Artificial Intelligence and Gamification Literacy in Higher Education Language Learning: Insights from a Gamified Diagnostic Test

Authors

  • Fazila Artykbaeva
  • Guldar Tursynova
  • Zhazira Abdullayeva
  • Shopan Mombekova
  • Laila Kassymbekova

Keywords:

AI literacy; gamified learning; language education; digital pedagogy; teacher education

Abstract

The rapid integration of artificial intelligence (AI) and gamification into higher education has transformed approaches to teaching, learning, and assessment. This study introduced and validated a case-based gamified diagnostic test for language education. The test was designed to measure students’ literacy in AI, gamification, and ethical–pedagogical competence in English as a foreign language (EFL) learning contexts. A purposive sample of 227 undergraduate pre-service teachers from Zh.A. Tashenev University (Kazakhstan) participated in the study. A mixed-methods research design was used, integrating quantitative data from gamified diagnostics and qualitative insights from a post-test group discussion with students. The diagnostic instrument, implemented on the Wayground gamified platform, incorporated adaptive scoring, leaderboards, real-time feedback, and progress visualization to foster engagement and reflective learning. Quantitative data included performance indicators (total score, accuracy, completion time), while qualitative reflections captured students’ motivation, ethical awareness, and perceptions of usability. Results reveal moderate to high literacy levels across all domains, with the highest scores in ethical awareness (M = 74.19, SD = 24.01). ANOVA results confirmed significant differences in accuracy across readiness levels (F(2,224) = 634.36, p < .001). Strong correlations among AI literacy, gamification literacy, and ethical awareness (r = .73–.94, p < .01) demonstrated the interconnected nature of cognitive, motivational, and ethical dimensions. The findings support the main hypothesis that gamified diagnostics can enhance digital pedagogical competence by combining engagement, ethical reflection, and data-driven learning. The study offers a replicable framework for integrating responsible AI and gamification training in higher education.

https://doi.org/10.26803/ijlter.25.2.27

References

Abisheva, C., Koldasbaeva, Z., Nossiyeva, N., Irgebaeva, N., Aipova, A., Doldinova, S., Smoilov, S., Aykenova, R., Umirzakova, L., & Idrissova, M. (2024). Formation of ethical competences for AI use in English foreign language teaching. Qubahan Academic Journal, 4(4), 191–205. https://doi.org/10.48161/qaj.v4n4a1256

Acuna, J. M. M., Hernandez-Perlines, F., & Cisneros, M. A. I. (2024). Digital transformation model for universities: A preliminary proposal. International Journal of Educational Practice, 12, 864–895. https://doi.org/10.18488/61.v12i3.3762

Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gaševi?, D., & Martinez-Maldonado, R. (2024). Human-centred learning analytics and AI in education: A systematic literature review. Computers and Education: Artificial Intelligence, 6, Article 100215. https://doi.org/10.1016/j.caeai.2024.100215

Alharbi, W. (2023). AI in the foreign language classroom: A pedagogical overview of automated writing assistance tools. Education Research International, 2023, 1–15. https://doi.org/10.1155/2023/4253331

Alwakid, W. N., Dahri, N. A., Humayun, M., & Alwakid, G. N. (2025). Exploring the role of AI and teacher competencies on instructional planning and student performance in an outcome-based education system. Systems, 13(7), Article 517. https://doi.org/10.3390/systems13070517

Antontseva, D., Kudysheva, A., Fominykh, N., Rakhimgaliyeva, Z., & Seidualiyeva, Z. (2025). Developing foreign language communicative competence in future natural science teachers with online speech simulators: The Kazakhstan experience. International Journal of Learning, Teaching and Educational Research, 24(6), 273–301. https://doi.org/10.26803/ijlter.24.6.13

Asiri, M. J. (2019). Do teachers’ attitudes, perception of usefulness, and perceived social influences predict their behavioral intentions to use gamification in EFL classrooms? Evidence from the Middle East. International Journal of Education and Practice, 7(3), 112–122. https://doi.org/10.18488/journal.61.2019.73.112.122

Barik, T., Murphy-Hill, E., & Zimmermann, T. (2016). A perspective on blending programming environments and games: Beyond points, badges, and leaderboards [Symposium]. 2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 4–8 September 2016, Cambridge, UK (pp. 134?142). IEEE. https://doi.org/10.1109/VLHCC.2016.7739676

Buckler, S. (2015). Self determination theory [Video]. Sage. https://doi.org/10.4135/9781473940970

Chiu, T. K. F. (2025). Developing intelligent-TPACK (I-TPACK) framework from unpacking AI literacy and competency: Implementation strategies and future research direction. Interactive Learning Environments, 33(7), 4189–4192. https://doi.org/10.1080/10494820.2025.2545053

Creighton, S., & Szymkowiak, A. (2014). The effects of cooperative and competitive games on classroom interaction frequencies. Procedia – Social and Behavioral Sciences, 140, 155–163. https://doi.org/10.1016/j.sbspro.2014.04.402

Dindar, M., Ren, L., & Järvenoja, H. (2021). An experimental study on the effects of gamified cooperation and competition on English vocabulary learning. British Journal of Educational Technology, 52(1), 142–159. https://doi.org/10.1111/bjet.12977

Floridi, L., & Cowls, J. (2019, July 2). A unified framework of five principles for AI in society. Harvard Data Science Review. https://doi.org/10.1162/99608f92.8cd550d1

Glover, I. (2013). Play as you learn: Gamification as a technique for motivating learners. In J. Herrington, A. Couros, & V. Irvine (Eds.), Proceedings of the World Conference on Educational Multimedia, Hypermedia and Telecommunications 2013 (pp. 1999–2008). AACE. https://shura.shu.ac.uk/7172/1/Glover_-_Play_As_You_Learn_-_proceeding_112246.pdf

González Vallejo, R. (2024). Notes on gamification and education. Gamification and Augmented Reality, 2, Article 44. https://gr.ageditor.ar/index.php/gr/article/view/13

Jiang, X., Wang, R., Hoang, T., Ranaweera, C., Dong, C., & Myers, T. (2025). AI-powered gamified scaffolding: Transforming learning in virtual learning environments. Electronics, 14(13), Article 2732. https://doi.org/10.3390/electronics14132732

Johnson, B. (2022). Metacognition for artificial intelligence system safety: An approach to safe and desired behavior. Safety Science, 151, Article 105743. https://doi.org/10.1016/j.ssci.2022.105743

Kalni?a, D., N?mante, D., & Baranova, S. (2024). Artificial intelligence for higher education: Benefits and challenges for pre-service teachers. Frontiers in Education, 9, Article 1501819. https://doi.org/10.3389/feduc.2024.1501819

KangJie, E. T., Song, T., Zhu, Z., Li, J., & Lee, Y.-C. (2025). AI literacy education for older adults: Motivations, challenges and preferences. Cornell University. https://doi.org/10.48550/arXiv.2504.14649

Kassenkhan, A., Moldagulova, A., & Serbin, 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

Kondoro, A. M., & Nkwabi, J. (2025). AI writing assistants in Tanzanian universities: Adoption trends, challenges, and opportunities [Workshop session]. Proceedings of the Fourth Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2025), May 2025, Albuquerque, New Mexico, US (pp. 37–46). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.in2writing-1.4

Kumar Minz, N., & Balani, T. (2023). Transforming education: The synergy of gamification and artificial intelligence for personalized learning and engagement. In A. Saluja & N. Kumar Minz (Eds.), Education unleashed: AI era (1st ed., pp. 118–143). Book Rivers.

Kusdiyanti, H., Juariyah, L., Wilujeng, I., Anggarani, D., Bramantya, A., Febrianto, I., & Lazuardi, W. (2024). Authentic assessment based on case-based learning as a media for increasing vocational school students’ economic literacy and self-efficacy in digital era [Conference session]. Proceedings of the EAI International Conference on Education and Training Technologies, 26 September 2023, Malang, East Java, Indonesia. EAI. https://doi.org/10.4108/eai.26-9-2023.2350724

Kütüklü, T. (2025). Augmenting spatial learning and problem-solving in game-based education through virtual environments [Conference session]. Proceedings of the 19th European Conference on Games Based Learning, 1–3 October 2025, Levanger, Norway (pp. 311–321). https://doi.org/10.34190/ecgbl.19.1.3897

Lampropoulos, G., & Sidiropoulos, A. (2024). Impact of gamification on students’ learning outcomes and academic performance: A longitudinal study comparing online, traditional, and gamified learning. Education Sciences, 14(4), Article 367. https://doi.org/10.3390/educsci14040367

Landers, R. N. (2014). Developing a theory of gamified learning: Linking serious games and gamification of learning. Simulation & Gaming, 46(6), 752–768. https://doi.org/10.1177/1046878114563660

Litman, D., & Pan, S. (2002). Designing and evaluating an adaptive spoken dialogue system. User Modeling and User-Adapted Interaction, 12(2–3), 111–137. https://people.cs.pitt.edu/~litman/umuai02.pdf

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, 11299–11338. https://doi.org/10.1007/s10639-024-13296-5

Mahmood, D., & Afzaal, R. (2026). Artificial intelligence–based gamification in cybersecurity education. In Y. Pansare, N. Zaman, & M. Rizvi (Eds.), Gamification learning framework for cybersecurity education (pp. 1–32). IGI Global. https://doi.org/10.4018/979-8-3373-0477-9.ch007

Mejías-Acosta, A., D’Armas Regnault, M., Vargas-Cano, E., Cárdenas-Cobo, J., & Vidal-Silva, C. (2024). Assessment of digital competencies in higher education students: Development and validation of a measurement scale. Frontiers in Education, 9, Article 1497376. https://doi.org/10.3389/feduc.2024.1497376

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041

O’Dea, X., Ng, D. T. K., Wong, M., Chandra, P., Li, S., & Karim, N. (2024). AI literacy and Gen-AI literacy frameworks. In X. O’Dea & D. T. K. Ng (Eds.), Effective practices in AI literacy education: Case studies and reflections (pp. 21–27). Emerald Publishing. https://doi.org/10.1108/978-1-83608-852-3-20241003

OECD. (2021). OECD digital education outlook 2021: Pushing the frontiers with AI, blockchain and robots. Organisation for Economic Co-operation and Development. https://doi.org/10.1787/589b283f-en

Panda, R. (2024). Artificial intelligence in educational systems: From early computational tools to contemporary AI-enhanced learning environments. International Journal of Research Publication and Reviews, 5(8), 3756–3760. https://doi.org/10.55248/gengpi.5.0824.2213

Peralta, E. A. S. (2019). Model predictive para la personalización del aprendizaje en la asignión de ejercicios [Predictive model for learning personalization in exercise assignment]. In J. Sánchez (Ed.)., Nuevas ideas en informática educativa [New ideas in educational computing] (Vol. 15, pp. 147–152). Santiago de Chile. https://www.tise.cl/Volumen15/TISE2019/TISE_2019_paper_4.pdf

Sajja, R., Sermet, Y., Cwiertny, D., & Demir, I. (2025). Integrating AI and learning analytics for data-driven pedagogical decisions and personalized interventions in education. Cornell University. https://doi.org/10.1007/s10758-025-09897-9

Schlick, K. (2024). Technology-integrated pedagogy: Leveraging AI to strengthen critical thinking in education [Manuscript]. ResearchGate. https://www.researchgate.net/publication/384631529_Technology-Integrated_Pedagogy_Leveraging_AI_to_Strengthen_Critical_Thinking_in_Education

Sholihah, L., & Miranty, D. (2025). Gamified diagnostic assessment using Quizizz: Investigating motivation and perceptions of Indonesian ESL students. Jo-ELT (Journal of English Language Teaching), 12(1), Article 176. https://doi.org/10.33394/jo-elt.v12i1.15153

UNESCO. (2025). AI competency framework for education and training. United Nations Educational, Scientific and Cultural Organization.

Welsandt, N., Fortunati, F., Winther, E., & Abs, H. (2024). Constructing and validating authentic assessments: The case of a new technology-based assessment of economic literacy. Empirical Research in Vocational Education and Training, 16, Article 10. https://doi.org/10.1186/s40461-024-00158-0

Wiese, L. J., Patil, I., Schiff, D. S., & Magana, A. J. (2025). AI ethics education: A systematic literature review. Computers and Education: Artificial Intelligence, 8, Article 100405. https://doi.org/10.1016/j.caeai.2025.100405

Yan, L., Zhao, L., Echeverria, V., Jin, Y., Alfredo, R., Li, X., Gaševi?, D., & Martinez-Maldonado, R. (2024). VizChat: Enhancing learning analytics dashboards with contextualised explanations using multimodal generative AI chatbots. Computers and Education: Artificial Intelligence, 6, Article 100226. https://doi.org/10.1016/j.caeai.2024.100226

Downloads

Published

2026-02-28

How to Cite

Artykbaeva, F. ., Tursynova, G. ., Abdullayeva, Z. ., Mombekova, S. ., & Kassymbekova, L. . (2026). Artificial Intelligence and Gamification Literacy in Higher Education Language Learning: Insights from a Gamified Diagnostic Test. International Journal of Learning, Teaching and Educational Research, 25(2), 596–625. Retrieved from http://www.ijlter.net/index.php/ijlter/article/view/2721