Matematik Eğitiminde Üretken Yapay Zeka Araçlarının İncelenmesi: Araç Özellikleri, Kullanım Amaçları ve Etkileri

Öz

Bu çalışmanın amacı, matematik eğitiminde üretken yapay zeka araçlarının kullanımını incelemek ve bu araçların potansiyel faydalarını değerlendirmektir. Araştırmada, doküman incelemesi yöntemi kullanılarak literatür taraması yapılmış, belirlenen anahtar kelimeler doğrultusunda Google Akademik, Web of Science ve Scopus veri tabanlarında yapılan aramalarla belirlenen çalışmalar detaylı şekilde analiz edilmiştir. Çalışmada, üretken yapay zeka araçları soru türü, eğitim düzeyi, açıklamalı anlatım, grafik oluşturma, görsel yükleyebilme, cihaz desteği, Türkçe dil desteği ve adım adım açıklamalı anlatım olmak üzere sekiz tema altında değerlendirilmiştir. Ayrıca 13 farklı üretken yapay zeka araçları tek tek ele alınarak özellikleri açıklanmıştır. Bulgular, ChatGPT, Mathway, GeoGebra ve Photomath gibi araçların, öğrencilerin matematiksel kavramları anlamalarını kolaylaştırdığı, görselleştirme ve simülasyonlarla öğrenme sürecini zenginleştirdiğini göstermiştir. Özellikle cebir ve geometri gibi zorlu konularda bu araçların öğrenci motivasyonunu ve başarısını artırdığı belirlenmiştir. Araştırmada, yapay zeka araçlarının etkin kullanımını sağlamak için öğretmenlerin pedagojik ve dijital becerilerinin geliştirilmesi gerektiği, ayrıca kullanıcı rehberliği ve etik kaygıların dikkate alınmasının önemi vurgulanmıştır.

Anahtar Kelimeler

• Üretken yapay zeka
• matematik eğitimi
• doküman incelemesi

Etik Beyan

Etik kurul raporu gerekmemektedir.

An Examination of Generative Artificial Intelligence Tools in Mathematics Education: Tool Features, Purposes of Use, and Impacts

Öz

The purpose of this study is to explore the use of generative artificial intelligence tools in mathematics education and evaluate their potential benefits. The research employed the document analysis method, conducting a literature review by searching for specified keywords in Google Scholar, Web of Science, and Scopus databases. The studies identified were analyzed in detail and evaluated under eight themes: question type, education level, explanatory descriptions, graph creation, visual uploading, device support, Turkish language support, and step-by-step explanatory narration. Additionally, 13 different generative artificial intelligence tools were examined individually, and their features were explained in detail. The findings revealed that tools such as ChatGPT, Mathway, GeoGebra, and Photomath facilitate students' understanding of mathematical concepts, enriching the learning process through visualization and simulations. These tools were found to increase student motivation and success, particularly in challenging topics like algebra and geometry. The study emphasized the necessity of enhancing teachers' pedagogical and digital skills to ensure the effective use of AI tools. Additionally, the importance of user guidance and addressing ethical concerns was highlighted.

Anahtar Kelimeler

• Generative artificial intelligence
• mathematics education
• document analysis.

Etik Beyan

An ethics committee report is not required.

Kaynakça

1. Acar, O. (2020). Yapay zeka fırsat mı yoksa tehdit mi?. İstanbul: Kriter Yayınevi.
2. Akdeniz, M., & Özdinç, F. (2021). Eğitimde yapay zeka konusunda Türkiye adresli çalışmaların incelenmesi. Van Yüzüncü Yıl Üniversitesi Eğitim Fakültesi Dergisi, 18(1), 912-932. https://doi.org/10.33711/yyuefd.938734
3. Alcalde, A. L. D., Catulong, D. R. P., Cabangbang, A. M. B., Catulong, K. M. A., & Miranda, A. C. (2024). Guided Symbolab Application (GSA): Intervention strategy in addressing the low-performing BSED math students in the LET enhancement assessment. Psychology and Education: A Multidisciplinary Journal, 17(5), 495-505. http://doi.org/10.5281/zenodo.10701345
4. Anh, N. N. P., & Ngan, H. T. (2021). Artificial intelligence in mathematics education: An empirical study of using chatbot in teaching and learning mathematics at Vietnamese high schools. In 5th ASIA PACIFIC International Modern Sciences Congress (pp. 306-317).
5. Arslan, K. (2020). Eğitimde yapay zeka ve uygulamaları. Batı Anadolu Eğitim Bilimleri Dergisi, 11(1), 71-88.
6. Baker, R. S. J. d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1), 3-17. https://doi.org/10.5281/zenodo.3554657
7. Bulut, M. A., Davarcı, M., Bozdoğan, N. K., & Sarpkaya, Y. (2024). Yapay zekanın eğitim üzerindeki etkileri. Ulusal Eğitim Dergisi, 4(3), 976–986.
8. Cabugwason, M. R., Galoy, R. M. P., Laoreno, B. G., Nobis Jr, M., & Valila, A. J. (2024). Math apps in math education: Experiences and challenges of pre-service teachers. Ignatian International Journal for Multidisciplinary Research, 2(5), 1909-1922. https://doi.org/10.5281/zenodo.11235604

9. Chen, L., Chen, P. ve Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
10. Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
11. Chiu, T. K., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118
12. Chytas, C., van Borkulo, S. P., Drijvers, P., Barendsen, E., & Tolboom, J. L. (2024). Computational thinking in secondary mathematics education with GeoGebra: Insights from an intervention in calculus lessons. Digital Experiences in Mathematics Education, 1-32. https://doi.org/10.1007/s40751-024-00141-0
13. Çetan, K., & Preethi, K. P. (2024). Yapay zeka tabanlı çok dilli chatbot: Kırsal topluluklarda yüksek öğrenimin geliştirilmesi. Uluslararası Mühendislik ve Yönetim Bilimsel Araştırma Dergisi (IJSREM), 8(7), 1-5. https://doi.org/10.55041/IJSREM36726
14. Dabingaya, M. (2022). Analyzing the effectiveness of AI-powered adaptive learning platforms in mathematics education. Interdisciplinary Journal Papier Human Review, 3(1), 1-7. https://doi.org/10.47667/ijphr.v3i1.226
15. Dahal, N., Luitel, B. C., & Pant, B. P. (2024). Exploring capabilities and limitations of generative AI chatbots in solving math algorithm problems. In The 15th International Congress on Mathematical Education (pp. 1-4).
16. Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. M. (2019). Hybrid intelligence. Business & Information Systems Engineering, 61, 637–643. https://doi.org/10.1007/s12599-019-00595-2
17. Demircioğlu, E., Yazıcı, C., & Demir, B. (2024). Yapay zeka 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
18. Dhivya, M. L., & Ramakrishnan, N. (2024). The extent of mobile application usage for learning mathematics among higher secondary students. Educational Administration: Theory and Practice, 30(5), 6272-6278. https://doi.org/10.53555/kuey.v30i5.3930
19. du Boulay, B. (2023). Artificial intelligence in education and ethics. In Handbook of open, distance and digital education (pp. 93-108). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-2080-6_6
20. Efendi, M. A., Panglipur, I. R., & Murtinasari, F. (2024). Identifying the use of artificial intelligence in math learning based on learning outcomes. At-Ta'lim Jurnal Pendidikan, 10(2), 53-59. https://doi.org/10.55210/attalim.v10i2.1689
21. Erdurmuş, M. (2023). Yapay zekanın sanat eğitiminde kullanılmasına yönelik bir uygulama örneği [Yayımlanmamış yüksek lisans tezi]. Gazi Üniversitesi.
22. Erümit, A. K., Calap, T., Çolak, A. F., Yavuz, S., & Aydın, E. (2020). Okullarda yapay zeka öğretimi. V. Nabiyev & A. K. Erümit (Ed.), Eğitimde yapay zeka: kuramdan uygulamaya. Pegem Akademi.
23. Güzey, C., Çakır, O., Athar, M. H., & Yurdaöz, E. (2023). Eğitimde yapay zeka üzerine gerçekleştirilmiş araştırmalardaki eğilimlerin incelenmesi. Bilgi ve İletişim Teknolojileri Dergisi, 5(1), 67-78. https://doi.org/10.53694/bited.1060730
24. Harper, F., Stumbo, Z., & Kim, N. (2021). When Robots invade the neighborhood: Learning to teach prek-5 mathematics leveraging both technology and community knowledge. Contemporary Issues in Technology and Teacher Education, 21(1), 19-52.
25. Hu, Y., Li, Q., & Hsu, S. W. (2022). Interactive visual computer vision analysis based on artificial intelligence technology in intelligent education. Neural Computing and Applications, 34(12), 9315-9333. https://doi.org/10.1007/s00521-021-06285-z
26. Hwang, G. J., & Tu, Y. F. (2021). Roles and research trends of artificial intelligence in mathematics education: A bibliometric mapping analysis and Systematic Review. Mathematics, 9 (6), 584. https://doi.org/10.3390/math9060584
27. Jarrah, A. M., Wardat, Y., Fidalgo, P., & Ali, N. (2025). Gamifying mathematics education through Kahoot: Fostering motivation and achievement in the classroom. Research and Practice in Technology Enhanced Learning, 20(10). https://doi.org/10.58459/rptel.2025.20010
28. Kara, E. (2024). 21. Yüzyıl Matematik eğitiminde yapay zeka: teknolojik dönüşümde global stratejiler. Çocuk ve Medeniyet Dergisi, 9(15), 8-43.
29. Karabıyık, Ü. (2024). Matematik eğitiminde yenilikçi bir yaklaşım: ChatGPT’nin rolü. Uşak Üniversitesi Eğitim Araştırmaları Dergisi, 10(1), 26–46. https://doi.org/10.29065/usakead.1393487
30. Kim, K. J., & Han, H. J. (2021). A design and effect of maker education using educational artificial intelligence tools in elementary online environment. Journal of Digital Convergence, 19(6), 61-71. https://doi.org/10.14400/JDC.2021.19.6.061
31. Kuchkarova, A. (2024). Harnessıng technology: geogebra and ıts ınfluence on hıgh school mathematıcs learnıng outcomes. Science and innovation, 3(A7), 95-98. https://doi.org/10.5281/zenodo.13141604
32. Kwon, O. N., Lee, K., Oh, S. J. & Park, J. S. (2021). An analysis of “Related Learning Elements” reflected in artificial ıntelligence mathematics textbooks. Communications of Mathematical Education, 35(4), 445–473. https://doi.org/10.7468/jksmee.2021.35.4.445
33. Lee, S. G., Lee, J. H., & Ham, Y. (2020). Artificial intelligence and college mathematics education. Communications of Mathematical Education, 34(1), 1-15.
34. Lingefjärd, T. (2024). Empowering mathematics education through programming. Journal of Mathematics and Science Teacher, 4(1). https://doi.org/10.29333/mathsciteacher/13847
35. Mahdalena, M. (2024). Using Wolfram Alpha for Assistance in the Learning of Linear Algebra.
36. MEB (2024). Milli Eğitim Bakanlığı öğretim programları. https://tymm.meb.gov.tr/ogretim-programlari. 20.03.2025 tarihinde erişilmiştir.
37. McCarthy, J. (2007). From here to human-level AI. Artificial Intelligence, 171(18), 1174-1182. https://doi.org/10.1016/j.artint.2007.10.009
38. McKenzie, A., Lochead, K., Weaver, K. D., Byl, L., Bermingham, C., Piatek, J., Holmes, T., & Anderson, S. (2024). Generative artificial intelligence (GenAI) overview. University of Waterloo Associate Vice-President, Academic Standing Committee on New Technologies, Pedagogies, and Academic Integrity.
39. Mohamed, M. A., Said, A. A., Hassan, H., El Sayed, M. M., Abdelhamid, M. G., Shehata, M. S., ... & Ali, Y. M. (2024). Applications of artificial intelligence in teaching mathematics for the second preparation year in Egyptian official language schools. Ain Shams University, Faculty of Education, Bachelor of Science and Education Mathematics, 1, 77-94.
40. 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), https://doi.org/10.29333/iejme/12132
41. Mosher, M. A., Dieker, L. A., & Hines, R. (2024). The past, present and future use of artificial intelligence in teacher Education. Journal of Special Education Preparation, 4(2), 6-17. https://doi.org/10.33043/8aa9855b
42. Nabiyev, V. & Erümit, A. K. (2020), Eğitimde yapay zeka: kuramdan uygulamaya. Pegem Akademi
43. Nayıroğlu, B., & Tutak, T. (2024). Matematik öğretiminde yapay zekanın rolü: eğitimde kullanılan araçların incelenmesi. Turkish Journal of Educational Studies, 11(1), 65-78. https://doi.org/10.33907/turkjes.1415591
44. Nurlaelah, E., Sudihartinih, E., & Putri, D. N. (2024). Application of artificial intelligence photomath in learning mathematics. In International Conference on Learning Community, 1(1), 548-556.
45. 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
46. Özkan, U. B. (2019). Eğitim bilimleri araştırmaları için doküman inceleme yöntemi. Ankara: Pegem Akademi.
47. Park, M. (2020). Applications and possibilities of artificial intelligence in mathematics education. Communications of Mathematical Education, 34(4), 545–561.
48. Paulin, M., & Ndagijimana, J. B. (2024). Effectiveness of the symbolab calculator in improving second year science and mathematics students ability to solve trigonometric equations. East African Journal of Education and Social Sciences, 4(6), 10-46606.
49. Pamungkas, R. G., Wardono, W., & Agoestanto, A. (2024). Mathematical Literacy and curiosity through creative problem solving learning using the PMRI Approach Assisted by Photomath. Didactical Mathematics, 6(2), 304-313. https://doi.org/10.31949/dm.v6i2.10822
50. Rahayu, A. M., Badruzzaman, F. H., & Harahap, E. (2021).Pembelajaran aljabar melalui aplikasi wolfram alpha. Matematika: Jurnal Teori dan Terapan Matematika, 20(1), 51-58.
51. Rizos, I., Foykas, E., & Georgakopoulos, S. (2024). Enhancing mathematics education for students with special educational needs through generative AI: A case study in Greece. Contemporary Educational Technology. https://doi.org/10.30935/cedtech/15487.
52. Salas-Pilco, S. Z., & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: a systematic review. International Journal of Educational Technology in Higher Education, 19(21). https://doi.org/10.1186/s41239-022-00326-w
53. Saragi, A. P. (2024). Systematic literature review: Pemanfaatan Aplikasi wolfarm alpha pada pembelajaran matriks. Journal of International Multidisciplinary Research, 2(5), 113-117.
54. Shin, B., Ryu, K., Kim, K., Kang, S., & Joo, J. (2024). A study on exploring strategies for developing digital literacy using generative AI: Focusing on the development of mathematics teaching and learning materials based on ChatGPT. Korean School Mathematics Society. https://doi.org/10.30807/ksms.2024.27.2.003.
55. Siswanto, D. H., Tanikawa, K., Alghiffari, E. K., Limori, M., & Aprilia, D. D. (2024). A Systematic Review: Use of GeoGebra in Mathematics Learning at Junior High School in Indonesia and Japan. Jurnal Pendidikan Matematika (Kudus), 7(1), 1-20. http://dx.doi.org/10.21043/jpmk.v7i1.26201
56. Taktak, M. (2024). Transformation of the teaching profession in Turkey with ChatGPT: Opportunities and challenges. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 25(3), 1595-1613.
57. Tokay, I., Agar, S., & Elmas, M. (2024). The significance of artificial ıntelligence in university education system and course syllabuses. Creative Education, 15(5), 739-749. https://doi.org/10.4236/ce.2024.155045
58. Umay, A. (2003). Matematiksel muhakeme yeteneği. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 2003(24), 234-243.
59. Voskoglou, M. G., & Salem, A.-B. M. (2020). Benefits and limitations of the artificial with respect to the traditional learning of mathematics. Mathematics, 8(4), 611. https://doi.org/10.3390/math8040611
60. Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential ımpact of artificial ıntelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences-Basel, 13(11), 6716. https://doi.org/10.3390/app13116716
61. Wongthan, J., (2024). Development of learning activities using Polya's problem-solving process ıntegrated with artificial intelligence applications to enhance mathematical problem-solving ability on the topic of systems of linear equations in two variables for grade 9 students. Independent Study Report. Graduate School, Naresuan University, Mathematics Education Program.
62. Woolf, B. P. (2009). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. San Francisco, CA: Morgan Kaufmann
63. Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., Liu, X., Wu, Y., Dong, F., Qiu, C. W., Qiu, J., Hua, K., Su, W., Wu, J., Xu, H., Han, Y., Fu, C., Yin, Z., Liu, M., ... Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. In Innovation, 2(4). Cell Press. https://doi.org/10.1016/j.xinn.2021.100179
64. Yeşilyurt, S., Dündar, R. & Aydın, M. (2024). Sosyal bilgiler eğitimi alanında lisansüstü eğitimini sürdüren öğrencilerin yapay zeka hakkındaki görüşleri. Asya Studies, 8(27), 1-14. https://doi.org/10.31455/asya.1406649
65. Yılmaz, A. (2023). Fen bilimleri eğitiminde dijital uygulamalar, yapay zeka ve akıllı yazılımlar: Tehditler ve fırsatlar. Matematik ve Fen Bilimleri Üzerine Araştırmalar-II (1-20). Gaziantep: Özgür Yayınları.
66. Yu, H., & Guo, Y. (2023). Generative artificial intelligence empowers educational reform: current status, issues, and prospects. Frontiers in Education, 8, 1183162. Frontiers Media SA. https://doi.org/10.3389/feduc.2023.1183162
67. Zain, I. N. M., Setambah, M. A. B., Othman, M. S., & Hanapi, M. H. M. (2023). Use of photomath applications in helping ımproving students’ mathematical (algebra) achievement. European Journal of Education and Pedagogy, 4(2), 85–87. https://doi.org/10.24018/ejedu.2023.4.2.601