Artificial Intelligence-Based Interactive Learning Media for Improving Reading Comprehension in Elementary Education
Published 2026-04-20
Keywords
- Artificial Intelligence,
- Elementary Education,
- Interactive Learning Media,
- Reading Comprehension,
- Technology-Enhanced Learning
Copyright (c) 2026 Nining Widyah Kusnanik, Lalu Ibrohim Burhan (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
This study investigates the effectiveness of Artificial Intelligence (AI)-based interactive learning media in improving elementary school students' reading comprehension within a technology-enhanced learning environment. The increasing integration of AI in education has created opportunities to develop adaptive, data-driven, and interactive instructional systems that support personalized learning. However, empirical studies examining the impact of AI on elementary-level reading comprehension remain limited. This study employed a quasi-experimental design with a pretest–posttest control group approach involving 60 fourth-grade students from a public elementary school in East Lombok Regency, Indonesia. Participants were divided into an experimental group that received AI-supported reading instruction and a control group that received conventional reading instruction. Data were collected using a reading comprehension test consisting of 30 items, student response questionnaires, and classroom observations. Quantitative data were analyzed using descriptive statistics, paired-sample and independent-sample t-tests, normalized gain (N-gain) analysis, and effect size calculations.
In contrast, qualitative data were examined through thematic analysis. The results indicate that students exposed to AI-based interactive learning media demonstrated significantly greater improvements in reading comprehension than those receiving traditional instruction. The greatest learning gains were observed in higher-order comprehension skills, particularly inferential reasoning and summarizing ability. Additionally, students reported positive perceptions of the AI-supported learning environment, highlighting the role of adaptive feedback and interactive tasks in fostering comprehension. These findings suggest that AI-based interactive learning media can effectively enhance elementary students' reading comprehension and offer a promising approach to strengthening literacy instruction in technology-enhanced learning environments.
References
- Abid, N., Aslam, S., Alghamdi, A. A., & Kumar, T. (2023). Relationships among students’ reading habits, study skills, and academic achievement in English at the secondary level. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1020269
- AlShaikh, R., Al-Malki, N., & Almasre, M. (2024). The implementation of the cognitive theory of multimedia learning in the design and evaluation of an AI educational video assistant utilizing large language models. Heliyon, 10(3), e25361. https://doi.org/10.1016/j.heliyon.2024.e25361
- Crompton, H., Edmett, A., Ichaporia, N., & Burke, D. (2024). AI and English language teaching: Affordances and challenges. British Journal of Educational Technology, 55(6), 2503–2529. https://doi.org/10.1111/bjet.13460
- Elmaadaway, M. A. N., El‐Naggar, M. E., & Abouhashesh, M. R. I. (2025). Improving Primary School Students’ Oral Reading Fluency Through Voice Chatbot‐Based AI. Journal of Computer Assisted Learning, 41(2). https://doi.org/10.1111/jcal.70019
- Fansury, A. H., Januarty, R., Rahman, A. W., & Syawal. (2020). Digital Content for Millennial Generations: Teaching the English Foreign Language Learner on COVID-19 Pandemic. Journal of Southwest Jiaotong University, 55(3). https://doi.org/10.35741/issn.0258-2724.55.3.40
- Feng, Y., & Wang, X. (2023). A comparative study on the development of Chinese and English abilities of Chinese primary school students through two bilingual reading modes: human-AI robot interaction and paper books. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1200675
- Lim, J., Leinonen, T., Lipponen, L., Lee, H., DeVita, J., & Murray, D. (2023). Artificial intelligence as relational artifacts in creative learning. Digital Creativity, 34, 192–210. https://doi.org/10.1080/14626268.2023.2236595
- Ma, Y., & Chen, M. (2025). The human touch in AI: optimizing language learning through self-determination theory and teacher scaffolding. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1568239
- Maassen, B. A. M., Glatz, T., Borleffs, E., Martínez, C., & de Groot, B. J. A. (2025). Digital game-based learning for dynamic assessment and early intervention targeting reading difficulties: Cross-linguistic studies of GraphoLearn. Clinical Linguistics & Phonetics, 39(6–8), 576–601. https://doi.org/10.1080/02699206.2025.2452979
- Md Yunus, M., Suliman, A., Szee Huei, L., Fang Kai, T., & Kiew, S. (2020). The Use of Voca-Lens to Enhance the Students Vocabulary Repertoire. International Journal of English Language and Literature Studies, 9(3), 172–184. https://doi.org/10.18488/journal.23.2020.93.172.184
- Muhid, A., Amalia, E. R., Hilaliyah, H., Budiana, N., & Wajdi, M. B. N. (2020). The Effect of Metacognitive Strategies Implementation on Students’ Reading Comprehension Achievement. International Journal of Instruction, 13(2), 847–862. https://doi.org/10.29333/iji.2020.13257a
- Orellana, P., Silva, M., & Iglesias, V. (2024). Students’ reading comprehension level and reading demands in teacher education programs: the elephant in the room? Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1324055
- Pellas, N. (2023). The influence of sociodemographic factors on students’ attitudes toward AI-generated video content creation. Smart Learning Environments, 10(1), 57. https://doi.org/10.1186/s40561-023-00276-4
- Rasmitadila, R., Aliyyah, R. R., Rachmadtullah, R., Samsudin, A., Syaodih, E., Nurtanto, M., & Tambunan, A. R. S. (2020). The Perceptions of Primary School Teachers of Online Learning during the COVID-19 Pandemic Period: A Case Study in Indonesia. Journal of Ethnic and Cultural Studies, 90–109. https://doi.org/10.29333/ejecs/388
- Rico-Juan, J., Peña-Acuña, B., & Navarro-Martínez, Ó. (2024). Holistic exploration of reading comprehension skills, technology and socioeconomic factors in Spanish teenagers. Heliyon, 10. https://doi.org/10.1016/j.heliyon.2024.e32637
- Saritepeci, M., & Durak, H. Y. (2024). Effectiveness of artificial intelligence integration in design-based learning on design thinking mindset, creative and reflective thinking skills: An experimental study. Education and Information Technologies, 29, 25175–25209. https://doi.org/10.1007/s10639-024-12829-2
- Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1260843
- 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
- Wen, Y., Chiu, M., Guo, X., & Wang, Z. (2025). AI ‐powered vocabulary learning for lower primary school students. British Journal of Educational Technology, 56(2), 734–754. https://doi.org/10.1111/bjet.13537
- Yapp, D., de Graaff, R., & van den Bergh, H. (2023). Effects of reading strategy instruction in English as a second language on students’ academic reading comprehension. Language Teaching Research, 27(6), 1456–1479. https://doi.org/10.1177/1362168820985236
- Zhang, Q., Nie, H., Fan, J., & Liu, H. (2025). Exploring the Dynamics of Artificial Intelligence Literacy on English as a Foreign Language Learners’ Willingness to Communicate: The Critical Mediating Roles of Artificial Intelligence Learning Self-Efficacy and Classroom Anxiety. Behavioral Sciences, 15(4), 523. https://doi.org/10.3390/bs15040523
