Sistematik Derlemeler ve Meta Analiz
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Matematik Eğitiminde Üretken Yapay Zeka Araçlarının İncelenmesi: Araç Özellikleri, Kullanım Amaçları ve Etkileri

Yıl 2025, Cilt: 11 Sayı: 2, 136 - 162, 28.08.2025

Esranur Hacioğlu Seven , Ali Kürşat Erümit

https://doi.org/10.29065/usakead.1688918

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.

Kaynakça

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

Yıl 2025, Cilt: 11 Sayı: 2, 136 - 162, 28.08.2025

Esranur Hacioğlu Seven , Ali Kürşat Erümit

https://doi.org/10.29065/usakead.1688918

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

  • Acar, O. (2020). Yapay zeka fırsat mı yoksa tehdit mi?. İstanbul: Kriter Yayınevi.
  • 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
  • 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
  • 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).
  • Arslan, K. (2020). Eğitimde yapay zeka ve uygulamaları. Batı Anadolu Eğitim Bilimleri Dergisi, 11(1), 71-88.
  • 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
  • Bulut, M. A., Davarcı, M., Bozdoğan, N. K., & Sarpkaya, Y. (2024). Yapay zekanın eğitim üzerindeki etkileri. Ulusal Eğitim Dergisi, 4(3), 976–986.
  • 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
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  • 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
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  • 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
  • Erdurmuş, M. (2023). Yapay zekanın sanat eğitiminde kullanılmasına yönelik bir uygulama örneği [Yayımlanmamış yüksek lisans tezi]. Gazi Üniversitesi.
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  • 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.
  • 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
  • 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
  • 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
  • Kara, E. (2024). 21. Yüzyıl Matematik eğitiminde yapay zeka: teknolojik dönüşümde global stratejiler. Çocuk ve Medeniyet Dergisi, 9(15), 8-43.
  • 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
  • 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
  • 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
  • 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
  • Lee, S. G., Lee, J. H., & Ham, Y. (2020). Artificial intelligence and college mathematics education. Communications of Mathematical Education, 34(1), 1-15.
  • Lingefjärd, T. (2024). Empowering mathematics education through programming. Journal of Mathematics and Science Teacher, 4(1). https://doi.org/10.29333/mathsciteacher/13847
  • Mahdalena, M. (2024). Using Wolfram Alpha for Assistance in the Learning of Linear Algebra.
  • MEB (2024). Milli Eğitim Bakanlığı öğretim programları. https://tymm.meb.gov.tr/ogretim-programlari. 20.03.2025 tarihinde erişilmiştir.
  • 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
  • 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.
  • 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.
  • 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
  • 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
  • Nabiyev, V. & Erümit, A. K. (2020), Eğitimde yapay zeka: kuramdan uygulamaya. Pegem Akademi
  • 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
  • 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.
  • 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
  • Özkan, U. B. (2019). Eğitim bilimleri araştırmaları için doküman inceleme yöntemi. Ankara: Pegem Akademi.
  • Park, M. (2020). Applications and possibilities of artificial intelligence in mathematics education. Communications of Mathematical Education, 34(4), 545–561.
  • 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.
  • 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
  • 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.
  • 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.
  • 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
  • Saragi, A. P. (2024). Systematic literature review: Pemanfaatan Aplikasi wolfarm alpha pada pembelajaran matriks. Journal of International Multidisciplinary Research, 2(5), 113-117.
  • 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.
  • 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
  • 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.
  • 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
  • Umay, A. (2003). Matematiksel muhakeme yeteneği. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 2003(24), 234-243.
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  • 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
  • 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
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  • 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
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Toplam 67 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Öğretim Teknolojileri, Matematik Eğitimi
Bölüm Makaleler
Yazarlar

Esranur Hacioğlu Seven 0009-0006-2255-2115

Ali Kürşat Erümit 0000-0003-4910-4989

Erken Görünüm Tarihi 28 Ağustos 2025
Yayımlanma Tarihi 28 Ağustos 2025
Gönderilme Tarihi 1 Mayıs 2025
Kabul Tarihi 20 Ağustos 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 11 Sayı: 2

Kaynak Göster

APA Hacioğlu Seven, E., & Erümit, A. K. (2025). Matematik Eğitiminde Üretken Yapay Zeka Araçlarının İncelenmesi: Araç Özellikleri, Kullanım Amaçları ve Etkileri. Uşak Üniversitesi Eğitim Araştırmaları Dergisi, 11(2), 136-162. https://doi.org/10.29065/usakead.1688918

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