36(6), 34–52. https://doi.org/10.14742/ajet.6494
Wang, Z., & Han, F. (2022). The effects of teacher feedback and automated feedback on cognitive and psychological aspects of foreign language writing: Mixed-methods research. Frontiers in Psychology, 13, 909802–909802. https://doi.org/10.3389/fpsyg.2022.909802
Wicaksono, C., Afidah, N., Ma’arif, I. B., & Agustina, U. W. (2025). The effect of SmallTalk2Me in English instruction at MTs Pesantren Al-Amin Sooko Mojokerto. Application: Applied Science in Learning Research, 4(3), 101–107. https://doi.org/10.32764/application.v4i3.5578
Wu, T., Hapsari, I. P., & Huang, Y. (2025). Effects of incorporating AI chatbots into think–pair–share activities on EFL speaking anxiety, language enjoyment, and speaking performance. Computer Assisted Language Learning, 39, 1408–1446. https://doi.org/10.1080/09588221.2025.2478271
Yan, H., & Singh, M. K. S. (2026). The impact of AI-mediated instruction on speaking proficiency, enjoyment, anxiety, and emotional engagement: A mixed-methods approach. Humanities and Social Sciences Communications, 13(1). https://doi.org/10.1057/s41599-026-06705-2
Zhou, Y., He, Y., Wang, X., Song, L., Liu, X., & Liu, W. (2025). AI-based real-time feedback system for improving English oral proficiency. 349–353. https://doi.org/10.1109/icdel65868.2025.11193512
Zou, B., Lyu, Q., Han, Y., Li, Z., & Zhang, W. (2023). Exploring students’ acceptance of an artificial intelligence speech evaluation program for EFL speaking practice: An application of the integrated model of technology acceptance. Computer Assisted Language Learning, 38, 1366–1391. https://doi.org/10.1080/09588221.2023.2278608
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 MD Nahid Hasan, Khadija Akter Onee, Shakila Akter, Nujhat Aslam Nieon, Pragga Paromita Bose, Zannatul Ferdushie, Md. Ismaile Hossain

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published by IJLTER are licensed under a Creative Commons Attribution Non-Commercial No-Derivatives 4.0 International License (CCBY-NC-ND4.0).