Gamified AI for Fostering Vocabulary Retention and Motivation: A Phenomenological Study of Uzbek EFL Learners

Authors

DOI:

https://doi.org/10.54855/

Keywords:

Gamified AI platforms, Vocabulary retention, Motivation, Cognitive Load Theory, Interpretative Phenomenological Analysis, Uzbek EFL learners

Abstract

The increasing integration of gamified artificial intelligence (AI) platforms in English as a Foreign Language (EFL) education offers promising prospects for vocabulary development, yet their cognitive and motivational impacts remain inadequately explored in culturally distinct contexts. While these platforms employ adaptive algorithms and game mechanics to customize learning experiences and sustain engagement, they may also generate disparities between design assumptions and the actual socio-technological contexts of learners, particularly in resource-constrained, teacher-centric educational systems like that of Uzbekistan. This research addressed a gap by doing a phenomenological inquiry grounded on Cognitive Load Theory (CLT), analyzing the engagement of 24 Uzbek female EFL learners with a gamified AI vocabulary platform across four weeks of casual use. Data were collected using digital reflective diaries including prompts designed for language retention and motivation, and were analyzed using Interpretative Phenomenological Analysis (IPA). Findings identified three interconnected categories: (1) Enhancing cognitive architecture through gamified scaffolding (e.g., minimizing extraneous load via micro-task sequencing and augmenting germane load through adaptive feedback loops), (2) Regulating motivation through intrinsic gamification cues (e.g., fostering autonomy through meaningful choices and sustaining engagement through mastery-oriented progression), and (3) Navigating socio-cultural and technological ambiguities (e.g., tension between gamified simplicity and academic complexity and digital literacy disparities exacerbating extraneous load). The results demonstrate that the efficacy of gamified AI systems depends not just on algorithmic customization but also on its alignment with learners' cognitive capacities, emotional needs, and contextual constraints.

Author Biographies

  • Barno Sayfutdinovna Abdullaeva, Vice-Rector for Scientific Affairs, Tashkent State Pedagogical University, Tashkent, Uzbekistan

    Professor Dr. Barno Abdullaeva, born in Tashkent in 1974, earned her PhD in Pedagogical Sciences in 2002 and her DSc in 2007 at Nizami Tashkent State Pedagogical University, where she is currently Professor. Her research focuses on the methodological and didactic foundations of interdisciplinary communication in mathematics education. She is the author of multiple monographs, textbooks, manuals, and more than 150 scholarly publications, and has developed six certified educational software systems. Prof. Abdullaeva has been honored with numerous national awards, including the “Excellent Public Education Worker” and the Independence Anniversary medals. She chairs the Scientific Council on Pedagogical Sciences at her university and serves on the Scientific and Technical Council under the Ministry of Innovative Development.
    ORCID:
    https://orcid.org/0000-0003-3648-4601

  • Mustafo Zulkhonov, University of Science and Technologies, Tashkent, Uzbekistan

    Dr. Mustafa Juraevich Zulkhonov, born in 1961 in Chirakchi District, earned his degree in German and English Philology in 1987 and his PhD in 1998 with a dissertation on consonant combinations in German and Uzbek. He has taught German and linguistics at several major universities, including the National University of Uzbekistan and the State University of World Languages. Since 2025, he has been Acting Associate Professor in the Department of Foreign Languages at the University of Science and Technology. Dr. Zulkhonov is the author of several textbooks and over 100 academic papers. He is married with four children. ORCID: https://orcid.org/0009-0000-7094-1541

  • Dilrabo Elova, Department of Linguistics, Alisher Navo’i, Tashkent State University of Uzbek Language and Literature, Tashkent, Uzbekistan

    Dr. Dilrabo Elova, born in 1983, completed her BA in Uzbek Philology (2004) and MA in Linguistics (2006) at Bukhara State University. She earned her PhD in Philology in 2022 with a dissertation on stylistic tagging and linguistic support for the Uzbek Language Corpus. She is currently Associate Professor in the Department of Uzbek Linguistics at the Tashkent State University of Uzbek Language and Literature. Her research spans sociolinguistics, computational linguistics, and applied stylistics, and she has contributed to major projects such as the Uzbek National Corpus and UzWordNet. Dr. Elova has 46 publications and holds three database certificates in information systems. ORCID: https://orcid.org/0000-0002-2329-1811

  • Jamshid Pardaev, Department of Finance and Tourism, Termez University of Economics and Service, Uzbekistan

    Dr. Jamshid Pardaev, born in 1988, completed his studies at the Tashkent Institute of Textile and Light Industry (2011) and earned his Master’s degree in Economics from the Tashkent State University of Economics (2013). He worked in finance and banking institutions while researching enterprise taxation, earning his PhD in Economics in 2024. He is currently Acting Associate Professor in the Department of Finance and Statistics at Termez University of Economics and Service. Dr. Pardaev has published one monograph, one textbook, and over 30 articles (including eight Scopus-indexed papers). He is a recipient of the “Shukhrat” Medal, the “Active Entrepreneur” Badge, and the “Dustlik” Order, and serves as a Deputy of the Surkhandarya Regional Council of People’s Deputies. ORCID: https://orcid.org/0009-0004-8319-6906

  • Laylo Usmonova, Department of Social Sciences and Humanities, Samarkand State Medical University, Samarkand, Uzbekistan

    Dr. Laylo Usmonova, born in 1989 in Samarkand, earned her Bachelor’s and Master’s degrees in Philosophy and Aesthetics from Samarkand State University. She taught at the Samarkand School of Arts while researching aesthetic education, later serving as lecturer at the Samarkand Institute of Foreign Languages and as a research applicant at Mirzo Ulugbek National University. Since 2020, she has been Associate Professor in the Department of Social and Humanitarian Sciences at Samarkand State Medical University. She completed her PhD in 2021 on miniature art in Central Asia and has authored two monographs, a textbook, a teaching manual, and over 50 publications. Her current work focuses on philosophical comparative studies and the dynamics of scientific knowledge. ORCID: https://orcid.org/0000-0002-7269-9688

References

Bahari, A., Wu, S., & Ayres, P. (2023). Improving computer-assisted language learning through the lens of cognitive load. Educational Psychology Review, 35(2), 53-74. https://doi.org/10.1007/s10648-023-09764-y

Barkhuizen, G., Benson, P., & Chik, A. (2013). Narrative inquiry in language teaching and learning research. Routledge.

Bass-Dolivan, D. W. (2011). Students’ engagement with second language learning: a sociocultural approach (Doctoral dissertation, University of Wollongong).

Chapelle, C. A. (2019). Technology-mediated language learning. In J. W. Schwieter & A. Benati (Eds.), The Cambridge Handbook of Language Learning (pp. 575–596). Cambridge University Press.

Deci, E. L., & Ryan, R. M. (2013). Intrinsic motivation and self-determination in human behavior. Springer.

Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: Defining gamification. In Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments (pp. 9–15). Association for Computing Machinery. https://doi.org/10.1145/2181037.2181040

Dörnyei, Z. (2001). Motivational strategies in the language classroom. Cambridge University Press.

Ellis, R. (1997). Second language acquisition. Oxford University Press.

Fatikhah, E. N., Martono, M., & Asrori, M. (2018). The correlation between learning motivation, vocabulary mastery and listening comprehension. English Education, 6(2), 231-238.

Fithriani, R. (2021). The utilization of mobile-assisted gamification for vocabulary learning: Its efficacy and perceived benefits. Computer-Assisted Language Learning Electronic Journal, 22(3), 146-163.

Godwin-Jones, R. (2023). Smart devices and informal language learning. In D. Toffoli, G. Sockett, & M. Kusyk (Eds.), Language learning and leisure: Informal language learning in the digital age (pp. 89–113). Walter de Gruyter GmbH.

Godwin-Jones, R. (2025). AI and VR converge: The future of language learning in an emerging metaverse. In AI-Mediated Language Education in the Metaverse Era (pp. 221-246). Singapore: Springer Nature Singapore.

Hamari, J., Koivisto, J., & Sarsa, H. (2014). Does gamification work? A study on the effects of gamification on engagement and motivation. In 47th Hawaii International Conference on System Sciences (pp. 3025–3034). IEEE. https://doi.org/10.1109/HICSS.2014.377

Hasanova, D. (2007). Teaching and learning English in Uzbekistan. English Today, 23(1), 3–9. https://doi.org/10.1017/S0266078407001022

Hasanova, D. (2022). The linguistic landscape of bukhara and tashkent in the post‐soviet era. World Englishes, 41(1), 24-37.

Hasanova, D., & Shadieva, T. (2008). Implementing communicative language teaching in Uzbekistan. TESOL Quarterly, 42(1), 138-143. https://www.jstor.org/stable/40264433

Hiver, P., Al-Hoorie, A. H., & Mercer, S. (Eds.). (2020). Student engagement in the language classroom. Multilingual Matters.

Hirose, K. (2009). Student-student written interactions during peer feedback in English writing instruction. ARELE: Annual Review of English Language Education in Japan, 20, 91–100.

Hockly, N. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. RELC Journal, 54(2), 445-451. https://doi.org/10.1177/00336882231168504

Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends, research issues and applications of artificial intelligence in language education. Educational Technology & Society, 26(1), 112-131. https://www.jstor.org/stable/48707971

Hubbard, P. (2013). Making a case for learner training in technology-enhanced language learning environments. CALICO Journal, 30(2), 163–178. https://doi.org/10.11139/cj.30.2.163-178

Hyland, K., & Hyland, F. (2006). Feedback on second language students' writing. Language Teaching, 39(2), 83-101. https://doi.org/10.1017/S0261444806003399

Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need?. Educational Psychology Review, 23(1), 1-19. https://doi.org/10.1007/s10648-010-9150-7

Kapur, M. (2015). Learning from productive failure. Learning: Research and practice, 1(1), 51-65. https://doi.org/10.1080/23735082.2015.1002195

Kirschner, P. A. (2002). Cognitive load theory: Implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1), 1-10. https://doi.org/10.1016/S0959-4752(01)00014-7

Littlemore, J. (2019). Metaphors in the Mind. Cambridge University Press.

MacIntyre, P. D., & Gardner, R. C. (1991). Methods and results in examining the relationship between language anxiety and second language learning. Language Learning, 41(4), 513–534. https://doi.org/10.1111/j.1467-1770.1991.tb00695.x

Madjar, N., Weinstock, M., & Kaplan, A. (2017). Epistemic beliefs and achievement goal orientations: Relations between constructs versus personal profiles. The Journal of Educational Research, 110(1), 32-49. https://doi.org/10.1080/00220671.2015.1034353

Mayer, R. E. (2002). Multimedia learning (3rd ed.). Cambridge University Press.

Mayer, R. E. (2014). Computer games for learning: An evidence-based approach. MIT press.

Mercer, S., & Dörnyei, Z. (2020). Engaging language learners in contemporary classrooms. Cambridge University Press.

Molina, D. V. T., Castro, M. D. C. R., Barrera, L. V. Q., & Velasco, Y. J. G. (2024). Gamification and its benefits for English vocabulary development in preschool children. Reincisol., 3(6), 5787-5802.

Nation, I. S., & Nation, I. S. P. (2001). Learning vocabulary in another language. Cambridge University Press.

Nazirova, S. O., Jalolova, S. M., Agzamova, D. B., Mamatova, F. M., & Yusupova, S. B. (2023). The problems faced by the teachers in teaching English as a foreign language in Uzbekistan. Journal of Law and Sustainable Development, 11(12), e2698-e2698. https://doi.org/10.55908/sdgs.v11i12.2698

Norton, B. (2013). Identity and language learning: Extending the conversation (2nd ed.). Multilingual Matters.

Paivio, A. (2014). Mind and its evolution: A dual coding theoretical approach. Lawrence Erlbaum Associates.

Perfetti, C. A., & Hart, L. (2001). The lexical basis of comprehension skill. In D. S. Gorfein (Ed.), On the consequences of meaning selection: Perspectives on resolving lexical ambiguity (pp. 67–86). American Psychological Association.

Piniel, K., & Zólyomi, A. (2022). Gender Differences in Foreign Language Classroom Anxiety: Results of a Meta-Analysis. Studies in Second Language Learning and Teaching, 12(2), 173-203.

Qian, D. D. (2002). Investigating the relationship between vocabulary knowledge and academic reading performance: An assessment perspective. Language Learning, 52(3), 513–536. https://doi.org/10.1111/1467-9922.00193

Rasti-Behbahani, A., & Shahbazi, M. (2022). Investigating the effectiveness of a digital game-based task on the acquisition of word knowledge. Computer Assisted Language Learning, 35(8), 1920-1945. https://doi.org/10.1080/09588221.2020.1846567

Read, J. (2000). Assessing vocabulary. Cambridge University Press.

Reynolds, B. L., & Kao, C. W. (2021). The effects of digital game-based instruction, teacher instruction, and direct focused written corrective feedback on the grammatical accuracy of English articles. Computer assisted language learning, 34(4), 462-482. https://doi.org/10.1080/09588221.2019.1617747

Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, Article 101860. https://doi.org/10.1016/j.cedpsych.2020.101860

Saito, K., Dewaele, J. M., & Abe, M. (2025). Disentangling the causal role of motivation, enjoyment, and anxiety in second language speech learning: A final report. Studies in Second Language Acquisition, 1-27. https://doi.org/10.1017/S0272263125000038

Savignon, S. J. (2018). Communicative competence. The TESOL Encyclopedia of English Language Teaching, 1-7.

Schmitt, N. (2008). Instructed second language vocabulary learning. Language Teaching Research, 12(3), 329–363. https://doi.org/10.1177/1362168808089921

Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative phenomenological analysis: Theory, method and research. Sage Publications.

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Springer.

Tan, L. Y., Hu, S., Yeo, D. J., & Cheong, K. H. (2025). Artificial intelligence-enabled adaptive learning platforms: A Review. Computers and Education: Artificial Intelligence, Article 100429. https://doi.org/10.1016/j.caeai.2025.100429

Temel, T., & Cesur, K. (2024). The effect of gamification with web 2.0 tools on EFL learners’ motivation and academic achievement in online learning environments. Sage Open, 14(2), 21582440241247928. https://doi.org/10.1177/21582440241247928

Ushioda, E. (2011). Language learning motivation, self and identity: Current theoretical perspectives. Computer Assisted Language Learning, 24(3), 199-210. https://doi.org/10.1080/09588221.2010.538701

van Merriënboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 53(3), 5–13. https://doi.org/10.1007/BF02504793

Webb, S., & Nation, P. (2017). How vocabulary is learned. Oxford University Press.

Yang, Y. F., Tseng, C. C., & Lai, S. C. (2024). Enhancing teachers’ self-efficacy beliefs in AI-based technology integration into English speaking teaching through a professional development program. Teaching and Teacher Education, 144, 104582. https://doi.org/10.1016/j.tate.2024.104582

Zou, B., Liviero, S., Hao, M., & Wei, C. (2020). Artificial intelligence technology for EAP speaking skills: Student perceptions of opportunities and challenges. In Technology and the psychology of second language learners and users (pp. 433–463). Springer.

Zou, D., & Xie, H. (2018). Personalized word-learning based on technique feature analysis and learning analytics. Educational Technology & Society, 21(2), 233–244. https://www.jstor.org/stable/26388363

Downloads

Published

2026-01-01

How to Cite

Gamified AI for Fostering Vocabulary Retention and Motivation: A Phenomenological Study of Uzbek EFL Learners. (2026). Computer-Assisted Language Learning Electronic Journal, 26(7), 117-136. https://doi.org/10.54855/