Artificial Intelligence in Education from the Perspective of Students: The Example of Mathematics Classes

Zeynep Çavuş Erdem

doi:10.53850/joltida.1766039

Artificial Intelligence in Education from the Perspective of Students: The Example of Mathematics Classes

Abstract

This study examines middle school students' opinions about the application of artificial intelligence in mathematics classes. The study was conducted with 206 middle school students. The students received an education that included artificial intelligence. Artificial intelligence in education was introduced in general terms, and its applications in mathematics education were demonstrated. Additionally, they were taught how ChatGPT could be used in a mathematics class in relation to types of feedback. Afterwards, a five-question, open-ended survey was administered to collect the students' opinions. The obtained data were analyzed using descriptive statistics and content analysis methods. According to the results, students found the educational role of AI sufficient and believed that it could not replace a teacher. Some students believe that all information produced by artificial intelligence is correct. Students who prefer ChatGPT for task and process feedback have mixed views about it, as well as some concerns. The results provide insights into the opportunities and limitations of ChatGPT from the students' perspective.

Keywords

Ethical Statement

Ethics and Consent: Ethical approval for this study was obtained from the Social and Human Sciences Ethics Committee (24/12/2024, E-76244175-050.04-398289).

References

Antonenko, P., & Abramowitz, B. (2022). In-service teachers’ (mis)conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64–78. https://doi.org/10.1080/15391523.2022.2119450
Arıkan, R. (2018). Anket yöntemi üzerinde bir değerlendirme. Haliç Üniversitesi Sosyal Bilimler Dergisi, 1(1), 97–159.
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
Bewersdorff, A., Zhai, X., Roberts, J., & Nerdel, C. (2023). Myths, mis-and preconceptions of artificial intelligence: A review of the literature. Computers and Education: Artificial Intelligence, 4, 100143. https://doi.org/10.1016/j.caeai.2023.100143
Biswas, S. (2023). ChatGPT and the future of medical writing. Radiology, 307(2), e223312. https://doi.org/10.1148/radiol.223312
Berry, J. H. (2025). Reactive AI feedback Improves task performance over time. Cognitive Systems Research, 101361. https://doi.org/10.1016/j.cogsys.2025.101361
Bulut, O., & Wongvorachan, T. (2022). Feedback generation through artificial intelligence. In The Open/Technology in education, society, and scholarship association conference (Vol. 2, No. 1, pp. 1-9). https://doi.org/10.18357/otessac.2022.2.1.125
Büyüköztürk, Ş., Kılıç Çakmak, E., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2016). Bilimsel araştırma yöntemleri (22. baskı). Pegem Akademi Yayınları.

Cave, S., Craig, C., Dihal, K., Dillon, S., Montgomery, J., Singler, B., & Taylor, L. (2018). Portrayals and perceptions of AI and why they matter. The Royal Society.
Chan, C. K. Y., & Tsi, L. H. (2023). The AI revolution in education: Will AI replace or assist teachers in higher education? arXiv Preprint, arXiv:2305.01185. https://doi.org/10.48550/arXiv.2305.01185
Cengiz, S., & Peker, A. (2025). Generative artificial intelligence acceptance and artificial intelligence anxiety among university students: The sequential mediating role of attitudes toward artificial intelligence and literacy. Current Psychology, 1–10. https://doi.org/10.1007/s12144-025-07433-7
Chang, L. H., & Ginter, F. (2024). Automatic short answer grading for finnish with chatgpt. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 21, pp. 23173-23181). https://doi.org/10.1609/aaai.v38i21.30363
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Creswell J. W. & Plano Clark V. L. (2018). Designing and conducting mixed methods research (3rd ed.).Sage. Çetin, M., & Aktaş, A. (2021). Yapay zeka ve eğitimde gelecek senaryoları. OPUS International Journal of Society Researches, 18(Eğitim Bilimleri Özel Sayısı), 4225–4268. https://doi.org/10.26466/opus.911444
Daher, W., & Gierdien, F. (2024). Use of language by generative AI tools in mathematical problem solving: The case of ChatGPT. African Journal of Research in Mathematics, Science and Technology Education, 28(2), 222–235. https://doi.org/10.1080/18117295.2024.2384676
Dasari, D., Hendriyanto, A., Sahara, S., Suryadi, D., Muhaimin, L. H., Chao, T., & Fitriana, L. (2023). ChatGPT in didactical tetrahedron, does it make an exception? A case study in mathematics teaching and learning. Frontiers in Education, 8, 1–15. https://doi.org/10.3389/feduc.2023.1295413
Demircioğlu, E., & Demir, B. (2024). Yapay zekâ destekli matematik eğitimi: Bir içerik analizi. International Journal of Social and Humanities Sciences Research (JSHSR), 11(106), 771–785. https://doi.org/10.5281/zenodo.11109449
Egara, F. O., Mosimege, M., & Mosia, M. (2025). Secondary school students' perceptions of their usage of artificial intelligence-based ChatGPT in mathematics learning. Journal of Education (University of KwaZulu-Natal), (98), 124–146. https://doi.org/10.17159/2520-9868/i98a07
Engelbrecht, J., Oates, G., & de Carvalho Borba, M. (2025). Artificial intelligence and social media in mathematics education. In Social media in the changing mathematics classroom (pp. 43–65). Springer Nature Switzerland.
Eren, E., Ayata, N., Çetinkaya, N. B., Yardimci, T., Kıç, A., & Akpınar, E. N. (2025). Eğitimde yapay zekâ kullanımı: Öğretmenlerin perspektifinden bir değerlendirme. Toplum, Eğitim ve Kültür Araştırmaları Dergisi, 4(1), 23–38. https://doi.org/10.5281/zenodo.15460358
Frieder, S., Pinchetti, L., Griffiths, R. R., Salvatori, T., Lukasiewicz, T., Petersen, P., & Berner, J. (2024). Mathematical capabilities of ChatGPT. Advances in Neural Information Processing Systems, 36. arXiv:2301.13867. https://ghosts.friederrr.org
Foddy, W. (1993). Constructing questions for interviews and questionnaires: Theory and practice in social research. Cambridge University Press.
Gerlich, M. (2023). Perceptions and acceptance of artificial intelligence: A multi-dimensional study. Social Sciences, 12(9), 502. https://doi.org/10.3390/socsci12090502
Getenet, S. (2024). Pre-service teachers and ChatGPT in multistrategy problem-solving: Implications for mathematics teaching in primary schools. International Electronic Journal of Mathematics Education, 19(1), em0766. https://doi.org/10.29333/iejme/14141
Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In Handbook of qualitative research (Vol. 2, pp. 105–163).
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
Heeg, D. M., & Avraamidou, L. (2025). Young children’s understanding of AI. Education and Information Technologies, 30(8), 10207-10230. https://doi.org/10.1007/s10639-024-13169-x
Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial intelligence for assessment and feedback to enhance student success in higher education. Mathematical Problems in Engineering, 2022(1), 5215722. https://doi.org/10.1155/2022/5215722
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and İndividual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Khor, E. T., Chan, L., Koh, E., & Seow, P. (2025). Exploring students’ perceptions of generative AI-generated feedback in learning programming. Educational Psychology, 1-33. https://doi.org/10.1080/01443410.2025.2564894
Kim, K., Kwon, K., Ottenbreit-Leftwich, A., Bae, H., & Glazewski, K. (2023). Exploring middle school students’ common naive conceptions of artificial intelligence concepts, and the evolution of these ideas. Education and Information Technologies, 28(8), 9827–9854. https://doi.org/10.1007/s10639-023-11600-3
Kolchenko, V. (2018). Can modern AI replace teachers? Not so fast! Artificial intelligence and adaptive learning: Personalized education in the AI age. HAPS Educator, 22(3), 249–252. https://doi.org/10.21692/haps.2018.032
Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
Li, M. (2025). Integrating artificial intelligence in primary mathematics education: Investigating internal and external influences on teacher adoption. International Journal of Science and Mathematics Education, 23(5), 1283–1308. https://doi.org/10.1007/s10763-024-10515-w
Lipnevich, A. A., & Smith, J. K. (2009). Effects of differential feedback on students’ examination performance. Journal of Experimental Psychology: Applied, 15(4), 319.
Lipsch-Wijnen, I., & Dirkx, K. (2022). A case study of the use of the Hattie and Timperley feedback model on written feedback in thesis examination in higher education. Cogent Education, 9(1). https://doi.org/10.1080/2331186X.2022.2082089
Marrone, R., Taddeo, V., & Hill, G. (2022). Creativity and artificial intelligence—A student perspective. Journal of Intelligence, 10(3), 65. https://doi.org/10.3390/jintelligence10030065
Mandouit, L., & Hattie, J. (2023). Revisiting “The Power of Feedback” from the perspective of the learner. Learning and Instruction, 84, 101718. https://doi.org/10.1016/j.learninstruc.2022.101718
Mertala, P., Fagerlund, J., & Calderon, O. (2022). Finnish 5th and 6th grade students' pre-instructional conceptions of artificial intelligence (AI) and their implications for AI literacy education. Computers and Education: Artificial Intelligence, 3, 100095. https://doi.org/10.1016/j.caeai.2022.100095
Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook. (3rd ed.). Sage.
Opara, E., Mfon-Ette Theresa, A., & Aduke, T. C. (2023). ChatGPT for Teaching, Learning and Research: Prospects and Challenges. Glob Acad J Humanit Soc Sci; 5(2), pp- 33-40. https://ssrn.com/abstract=4375470
Opesemowo, O. A. G. (2025). Artificial intelligence in mathematics education: The pros and cons. In Encyclopedia of Information Science and Technology, Sixth Edition (pp. 1–18). IGI Global.
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020
Papert, S. (1973). Use of technology to enhance education (AI memo no. 298). MIT.
Patero, J. L. (2023). Revolutionizing math education: Harnessing ChatGPT for student success. Mathematics Education, 3(1), 807–813. https://doi.org/10.48175/ijarsct-12375
Rodrigues, L., Guerino, G., Silva, T. E., Challco, G. C., Oliveira, L., da Penha, R. S., … & Isotani, S. (2025). MathAide: A qualitative study of teachers’ perceptions of an ITS unplugged for underserved regions. International Journal of Artificial Intelligence in Education, 35(1), 2–30. https://doi.org/10.1007/s40593-024-00397-y
Rudolph, J., Tan, S., & Aspland, T. (2023). Editorial 6 (2): Personal digital assistant or job killer? Generative AI and the teaching profession in higher education. Journal of Applied Learning and Teaching, 6(2), 07–16. https://doi.org/10.37074/jalt.2023.6.2.1
Rycroft-Smith, L., Müller, D., Chiodo, M., & Macey, D. (2024). A useful ethics framework for mathematics teachers. In Ethics and Mathematics Education: The Good, the Bad and the Ugly (pp. 359–394). Springer Nature Switzerland.
Sailer, M., Bauer, E., Hofmann, R., Kiesewetter, J., Glas, J., Gurevych, I., & Fischer, F. (2023). Adaptive feedback from artificial neural networks facilitates pre-service teachers’ diagnostic reasoning in simulation-based learning. Learning and Instruction, 83, 101620. https://doi.org/10.1016/j.learninstruc.2022.101620
Sidoti, C., Mitchell, A., & Gottfried, J. (2023, November 7). Teens, social media and technology 2023. Pew Research Center. https://www.pewresearch.org/internet/2023/11/07/teens-social-media-and-technology-2023/
Song, Y., Kim, J., Liu, Z., Li, C., & Xing, W. (2025). Students’ perceived roles, opportunities, and challenges of a generative AI-powered teachable agent: A case of a middle school math class. Journal of Research on Technology in Education, 1–19. https://doi.org/10.1080/15391523.2024.2447727
Stöhr, C., Ou, A. W., & Malmström, H. (2024). Perceptions and usage of AI chatbots among students in higher education across genders, academic levels and fields of study. Computers and Education: Artificial Intelligence, 7, 100259. https://doi.org/10.1016/j.caeai.2024.100259
Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019). Envisioning AI for K-12: What should every child know about AI? [Paper presentation]. The AAAI Conference on Artificial Intelligence, 33(1), 9795–9799. https://doi.org/10.1609/aaai.v33i01.33019795
Urhan, S., Gençaslan, O., & Dost, Ş. (2024). An argumentation experience regarding concepts of calculus with ChatGPT. Interactive Learning Environments, 1–26. https://doi.org/10.1080/10494820.2024.2308093
Ünal, D., Erdem, Z. Ç., & Şahin, Z. G. (2025). Will artificial intelligence succeed in passing this test? Creating an achievement test utilizing ChatGPT. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13461-4
Velander, J., Ahmed Taiye, M., Otero, N., Milrad, M., & Zijlema, A. (2023). Reflections on methods for eliciting teachers’ understanding, attitudes and emotions about AI. In International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning (pp. 124–135). Springer Nature Switzerland.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Weber, F., Wambsganss, T., & Söllner, M. (2024). Enhancing legal writing skills: The impact of formative feedback in a hybrid intelligence learning environment. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13529
Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 487662. https://doi.org/10.3389/fpsyg.2019.03087
Yıldırım, A., & Şimşek, H. (2016). Sosyal Bilimlerde Nitel Araştırma Yöntemleri, Seçkin Yayıncılık, (11th ed.).Seçkin Yayıncılık.
Yi, L., Liu, D., Jiang, T., & Xian, Y. (2025). The effectiveness of AI on K-12 students’ mathematics learning: A systematic review and meta-analysis. International Journal of Science and Mathematics Education, 23(4), 1105–1126. https://doi.org/10.1007/s10763-024-10499-7
Yildiz Durak, H., & Onan, A. (2025). A systematic review of AI-based feedback in educational settings. Journal of Computational Social Science, 8(4), 96. https://doi.org/10.1007/s42001-025-00428-1
Yoon, H., Hwang, J., Lee, K., Roh, K. H., & Kwon, O. N. (2024). Students’ use of generative artificial intelligence for proving mathematical statements. ZDM–Mathematics Education, 1-21. https://doi.org/10.1007/s11858-024-01629-0

Details

Primary Language

English

Subjects

Artificial Intelligence (Other)

Journal Section

Research Article

Authors

Zeynep Çavuş Erdem ^*
0000-0002-7448-2722
Türkiye

Publication Date

January 14, 2026

Submission Date

August 15, 2025

Acceptance Date

November 28, 2025

Published in Issue

Year 2026 Number: 1

DOI

https://doi.org/10.53850/joltida.1766039

IZ

https://izlik.org/JA33MZ78JS

Cite

RIS / Bibtex

APA

Çavuş Erdem, Z. (2026). Artificial Intelligence in Education from the Perspective of Students: The Example of Mathematics Classes. Journal of Learning and Teaching in Digital Age, 1, 134-143. https://doi.org/10.53850/joltida.1766039