Adaptive AI Scaffolding within Gamified Reading Missions: Effects on Grade 10 Students Reading Comprehension in South Sulawesi
Downloads
Background. Reading comprehension remains a critical challenge in secondary education, while conventional instruction often provides limited opportunities for adaptive feedback and sustained student engagement.
Purpose. This study examined the effectiveness of an AI assisted gamified learning strategy in improving the reading comprehension of Grade 10 students at SMA Negeri 4 Sidrap, South Sulawesi, Indonesia.
Method. A quantitative quasi experimental method with a nonequivalent pretest posttest control group design was employed. The participants were 54 students divided into an experimental group (n = 29) and a control group (n = 25). Reading comprehension was measured using a 30 item test, and the data were analyzed using descriptive statistics and ANCOVA.was then processed using descriptive statistics in the form of percentages.
Novelty. The study integrates AI generated adaptive scaffolding with structured gamification elements, including reading missions, progress indicators, achievement badges, and immediate feedback, within a unified reading instruction design.
Results. The experimental group achieved a higher adjusted posttest mean than the control group (82.03 vs. 73.97). ANCOVA revealed a significant instructional effect, F(1, 51) = 15.00, p < .001, partial ?² = .227.
Conclusion. AI assisted gamified learning effectively improved students’ reading comprehension and offers a promising adaptive approach for secondary school literacy instruction.
Abdi Tabari, M., Kushki, A., & Wang, Y. (2025). Comparing the effects of teacher and AI mediated corrective feedback on accuracy, complexity, and quality in L2 written narratives. Computer Assisted Language Learning, 1–24. https://doi.org/10.1080/09588221.2025.2561608
Abduh, A., Achmad, S. F., Syam, C., Samad, S., Arham, M., & Pandang, A. (2024). Dataset on the Number of Schools, Teachers, and Students in Sulawesi, Indonesia: Kindergarten, Primary, Junior, Senior High, Vocational, and Islamic Boarding Schools with Educational Access, Quality, and Cultural Implications to Solve Challenges and Strategies in Education Management and Support Sustainable Development Goals (SDGs).
Akmal, M., & Pritchett, L. (2021). Learning equity requires more than equality: Learning goals and achievement gaps between the rich and the poor in five developing countries?. International Journal of Educational Development, 82, 102350. https://doi.org/10.1016/j.ijedudev.2021.102350
Aldamen, H., Alnemrat, A., Al Deaibes, M., & Alsharefeen, R. (2026). Using AI to adapt reading input for mixed proficiency EFL learners. Frontiers in Education, 11, 1737903. https://doi.org/10.3389/feduc.2026.1737903
Alqahtani, T., Badreldin, H. A., Alrashed, M., Alshaya, A. I., Alghamdi, S. S., Bin Saleh, K., Alowais, S. A., Alshaya, O. A., Rahman, I., Al Yami, M. S., & Albekairy, A. M. (2023). The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research. Research in Social and Administrative Pharmacy, 19(8), 1236–1242. https://doi.org/10.1016/j.sapharm.2023.05.016
Alsawaier, R. S. (2018). The effect of gamification on motivation and engagement. The International Journal of Information and Learning Technology, 35(1), 56–79. https://doi.org/10.1108/IJILT 02 2017 0009
Anggia, H., & Habók, A. (2023). Textual complexity adjustments to the English reading comprehension test for undergraduate EFL students. Heliyon, 9(1), e12891. https://doi.org/10.1016/j.heliyon.2023.e12891
Chen, J. (2022). Effectiveness of blended learning to develop learner autonomy in a Chinese university translation course. Education and Information Technologies, 27(9), 12337–12361. https://doi.org/10.1007/s10639 022 11125 1
Cheng, J., Lu, C., & Xiao, Q. (2025). Effects of gamification on EFL learning: A quasi experimental study of reading proficiency and language enjoyment among Chinese undergraduates. Frontiers in Psychology, 16, 1448916. https://doi.org/10.3389/fpsyg.2025.1448916
Díaz Suárez, V., Martín Paciente, M., & Travieso González, C. M. (2025). Exploring the Impact of Digital Platforms on Teaching Practices: Insights into Competence Development and Openness to Active Methodologies. Applied System Innovation, 8(3), 64. https://doi.org/10.3390/asi8030064
El Fathi, T., Saad, A., Larhzil, H., Lamri, D., & Al Ibrahmi, E. M. (2025). Integrating generative AI into STEM education: Enhancing conceptual understanding, addressing misconceptions, and assessing student acceptance. Disciplinary and Interdisciplinary Science Education Research, 7(1), 6. https://doi.org/10.1186/s43031 025 00125 z
Erniwati, E., Darmawan, D., Kamaruddin, A., & Amalia, R. (2025). Using Collaborative Strategic Reading (CSR) to Improve Reading Comprehension of Vocational School Students (An experimental study at SMK Negeri 1 Dampal Selatan, Toli Toli, Central Sulawesi). Ethical Lingua: Journal of Language Teaching and Literature, 12(1). https://doi.org/10.30605/25409190.786
Erwin, Degeng, M. D. K., Degeng, I. N. S., & Praherdhiono, H. (2026). The effectiveness of collaborative blended learning on mastery of instructional media concepts. Multidisciplinary Reviews, 9(12), 2026497. https://doi.org/10.31893/multirev.2026497
Erwin, E., & Kuswandi, D. (2024). Tinjauan pustaka: Model pembelajaran blended learning di era Society 5.0. INOPENDAS: Jurnal Ilmiah Kependidikan, 7(1), 39–47.
Eti, S. (2015). Nonequivalent Pretest Posttest Control Group Design. Jurnal Penelitian Ilmu Pendidikan, 8, 54–67.
Ferrara, S., Steedle, J. T., & Frantz, R. S. (2022). Response Demands of Reading Comprehension Test Items: A Review of Item Difficulty Modeling Studies. Applied Measurement in Education, 35(3), 237–253. https://doi.org/10.1080/08957347.2022.2103135
Gifarini, T. L., Usman, S., Mashuri, M., & Manurung, K. (2025). Enhancing students’ reading comprehension through the Jigsaw method: Evidence from a private senior high school in Palu, Central Sulawesi: PENERAPAN METODE JIGSAW UNTUK MENINGKATKAN PEMAHAMAN MEMBACA SISWA KELAS X DI SMA LAB SCHOOL UNTAD PALU. Celtic?: A Journal of Culture, English Language Teaching, Literature and Linguistics, 12(2), 908–923. https://doi.org/10.22219/celtic.v12i2.42089
Gyedu, F. O., Partey, P. A., Boafo, F. A., & Agbo, D. D. (2026). Gamification Effect: Enhancing Student Learning Outcomes in Higher Education: A Meta Analysis and Policy Implications. Sage Open, 16(1), 21582440261421375. https://doi.org/10.1177/21582440261421375
Köhler, C., Hartig, J., & Naumann, A. (2021). Detecting Instruction Effects-Deciding Between Covariance Analytical and Change Score Approach. Educational Psychology Review, 33(3), 1191–1211. https://doi.org/10.1007/s10648 020 09590 6
Lermann Henestrosa, A., & Kimmerle, J. (2025). “Always check important information!”-The role of disclaimers in the perception of AI generated content. Computers in Human Behavior: Artificial Humans, 4, 100142. https://doi.org/10.1016/j.chbah.2025.100142
Lohr, S. L. (2021). Sampling: Design and analysis. Chapman and Hall/CRC.
Marcq, K., & Braeken, J. (2025). From framework to functionality: A cross country analysis of PISA 2018 reading assessment framework’s item features as determinants of item difficulty. Large Scale Assessments in Education, 13(1), 26. https://doi.org/10.1186/s40536 025 00261 y
Mudinillah, A., Kuswandi, D., Erwin, E., Sugiarni, S., Winarno, W., Annajmi, A., & Hermansah, S. (2024). Optimizing Project Based Learning in Developing 21st Century Skills: A Future Education Perspective. Qubahan Academic Journal, 4(2), 86–101. https://doi.org/10.48161/qaj.v4n2a352
Nguyen Viet, B., & Doan Ngoc Minh, H. (2025). How Gamification Enhances Learning Effectiveness Through Blended Learning and Intrinsic Motivation: The Moderating Effects of Self Regulation. Sage Open, 15(4), 21582440251385846. https://doi.org/10.1177/21582440251385846
Nygren, T., Spearing, E. R., Fay, N., Vega, D., Hardwick, I. I., Roozenbeek, J., & Ecker, U. K. H. (2026). The seven roles of generative AI: Potential & pitfalls in combatting misinformation. Behavioral Science & Policy, 12(1), 30–39. https://doi.org/10.1177/23794607261417815
Sajja, R., Sermet, Y., Cikmaz, M., Cwiertny, D., & Demir, I. (2024). Artificial Intelligence Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education. Information, 15(10), 596. https://doi.org/10.3390/info15100596
Sinha, T. (2026). Making failure desired during learning – A quasi experimental study. Thinking Skills and Creativity, 60, 102094. https://doi.org/10.1016/j.tsc.2025.102094
Spencer, M., Gilmour, A. F., Miller, A. C., Emerson, A. M., Saha, N. M., & Cutting, L. E. (2019). Understanding the influence of text complexity and question type on reading outcomes. Reading and Writing, 32(3), 603–637. https://doi.org/10.1007/s11145 018 9883 0
Sun, C. T., Chou, K. T., & Yu, H. C. (2022). Relationship between digital game experience and problem solving performance according to a PISA framework. Computers & Education, 186, 104534. https://doi.org/10.1016/j.compedu.2022.104534
Urmeneta, A., & Romero, M. (Eds.). (2024). Creative Applications of Artificial Intelligence in Education. Springer Nature Switzerland. https://doi.org/10.1007/978 3 031 55272 4
Yang, Y., Chen, J., & Zhuang, X. (2025). Self determination theory and the influence of social support, self regulated learning, and flow experience on student learning engagement in self directed e learning. Frontiers in Psychology, 16, 1545980. https://doi.org/10.3389/fpsyg.2025.1545980
Zhou, Q., Zhang, H., & Li, F. (2024). The Impact of Online Interactive Teaching on University Students’ Deep Learning-The Perspective of Self Determination. Education Sciences, 14(6), 664. https://doi.org/10.3390/educsci14060664
Copyright (c) 2024 Firman Saleh, Hastuti Hamka
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
