AI in Students’ Mathematics Learning: A PRISMA-Based Systematic Review of Challenges and Solutions (2021-2025)
Keywords:
AI; mathematics learning; challenges; solutions; PRISMAAbstract
Digital technology has fundamentally transformed the landscape of education. Recent advances in artificial intelligence (AI) are redefining educational practices and creating new opportunities for mathematics learning. However, despite growing interest, AI usage in mathematics learning remains in its early stages. Existing studies demonstrate the limited integration of AI tools into mathematics-specific pedagogy and insufficient focus on students’ mathematical problem-solving abilities, while there remains a need for the challenges associated with AI implementation to be systematically categorized. To address these gaps, this study conducted a systematic literature review (SLR) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Twelve eligible quantitative studies published between 2021 and 2025 were retrieved from Web of Science (WoS) and Scopus databases using rigorous screening procedures and predefined inclusion criteria. Subsequently, these eligible studies underwent in-depth analysis to synthesize research characteristics, AI technologies implemented, challenges encountered in AI-supported mathematics learning, and corresponding solutions. The findings indicate that China contributed the largest number of publications. The reviewed studies predominantly employed quasi-experimental designs with short intervention durations and small sample sizes, with most research being conducted in primary education settings. Three primary types of AI technologies were identified: adaptive learning systems, intelligent tutoring systems, and chatbots. This review highlighted three major categories of challenges and solutions: research-related, technical and design-related, and educational-pedagogical. Finally, this study offers evidence-based insights to support researchers, developers, educators, and policymakers in aligning AI technologies with the cognitive and problem-solving demands of mathematics learning, informing more focused instructional design.
https://doi.org/10.26803/ijlter.25.3.12
References
Aditya, R. Q., & Suranto, S. (2024). The role of educational transformation in the digital era in improving student quality. Al Qalam: Jurnal Ilmiah Keagamaan Dan Kemasyarakatan, 18(3), 1756-1776. https://doi.org/10.35931/aq.v18i3.3301
Adiyono, A., Suwartono, T., Nurhayati, S., Dalimarta, F. F., & Wijayanti, O. (2025). Impact of artificial intelligence on student reliance for exam answers: A case study in IRCT Indonesia. International Journal of Learning, Teaching and Educational Research, 24(3), 455–479. https://doi.org/10.26803/ijlter.24.3.22
Alam, T. M., Stoica, G. A., Sharma, K., & Özgöbek, Ö. (2025). Digital technologies in the classrooms in the last decade (2014–2023): A bibliometric analysis. Frontiers in Education, 10, 1533588. https://doi.org/10.3389/feduc.2025.1533588
Alkhasawneh, S. (2025). AI-driven personalized mathematics learning through interactive mobile platforms: Effects on achievement and motivation. International Journal of Interactive Mobile Technologies, 19(13), 33–54. https://doi.org/10.3991/ijim.v19i13.54947
Almarashdi, H. S., Jarrah, A. M., Abu Khurma, O., & Gningue, S. M. (2024). Unveiling the potential: A systematic review of ChatGPT in transforming mathematics teaching and learning. Eurasia Journal of Mathematics, Science and Technology Education, 20(12), em2555. https://doi.org/10.29333/ejmste/15739
Alvarez, J. I. (2024). Evaluating the impact of AI–powered tutors MathGPT and Flexi 2.0 in enhancing calculus learning. Jurnal Ilmiah Ilmu Terapan Universitas Jambi, 8(2), 495–508. https://doi.org/10.22437/jiituj.v8i2.34809
Awang, L. A., Yusop, F. D., & Danaee, M. (2025). Current practices and future direction of artificial intelligence in mathematics education: A systematic review. International Electronic Journal of Mathematics Education, 20(2), em0823. https://doi.org/10.29333/iejme/16006
Bawa, I., & Bawa, S. (2025). Bridging EdTech gaps: Examining learning equity in low-income educational settings. International Journal of Educational Development, 118, 103398. https://doi.org/10.1016/j.ijedudev.2025.103398
Chau, D. B., Luong, V. T., Long, T. T., & Linh, N. T. T. (2025). Personalized mathematics teaching with the support of AI chatbots to improve mathematical problem-solving competence for high school students in Vietnam. European Journal of Educational Research, 14(1), 323–333. https://doi.org/10.12973/eu-jer.14.1.323
Daher, R. (2025). Integrating AI literacy into teacher education: A critical perspective paper. Discover Artificial Intelligence, 5(1), 217. https://doi.org/10.1007/s44163-025-00475-7
del Olmo-Muñoz, J., González-Calero, J. A., Diago, P. D., Arnau, D., & Arevalillo-Herráez, M. (2022). Using intra-task flexibility on an intelligent tutoring system to promote arithmetic problem-solving proficiency. British Journal of Educational Technology, 53(6), 1976–1992. https://doi.org/10.1111/bjet.13228
Ding, L., & Wu, S. (2024). Digital transformation of education in China: A review against the backdrop of the 2024 world digital education conference. Science Insights Education Frontiers, 20(2), 3283–3299. https://doi.org/10.15354/sief.24.re340
Filippucci, F., Gal, P., Jona-Lasinio, C., Leandro, A., & Nicoletti, G. (2024). The impact of artificial intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges. (OECD Artificial Intelligence Papers No. 15). OECD Publishing. https://doi.org/10.1787/8d900037-en
Garzón, J., Patiño, E., & Marulanda, C. (2025). Systematic review of artificial intelligence in education: Trends, benefits, and challenges. Multimodal Technologies and Interaction, 9(8), 84. https://doi.org/10.3390/mti9080084
Gasparyan, A. Y., Ayvazyan, L., & Kitas, G. D. (2013). Multidisciplinary bibliographic databases. Journal of Korean Medical Science, 28(9), 1270. https://doi.org/10.3346/jkms.2013.28.9.1270
Golda, A., Mekonen, K., Pandey, A., Singh, A., Hassija, V., Chamola, V., & Sikdar, B. (2024). Privacy and security concerns in generative AI: A comprehensive survey. IEEE Access, 12, 48126–48144. https://doi.org/10.1109/ACCESS.2024.3381611
Goos, M., Carreira, S., & Namukasa, I. K. (2023). Mathematics and interdisciplinary STEM education: Recent developments and future directions. ZDM – Mathematics Education, 55(7), 1199–1217. https://doi.org/10.1007/s11858-023-01533-z
Granados-Duque, V., & García-Perdomo, H. A. (2021). Systematic review and meta-analysis: Which pitfalls to avoid during this process. International Braz J Urol, 47(5), 1037–1041. https://doi.org/10.1590/s1677-5538.ibju.2020.0746
Guan, C., Mou, J., & Jiang, Z. (2020). Artificial intelligence innovation in education: A twenty-year data-driven historical analysis. International Journal of Innovation Studies, 4(4), 134–147. https://doi.org/10.1016/j.ijis.2020.09.001
Gulz, A., Londos, L., & Haake, M. (2020). Preschoolers’ understanding of a teachable agent-based game in early mathematics as reflected in their gaze behaviors – an experimental study. International Journal of Artificial Intelligence in Education, 30(1), 38–73. https://doi.org/10.1007/s40593-020-00193-4
Huang, J., Cai, Y., Lv, Z., Huang, Y., & Zheng, X.-L. (2024a). Toward self-regulated learning: Effects of different types of data-driven feedback on pupils’ mathematics word problem-solving performance. Frontiers in Psychology, 15, 1356852. https://doi.org/10.3389/fpsyg.2024.1356852
Huang, J., Saleh, S., & Liu, Y. (2021). A review on Artificial intelligence in Education. Academic Journal of Interdisciplinary Studies, 10(3), 206. https://doi.org/10.36941/ajis-2021-0077
Huang, R., Liu, D., Kanwar, A. S., Zhan, T., Yang, J., Zhuang, R., Liu, M., Li, Z., & Adarkwah, M. A. (2024b). Global understanding of smart education in the context of digital transformation. Open Praxis, 16(4), 663–676. https://doi.org/10.55982/openpraxis.16.4.761
Just, J., & Siller, H.-S. (2022). The role of mathematics in STEM secondary classrooms: A systematic literature review. Education Sciences, 12(9), 629–647. https://doi.org/10.3390/educsci12090629
Khazanchi, R., Di Mitri, D., & Drachsler, H. (2025). The effect of AI-based systems on mathematics achievement in rural context: A quantitative study. Journal of Computer Assisted Learning, 41(1), e13098. https://doi.org/10.1111/jcal.13098
Kim, Y., & Steiner, P. (2016). Quasi-experimental designs for causal inference. Educational Psychologist, 51(3–4), 395–405. https://doi.org/10.1080/00461520.2016.1207177
Li, C., & Lyu, B. (2025). Investigating the motivational and knowledge affordances of conversational AI using induction, concretization and exemplification in math learning. British Journal of Educational Technology, 56(5), 1814–1841. https://doi.org/10.1111/bjet.13612
Lin, C.-H., Kuo, B.-C., & Chang, F. T. Y. (2025). The impact of Taiwan Adaptive Learning Platform (TALP) on self-regulated learning and mathematics achievement. Educational Psychology, 1–22. https://doi.org/10.1080/01443410.2025.2561028
Lin, W., & Jiang, P. (2025). Factors influencing college students’ generative artificial intelligence usage behavior in mathematics learning: A case from China. Behavioral Sciences, 15(3), 295–322. https://doi.org/10.3390/bs15030295
Liu, J., Sun, D., Sun, J., Wang, J., & Yu, P. L. H. (2025). Designing a generative AI enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction. Computers and Education: Artificial Intelligence, 9, 100438. https://doi.org/10.1016/j.caeai.2025.100438
Luo, J., Zheng, C., Yin, J., & Teo, H. H. (2025). Design and assessment of AI-based learning tools in higher education: A systematic review. International Journal of Educational Technology in Higher Education, 22(1), 42. https://doi.org/10.1186/s41239-025-00540-2
Merino-Campos, C. (2025). The impact of artificial intelligence on personalized learning in higher education: A systematic review. Trends in Higher Education, 4(2), 17. https://doi.org/10.3390/higheredu4020017
Mills, N. J. (2021). ALEKS constructs as predictors of high school mathematics achievement for struggling students. Heliyon, 7(6), e07345. https://doi.org/10.1016/j.heliyon.2021.e07345
Mohamed, M. Z. B., Hidayat, R., Suhaizi, N. N. B., Sabri, N. B. M., Mahmud, M. K. H. B., & Baharuddin, S. N. B. (2022). Artificial intelligence in mathematics education: A systematic literature review. International Electronic Journal of Mathematics Education, 17(3), em0694. https://doi.org/10.29333/iejme/12132
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2010). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery, 8(5), 336–341. https://doi.org/10.1016/j.ijsu.2010.02.007
Munárriz, A., & Rincón, Y. R. (2025). Mind the gap: Linking quantitative skill deficits and academic success in economics and business degrees — a systematic literature review. The International Journal of Management Education, 23(3), 101277. https://doi.org/10.1016/j.ijme.2025.101277
Nedungadi, P., Tang, K.-Y., & Raman, R. (2024). The transformative power of generative artificial intelligence for achieving the sustainable development goal of quality education. Sustainability, 16(22), 9779. https://doi.org/10.3390/su16229779
Ng, D. T. K., Su, J., Leung, J. K. L., & Chu, S. K. W. (2024). Artificial intelligence (AI) literacy education in secondary schools: A review. Interactive Learning Environments, 32(10), 6204–6224. https://doi.org/10.1080/10494820.2023.2255228
Nguyen, D. T., & Pham, Q. V. (2025). The evolving landscape of AI integration in mathematics education: A systematic review of trends (2015-2025). Eurasia Journal of Mathematics, Science and Technology Education, 21(10), em2714. https://doi.org/10.29333/ejmste/17078
Ni, Y., Zhou, D.-H. R., Cai, J., Li, X., Li, Q., & Sun, I. X. (2018). Improving cognitive and affective learning outcomes of students through mathematics instructional tasks of high cognitive demand. The Journal of Educational Research, 111(6), 704–719. https://doi.org/10.1080/00220671.2017.1402748
Opesemowo, O. A. G., & Adewuyi, H. O. (2024). A systematic review of artificial intelligence in mathematics education: The emergence of 4IR. Eurasia Journal of Mathematics, Science and Technology Education, 20(7), em2478. https://doi.org/10.29333/ejmste/14762
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, n71. https://doi.org/10.1136/bmj.n71
Pai, K.-C., Kuo, B.-C., Liao, C.-H., & Liu, Y.-M. (2021). An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning. Educational Psychology, 41(2), 137–152. https://doi.org/10.1080/01443410.2020.1731427
Pala, C. A., Lagrimas, D., & Nobis Jr., M. L. (2025). Exploration of chatbots in mathematics education for innovative learning process. Asian Journal of Advanced Research and Reports, 19(5), 178–194. https://doi.org/10.9734/ajarr/2025/v19i51010
Panqueban, D., & Huincahue, J. (2024). Inteligencia artificial en educación matemática: Una revisión sistemática. Uniciencia, 38(1), 1–17. https://doi.org/10.15359/ru.38-1.20
Qiu, Y., & Ishak, N. A. (2025). AI-assisting technology and social support in enhancing deep learning and self-efficacy among primary school students in mathematics in China. International Journal of Learning, Teaching and Educational Research, 24(2), 21–37. https://doi.org/10.26803/ijlter.24.2.2
Rahmatika, W., Mursalin, M., Saputra, E., & Fonna, M. (2025). The influence of the use of AI in mathematics learning at the high school level: A systematic literature review. Electronic Journal of Education, Social Economics and Technology, 6(2), 1068. https://doi.org/10.33122/ejeset.v6i2.1068
Sajja, R., Sermet, Y., & Demir, I. (2025). End-to-end deployment of the educational AI hub for personalized learning and engagement: A case study on environmental science education. IEEE Access, 13, 55169–55186. https://doi.org/10.1109/ACCESS.2025.3554222
Shamseer, L., Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., Stewart, L. A., & the PRISMA-P Group. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ, 349, g7647. https://doi.org/10.1136/bmj.g7647
Shih, S.-C., Chang, C.-C., Kuo, B.-C., & Huang, Y.-H. (2023). Mathematics intelligent tutoring system for learning multiplication and division of fractions based on diagnostic teaching. Education and Information Technologies, 28(7), 9189–9210. https://doi.org/10.1007/s10639-022-11553-z
Son, T. (2024). Intelligent tutoring systems in mathematics education: A systematic literature review using the substitution, augmentation, modification, redefinition model. Computers, 13(10), 270. https://doi.org/10.3390/computers13100270
Steenbergen-Hu, S., & Cooper, H. (2013). A meta-analysis of the effectiveness of intelligent tutoring systems on K–12 students’ mathematical learning. Journal of Educational Psychology, 105(4), 970–987. https://doi.org/10.1037/a0032447
Steiner, P. M., & Kim, Y. (2024). Causal research designs and analysis in education. Asia Pacific Education Review, 25(3), 555–556. https://doi.org/10.1007/s12564-024-09988-9
Thai, K.-P., Bang, H. J., & Li, L. (2022). Accelerating early math learning with research-based personalized learning games: A cluster randomized controlled trial. Journal of Research on Educational Effectiveness, 15(1), 28–51. https://doi.org/10.1080/19345747.2021.1969710
Timotheou, S., Miliou, O., Dimitriadis, Y., Sobrino, S. V., Giannoutsou, N., Cachia, R., Monés, A. M., & Ioannou, A. (2023). Impacts of digital technologies on education and factors influencing schools’ digital capacity and transformation: A literature review. Education and Information Technologies, 28(6), 6695–6726. https://doi.org/10.1007/s10639-022-11431-8
Vistorte, A. O. R., Deroncele-Acosta, A., Ayala, J. L. M., Barrasa, A., López-Granero, C., & Martí-González, M. (2024). Integrating artificial intelligence to assess emotions in learning environments: A systematic literature review. Frontiers in Psychology, 15, 1387089. https://doi.org/10.3389/fpsyg.2024.1387089
Walkington, C. (2025). The implications of generative artificial intelligence for mathematics education. School Science and Mathematics, ssm.18356. https://doi.org/10.1111/ssm.18356
Wang, J., & Fan, W. (2025). The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: Insights from a meta-analysis. Humanities and Social Sciences Communications, 12(1), 621. https://doi.org/10.1057/s41599-025-04787-y
Wang, S., Christensen, C., Cui, W., Tong, R., Yarnall, L., Shear, L., & Feng, M. (2023). When adaptive learning is effective learning: Comparison of an adaptive learning system to teacher-led instruction. Interactive Learning Environments, 31(2), 793–803. https://doi.org/10.1080/10494820.2020.1808794
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252, 124167. https://doi.org/10.1016/j.eswa.2024.124167
Waqar, Y., Rashid, S., Anis, F., & Muhammad, Y. (2024). Digital divide & inclusive education: Examining how unequal access to technology affects educational inclusivity in urban versus rural Pakistan. Journal of Social & Organizational Matters, 3(3), 1–13. https://doi.org/10.56976/jsom.v3i3.97
Xu, W., & Ouyang, F. (2022). The application of AI technologies in STEM education: A systematic review from 2011 to 2021. International Journal of STEM Education, 9(1), 59. https://doi.org/10.1186/s40594-022-00377-5
Zhao, L., Wu, X., & Luo, H. (2022). Developing AI literacy for primary and middle school teachers in China: Based on a structural equation modeling analysis. Sustainability, 14(21), 14549. https://doi.org/10.3390/su142114549
Zou, Y., Kuek, F., Feng, W., & Cheng, X. (2025). Digital learning in the 21st century: Trends, challenges, and innovations in technology integration. Frontiers in Education, 10, 1562391. https://doi.org/10.3389/feduc.2025.1562391
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Yaqian Song, Mohamed Yusoff Mohd Nor, Bity Salwana Alias
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published by IJLTER are licensed under a Creative Commons Attribution Non-Commercial No-Derivatives 4.0 International License (CCBY-NC-ND4.0).
