Gamification with natural language processing: A pathway to improved English speaking for EFL students
DOI:
https://doi.org/10.22219/celtic.v12i2.42320Abstract
Advances in artificial intelligence and gamification have transformed language learning by offering interactive, feedback-rich, and engaging environments that go beyond traditional instruction. In this context, this study investigates the impact of Natural Language Processing (NLP)-based gamification applications on the English speaking performance of students learning English as a Foreign Language (EFL). Using a quasi-experimental design, 90 tourism students were divided into three groups: two experimental groups using ELSA Speak and Duolingo, and a control group following conventional learning methods. Speaking tests were administered before and after a ten-session intervention, and the results were analyzed using Quantitative. The findings revealed substantial improvements in the speaking skills of students using NLP-based gamification applications. Both ELSA and Duolingo produced significant gains in pronunciation, fluency, and overall speaking performance compared to the control group, with Duolingo demonstrating slightly more consistent improvements. Large effect sizes confirmed the practical significance of these results, while the negligible changes in the control group underscored the effectiveness of technology-based interventions.
Downloads
References
Akhter, E. (2025). The impact of human-machine interaction on English pronunciation and fluency: Case studies using AI speech assistants. Review of Applied Science and Technology, 04(02), 473–500. https://doi.org/10.63125/1wyj3p84
Al-Khresheh, M. H. (2025). The cognitive and motivational benefits of gamification in English language learning: A systematic review. The Open Psychology Journal, 18(1). https://doi.org/10.2174/0118743501359379250305083002
Azizbek Tursunbayevich, B. (2024). The influence of gamification on student motivation and achievement in higher education English as a foreign languagelearning.
Celaj, D., & Jani, G. (2024). NLP applications in vocabulary acquisition. https://doi.org/http://dx.doi.org/10.2139/ssrn.5010936
Chen, Y., & Zhao, S. (2022). Understanding Chinese EFL learners’ acceptance of gamified vocabulary learning apps: An integration of self-determination theory and technology acceptance model. Sustainability (Switzerland), 14(18). https://doi.org/10.3390/su141811288
Çopur Bilgi, A. (2025). Transforming language education: Opportunities and challenges of AI. Computational Intelligence and Machine Learning, 6(1).
Creswell, J. (2007). Creswell , J . W . ( 2007 ). Qualitative inquiry and research design : Choosing among five approaches ( 2 " ’ ’ Edition ). Thousand Oaks : Sage . Qualitative Inquiry.
Dehghanzadeh, H., Farrokhnia, M., Dehghanzadeh, H., Taghipour, K., & Noroozi, O. (2024). Using gamification to support learning in K-12 education: A systematic literature review. In British Journal of Educational Technology (Vol. 55, Issue 1, pp. 34–70). John Wiley and Sons Inc. https://doi.org/10.1111/bjet.13335
Dewi, D. S., Saptiany, S. G., & Ria, T. N. (2025). Examining the impact of digital storytelling and video-assisted instruction on speaking performance across self-regulated learning levels in an ESP context. Journal on English as a Foreign Language, 15(1), 110–134. https://doi.org/10.23971/jefl.v15i1.9358
Du, Q. (2025). How artificially intelligent conversational agents influence EFL learners’self-regulated learning and retention. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13602-9
Fathali, S., & Okada, T. (2018). Technology acceptance model in technology-enhanced OCLL contexts: A self-determination theory approach. Australasian Journal of Educational Technology, 4, 34. https://doi.org/https://doi.org/10.3390/su141811288
Grimshaw, J., Campbell, M., Eccles, M., & Steen, N. (2000). Experimental and quasi-experimental designs for evaluating guideline implementation strategies. Family Practice, 17(SUPPL. 1). https://doi.org/10.1093/fampra/17.suppl_1.s11
He, L., & Li, C. (2023). Continuance intention to use mobile learning for second language acquisition based on the technology acceptance model and self-determination theory. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1185851
Hellín, C. J., Calles-Esteban, F., Valledor, A., Gómez, J., Otón-Tortosa, S., & Tayebi, A. (2023). Enhancing student motivation and engagement through a gamified learning environment. Sustainability, 15(19). https://doi.org/10.3390/su151914119
Hsu, L. (2023). EFL learners’ self-determination and acceptance of LMOOCs: The UTAUT model. Computer Assisted Language Learning, 36(7), 1177–1205. https://doi.org/10.1080/09588221.2021.1976210
Kassenkhan, A. M., Moldagulova, A. N., & Serbin, V. V. (2025). Gamification and artificial intelligence in education: A review of innovative approaches to fostering critical thinking. IEEE Access, 13, 98699–98728. https://doi.org/10.1109/ACCESS.2025.3576147
Lestari, L. D. A., Hidayati, K. H., & Laeli Anita Fatimatul. (2024). Exploring the level of self-confidence among students with different speaking performance. Celtic: A Journal of Culture, 11(2). https://doi.org/10.22219/celtic.v11i2
Liu, J. (2024). Enhancing English language education through big data analytics and generative AI. Journal of Web Engineering, 23(2), 227–250. https://doi.org/10.13052/jwe1540-9589.2322
Liu, L. (2025). Impact of AI gamification on EFL learning outcomes and nonlinear dynamic motivation: Comparing adaptive learning paths, conversational agents, and storytelling. Education and Information Technologies, 30(8), 11299–11338. https://doi.org/10.1007/s10639-024-13296-5
Marengo, A., Pagano, A., Lund, B., & Santamato, V. (2025). Research AI: Integrating AI and gamification in higher education for e-learning optimization and soft skills assessment through a cross-study synthesis. Frontiers in Computer Science, 7. https://doi.org/10.3389/fcomp.2025.1587040
Markad, R., Misal, T., Patil, P., Pol, S., & Rane, M. S. (2025). Gamification model and behavior analysis using NLP. IJARCCE, 14(6). https://doi.org/10.17148/ijarcce.2025.14606
Masuram, J., & Sripada, P. N. (2020). Developing speaking skills through task-based materials. Procedia Computer Science, 172, 60–65. https://doi.org/10.1016/j.procs.2020.05.009
Mishra, B. K., & Kumar, R. (2021). Natural language processing in artificial intelligence. Apple Academic Press.
Mohana, R., Sekhar, K. C., Gupta, S. S., Punithaasree, K. S., E, G. D., & Muthuperumal, S. (2024). Increasing learner engagement in English language acquisition through AI-powered gamification. 2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA), 1–6. https://doi.org/10.1109/ICAIQSA64000.2024.10882349
Omar, T. K. (2023). Students’ challenges in EFL speaking classrooms. Academic Journal of Nawroz University, 12(4), 957–963. https://doi.org/10.25007/ajnu.v12n4a1809
Pearlin, E., & Gandhi, S. M. G. (2024). Enhancing user behavior analysis in mobile language learning apps through gamification and AI integration: A transformer-based deep learning approach. 2024 International Conference on Data Science and Network Security (ICDSNS), 1–6. https://doi.org/10.1109/ICDSNS62112.2024.10690955
Purgina, M., Mozgovoy, M., & Blake, J. (2020). WordBricks: Mobile technology and visual grammar formalism for gamification of natural language grammar acquisition. Journal of Educational Computing Research, 58(1), 126–159. https://doi.org/10.1177/0735633119833010
Rahmanipur Ali, Shokri Moein, & Heidarnia Mohammadreza. (2025, January 30). Improved personalized language learning for English learners: A systematic review of NLP’s impact. https://www.researchgate.net/publication/389590970
Ramasamy, V., Sigsen, D., & Walia, G. S. (2024). Fostering student engagement and success in STEM education: An AI-driven exploration of high impact practices from cross-disciplinary general education courses. Journal of Engineering Education Transformations, 37.
Riadil, I. G. (2020). Students in speaking skill: Identifying English education students’ perceptions of psychological problems in speaking. Journal of English Teaching and Applied Linguistics, 2.
Rosli, M. S., & Saleh, N. S. (2023). Technology enhanced learning acceptance among university students during Covid-19: Integrating the full spectrum of Self-Determination Theory and self-efficacy into the Technology Acceptance Model. Current Psychology, 42(21), 18212–18231. https://doi.org/10.1007/s12144-022-02996-1
Sadigzade, Z. (2025). Language learning through games: A computational linguistics perspective. EuroGlobal Journal of Linguistics and Language Education, 2(3), 163–188. https://doi.org/10.69760/egjlle.2500206
Safdar, U., Shafi, S., & Junaid, M. (2025). The impact of AI-Driven gamification on student engagement and academic performance in English language teaching. Indus Journal of Social Sciences, 3(1), 646–656. https://doi.org/https://doi.org/10.59075/ijss.v3i1.758
Saleem, A. N., Noori, N. M., & Ozdamli, F. (2022). Gamification applications in E-learning: A literature review. Technology, Knowledge and Learning, 27(1), 139–159. https://doi.org/10.1007/s10758-020-09487-x
Salmanova, S. (2025). Gamification and AI in language learning – A new era of digital education. Acta Globalis Humanitatis et Linguarum, 2(1), 262–269. https://doi.org/10.69760/aghel.02500134
Saptiany, S. G., Hadi, S., Hardian, B. A. N., & Nashir, M. M. (2024). Artificial Intelligence-moderated gamification apps: Elevating gen Z’s English vocabulary mastery. AL-ISHLAH: Jurnal Pendidikan, 16(4), 4969–4983. https://doi.org/10.35445/alishlah.v16i4.5957
Schurz, A., & Coumel, M. (2023). Grammar teaching in ELT: A cross-national comparison of teacher-reported practices. 27(5), 1167–1192. https://doi.org/DOI:10.1177/1362168820964137journals.sagepub.com/home/ltrh
Sheriffdeen, K. (2025). Enhancing personalized learning: The role of adaptive AI-Driven natural language processing in real-time feedback for online education. Journal of Advanced Research in Artificial Intelligence & It’s Applications, 2(1), 3048–6440. https://doi.org/10.5281/zenodo.14292153
Tayeh, Q., Krishan, T. M., & Malkawi, N. (2024). The effect of using gamification to improve EFL students’ academic performance. Journal of Ecohumanism, 3(3), 1566–1573. https://doi.org/10.62754/joe.v3i3.3985
Torres Martín, J., & Romano, A. (2025). Assessing the efficacy of an adaptive learning platform enhanced with gamification and natural language processing for engineering disciplines. Frontiers in Emerging Computer Science and Information Technology, 2. https://irjernet.com/index.php/fecsit
Uppoor, N., Banerjee, D., Shah, D., Mishra, P., & Saha, I. (2022). Interactive language learning with VR and NLP assistance. 2022 IEEE 7th International Conference for Convergence in Technology, I2CT 2022. https://doi.org/10.1109/I2CT54291.2022.9824754
Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1261955
Zerkouk, M., Mihoubi, M., & Chikhaoui, B. (2025). A comprehensive review of AI-based intelligent tutoring systems: Applications and challenges. Journal of Computers in Education. https://doi.org/https://doi.org/10.48550/arXiv.2507.18882
Zrekat, Y., & Al-Sohbani, Y. (2022). Arab EFL University learners’ perceptions of the factors hindering them to speak English fluently. Journal of Language and Linguistic Studies, 18(1), 775–790. https://doi.org/10.52462/jlls.219
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Shella Gherina Saptiany, C Susmono Widagdo, Abel Julia Istifary, Aruf Mustofa

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
- Authors retain copyright to publish without restrictions and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.





















