THE EFFICACY OF AI-POWERED TUTORS VS. HUMAN TUTORS IN DEVELOPING EFL ORAL FLUENCY: A COMPARATIVE EXPERIMENTAL STUDY
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The rapid advancement of artificial intelligence has led to the increasing use of AI-powered tutors in English as a Foreign Language (EFL) instruction, particularly for speaking skills development. Despite growing adoption, empirical evidence comparing the effectiveness of AI-powered tutors and human tutors in developing oral fluency remains limited and inconclusive. This study aims to comparatively examine the efficacy of AI-powered tutors and human tutors in enhancing EFL learners’ oral fluency across multiple fluency dimensions. This research employed a comparative experimental design involving two groups of EFL learners who received equivalent instructional content over a fixed intervention period, differentiated only by tutoring modality. One group engaged in AI-powered tutoring, while the other received instruction from human tutors. Pretest and posttest measures of oral fluency were administered, focusing on temporal, interactional, and discourse-related indicators. Quantitative data were analyzed using inferential statistical techniques to determine within-group and between-group differences. The findings reveal that both AI-powered tutors and human tutors significantly improved learners’ oral fluency. AI-powered tutors were particularly effective in enhancing temporal fluency, including speech rate and reduced hesitation. Human tutors demonstrated superior effectiveness in developing interactional competence, discourse coherence, and pragmatic appropriateness. The study concludes that AI-powered tutors serve as effective supplementary tools for oral fluency practice, while human tutors remain essential for higher-level communicative development. A hybrid instructional approach is recommended to maximize EFL speaking outcomes.
Adorni, G., Artico, I., Piatti, A., Lutz, E., Gambardella, L. M., Negrini, L., Mondada, F., & Assaf, D. (2024). Development of algorithmic thinking skills in K-12 education: A comparative study of unplugged and digital assessment instruments. Computers in Human Behavior Reports, 15, 100466. https://doi.org/https://doi.org/10.1016/j.chbr.2024.100466
Adorni, G., & Piatti, A. (2025). Designing the virtual CAT: A digital tool for algorithmic thinking assessment in compulsory education. International Journal of Child-Computer Interaction, 45, 100760. https://doi.org/https://doi.org/10.1016/j.ijcci.2025.100760
Al-Bogami, R. M., & Alahmadi, N. A. (2025). Effects of an AI-based reading progress tool on third-grade EFL learners’ oral reading fluency. Computers and Education Open, 9, 100283. https://doi.org/https://doi.org/10.1016/j.caeo.2025.100283
Aladini, A., Ismail, S. M., Ahmad Saleem Khasawneh, M., & Shakibaei, G. (2025). Self-directed writing development across computer/AI-based tasks: Unraveling the traces on L2 writing outcomes, growth mindfulness, and grammatical knowledge. Computers in Human Behavior Reports, 17, 100566. https://doi.org/https://doi.org/10.1016/j.chbr.2024.100566
Alsswey, A., El-Qirem, F. A., & Omar, F. (2025). 3D holograms and emotional intelligence: Transforming interactive learning in higher education. Acta Psychologica, 261, 105758. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105758
Avci, H., Lunn, S. J., & Hazari, Z. (2025). Exploring STEM educators’ perspectives on the integration of AI-enabled technologies in teaching and learning. Computers and Education Open, 9, 100304. https://doi.org/https://doi.org/10.1016/j.caeo.2025.100304
Brezovec, E., Zeli?, M., & Zagode, A. M. (2025). Stabilizing truth in educational sciences: a systematic review of generative AI in education. Kybernetes, 55(13), 1–17. https://doi.org/https://doi.org/10.1108/K-09-2025-2339
Brunton, R. J., Rhazzafe, S., Moodley, R., Kuhn, S., Caraffini, F., Wilford, S., Higginbottom, R., Colreavy-Donnelly, S., & Gongora, M. (2025). Using generative artificial intelligence to enhance the performance of disadvantaged students in secondary education. Social Sciences & Humanities Open, 12, 102110. https://doi.org/https://doi.org/10.1016/j.ssaho.2025.102110
Buciuman, C.-F., & Potra, S. (2025). Revolutionizing Education in Industry 4.0: Eye-Tracking and AI for Personalized Learning. Procedia Computer Science, 253, 1658–1667. https://doi.org/https://doi.org/10.1016/j.procs.2025.01.228
Chen, S., & Cheung, A. C. K. (2025). Effect of generative artificial intelligence on university students learning outcomes: A systematic review and meta-analysis. Educational Research Review, 49, 100737. https://doi.org/https://doi.org/10.1016/j.edurev.2025.100737
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2023.102642
Ebadi, S., Velayati, S., Ramezanzadeh, A., & Rawdhan Salman, A. (2025). Exploring the impact of AI-powered speaking tasks on EFL learners’ speaking performance and anxiety: An activity theory study. Acta Psychologica, 259, 105391. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105391
Görer, B., & Aydemir, F. B. (2024). Exploring the REIT architecture for requirements elicitation interview training with robotic and virtual tutors. Journal of Systems and Software, 212, 112018. https://doi.org/https://doi.org/10.1016/j.jss.2024.112018
Guo, K., Zhang, J., & Ansari, H. W. A. (2025). Teacher care and mental wellbeing: Exploring the role of grit, resilience, and AI-interaction in education management. Acta Psychologica, 261, 105977. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105977
Heydarnejad, T. (2025). Unmasking the Impacts of Self-Evaluation in AI-Supported Writing Instruction on EFL Learners’ Emotion Regulation, Self-Competence, Motivation, and Writing Achievement. Computers and Education: Artificial Intelligence, 100494. https://doi.org/https://doi.org/10.1016/j.caeai.2025.100494
Huwer, J., Thyssen, C., Becker-Genschow, S., von Kotzebue, L., Finger, A., Kremser, E., Berber, S., Brückner, M., Maurer, N., Bruckermann, T., Meier, M., & Thoms, L.-J. (2025). Competencies for teaching with and about artificial intelligence in the natural sciences — DiKoLAN AI. Computers and Education Open, 9, 100303. https://doi.org/https://doi.org/10.1016/j.caeo.2025.100303
Kohnke, L., & Moorhouse, B. L. (2025). Enhancing the emotional aspects of language education through generative artificial intelligence (GenAI): A qualitative investigation. Computers in Human Behavior, 167, 108600. https://doi.org/https://doi.org/10.1016/j.chb.2025.108600
Korzynski, P., Edwards, A., Gupta, M. C., Mazurek, G., & Wirtz, J. (2025). Humanoid robotics and agentic AI: reframing management theories and future research directions. European Management Journal, 43(4), 548–560. https://doi.org/https://doi.org/10.1016/j.emj.2025.06.002
Lachheb, A., Leung, J., Abramenka-Lachheb, V., & Sankaranarayanan, R. (2025). AI in higher education: A bibliometric analysis, synthesis, and a critique of research. The Internet and Higher Education, 67, 101021. https://doi.org/https://doi.org/10.1016/j.iheduc.2025.101021
Lai, W. Y. W., & Lee, J. S. (2024). A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedents. Computers and Education: Artificial Intelligence, 7, 100291. https://doi.org/https://doi.org/10.1016/j.caeai.2024.100291
Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 6, 100174. https://doi.org/https://doi.org/10.1016/j.caeo.2024.100174
Lissack, M., & Meagher, B. (2024). Responsible Use of Large Language Models: An Analogy with the Oxford Tutorial System. She Ji: The Journal of Design, Economics, and Innovation, 10(4), 389–413. https://doi.org/https://doi.org/10.1016/j.sheji.2024.11.001
Liu, G. L., Lee, J. S., & Zhao, X. (2025). Critical digital literacies, agentic practices, and AI-mediated informal digital learning of English. System, 134, 103797. https://doi.org/https://doi.org/10.1016/j.system.2025.103797
Liu, Y., Zhang, H., Jiang, M., Chen, J., & Wang, M. (2024). A systematic review of research on emotional artificial intelligence in English language education. System, 126, 103478. https://doi.org/https://doi.org/10.1016/j.system.2024.103478
Mahmoudi-Dehaki, M., & Nasr-Esfahani, N. (2025). Empowering stuttering female English learners: AI vs. human-AI hybrid tutoring for alleviating social anxiety. Journal of Responsible Technology, 24, 100141. https://doi.org/https://doi.org/10.1016/j.jrt.2025.100141
Menon, D., & Shilpa, K. (2023). “Hey, Alexa” “Hey, Siri”, “OK Google” ….” exploring teenagers’ interaction with artificial intelligence (AI)-enabled voice assistants during the COVID-19 pandemic. International Journal of Child-Computer Interaction, 38, 100622. https://doi.org/https://doi.org/10.1016/j.ijcci.2023.100622
Mim, J. F., Islam, M. M., & Raza, A. H. (2025). A hybrid MCDM approach for unveiling ChatGPT’s effect on students’ learning. Computers and Education: Artificial Intelligence, 9, 100457. https://doi.org/https://doi.org/10.1016/j.caeai.2025.100457
Namaziandost, E. (2025). Integrating flipped learning in AI-enhanced language learning: Mapping the effects on metacognitive awareness, writing development, and foreign language learning boredom. Computers and Education: Artificial Intelligence, 9, 100446. https://doi.org/https://doi.org/10.1016/j.caeai.2025.100446
Nandagopal, S. (2025). Transforming the self: Individual-level changes arising from collaboration with generative AI. Computers in Human Behavior: Artificial Humans, 6, 100232. https://doi.org/https://doi.org/10.1016/j.chbah.2025.100232
Ng, M. L., Behforouz, B., & Ghaithi, A. Al. (2025). Grammar and engagement in focus: Evaluating Gemini AI’s impact on an educational environment. Computers and Education Open, 9, 100302. https://doi.org/https://doi.org/10.1016/j.caeo.2025.100302
Park, A., & Kim, T. (2025). Code suggestions and explanations in programming learning: Use of ChatGPT and performance. The International Journal of Management Education, 23(2), 101119. https://doi.org/https://doi.org/10.1016/j.ijme.2024.101119
Schmidt, D. A., Alboloushi, B., Thomas, A., & Magalhaes, R. (2025). Integrating artificial intelligence in higher education: perceptions, challenges, and strategies for academic innovation. Computers and Education Open, 9, 100274. https://doi.org/https://doi.org/10.1016/j.caeo.2025.100274
Shahini, A. (2025). Emotional dimensions of feedback: How AI and human responses shape ESL learning outcomes. Ampersand, 15, 100235. https://doi.org/https://doi.org/10.1016/j.amper.2025.100235
?im?ek, A. C., Anders, G., Göth, J., Specht, L., & Huff, M. (2025). Is ChatGPT a good study companion? The role of AI-generated summaries and reflective prompts in learning from educational videos. Computers and Education: Artificial Intelligence, 9, 100512. https://doi.org/https://doi.org/10.1016/j.caeai.2025.100512
Sun, H., Zhang, T., Han, J., & Chu, H. (2024). A fast transfer reinforcement learning model for transferring force-based human speed adjustment skills to robots for collaborative assembly posture alignment. Advanced Engineering Informatics, 62, 102836. https://doi.org/https://doi.org/10.1016/j.aei.2024.102836
Tian, Q., & Zheng, X. (2025). The impact of artificial intelligence on students’ 4C skills: A meta-analysis. Educational Research Review, 49, 100728. https://doi.org/https://doi.org/10.1016/j.edurev.2025.100728
Tram, N. H. M., Nguyen, T. T., & Tran, C. D. (2024). ChatGPT as a tool for self-learning English among EFL learners: A multi-methods study. System, 127, 103528. https://doi.org/https://doi.org/10.1016/j.system.2024.103528
von Garrel, J., & Mayer, J. (2024). Which features of AI-based tools are important for students? A choice-based conjoint analysis. Computers and Education: Artificial Intelligence, 7, 100311. https://doi.org/https://doi.org/10.1016/j.caeai.2024.100311
Xie, L., Jiang, Y., Chang, C.-N., Zeng, X.-Y., Hong, J., & Mo, F. (2025). How are faculty and college students embracing AI? — A multi-informant mixed method study. Computers and Education: Artificial Intelligence, 9, 100506. https://doi.org/https://doi.org/10.1016/j.caeai.2025.100506
Yang, L., & Zhao, S. (2024). AI-induced emotions in L2 education: Exploring EFL students’ perceived emotions and regulation strategies. Computers in Human Behavior, 159, 108337. https://doi.org/https://doi.org/10.1016/j.chb.2024.108337
Zhai, X., & Li, S. (2025). The roles of growth mindset, resilience, and self-efficacy in student Engagement with AI-enhanced Chinese learning: A self-determination theory perspective. Learning and Motivation, 92, 102183. https://doi.org/https://doi.org/10.1016/j.lmot.2025.102183
Zhang, Z. (2025). Enhancing English listening comprehension via AI - based adaptive learning platforms incorporating speech - to - text and predictive analytics. Systems and Soft Computing, 7, 200418. https://doi.org/https://doi.org/10.1016/j.sasc.2025.200418
Zhuang, M., Long, S., Martin, F., & Castellanos-Reyes, D. (2025). The affordances of Artificial Intelligence (AI) and ethical considerations across the instruction cycle: A systematic review of AI in online higher education. The Internet and Higher Education, 67, 101039. https://doi.org/https://doi.org/10.1016/j.iheduc.2025.101039
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