Matematik Öğretmen Adaylarının Metaverse Bilgi Düzeylerinin Analizi: ANFIS Yaklaşımı

Abstract

Eğitim alanı teknolojik gelişmeden etkilenen ve hızla uyum sağlama gerektiren bir alandır. Metaverse de bu teknolojilerden biridir ve araştırmalarda eğitim de dahil olmak üzere, geleceğin dünyasında yaygın şekilde yerini alacağı öngörülmektedir. Ancak metaverse üzerine yapılan çalışmaların az olduğu ve yapılan çalışmaların da genellikle istatistiksel yöntemler kullanılarak analiz edildiği görülmektedir. Buradan hareketle çalışmada, Uyarlanabilir Nöro-Bulanık Çıkarım Sistemi (ANFİS) kullanarak matematik öğretmen adaylarının metaverse bilgi düzeylerini tahmin etmek ve modeller oluşturmak amaçlanmıştır. Bulanık mantık kullanımı bilim ve teknolojinin gelişmesi ile eğitim alanına da yayılmıştır. ANFIS ile sinir ağı araştırması ve bulanık mantığı birleştirerek ilgili yeteneklerden yararlanılır. Bu önemli avantaj göz önünde bulundurularak öğretmen adaylarının metaverse bilgi düzeylerini tahmin etmek için ANFIS modeli kurulmuştur. Araştırma 192 öğretmen adayının katılımı ile gerçekleşmiştir. Araştırmada veri toplama aracı olarak kişisel bilgi formu ve metaverse ölçeği kullanılmıştır. Çalışma sonucunda, öğretmen adaylarının metaverse ölçeğinden elde edilen puanları orta düzeyde çıkmış ve öğretmen adaylarının metaverse bilgi düzeylerinin gerçek ve yapay puanları birbirine oldukça yakın olarak tespit edilmiştir.

Keywords

• Metaverse
• Matematik öğretmen adayları
• Yapay zeka

Analysis of Metaverse Knowledge Levels of Prospective Mathematics: ANFIS Approach

Abstract

Education is a field that is affected by technological development and requires rapid adaptation. Metaverse is one of these technologies and it is predicted that it will take its place widely in the world of the future, including education in research. However, it is seen that there are few studies on metaverse and the studies are generally analysed using statistical methods. From this point of view, the aim of this study was to predict the metaverse knowledge levels of pre-service mathematics teachers by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and to create models. The use of fuzzy logic has spread to the field of education with the development of science and technology. ANFIS combines neural network research and fuzzy logic to utilise the relevant capabilities. Considering this important advantage, ANFIS model was established to predict the metaverse knowledge levels of pre-service teachers. The research was conducted with the participation of 192 pre-service teachers. Personal information form and metaverse scale were used as data collection tools. As a result of the study, the scores of the pre-service teachers obtained from the metaverse scale were found to be at a moderate level and the real and artificial scores of the pre-service teachers' metaverse knowledge levels were found to be quite close to each other.

Keywords

• Metaverse
• Education
• Prospective Mathematics Teachers
• Artificial intelligence

References

1. Aburbeian, A. M., Owda, A. Y., & Owda, M. (2022). A technology acceptance model survey of the metaverse prospects. AI, 3, 285–302. https://doi.org/10.3390/ai3020018
2. Akpınar, B., Kuloğlu, A., & Erdamar, F. S. (2022). Metaverse awareness of Turkish generation z preservice teachers. OPUS Journal of Society Research, 19(50), 838-852. https://doi.org/10.26466/opusjsr.1113997
3. Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A. & Habibi, A. (2023). Extending the technology acceptance model (Tam) to predict university students’ intentions to use Metaverse-Based learning platforms. Education and Information Technologies, 28, 15381–15413 https://doi.org/10.1007/s10639-023-11816-3
4. Araya, N. M. M., & Avila, R. S. H. (2018). Collaborative learning through integration of environments real and virtual-immersive. In 2018 37th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). IEEE.
5. Cemil, Ç. (2015). AHP ve Dematel Tabanlı ANFIS ile Sıcaklık Tahmininin Modellenmesi. [Yayınlanmamış Yüksek Lisans Tezi], Kocaeli Üniversitesi, Kocaeli.
6. Devy, T. K. N. (2022) What is the metaverse? Definitions, technologies and the community of inquiry, Australian Journal of Educational Technology, 38(4). https://doi.org/10.14742/ajet.7945
7. Dickey, M. D. (2005), Three-dimensional virtual worlds and distance learning: two case studies of Active Worlds as a medium for distance education. British Journal of Educational Technology, 36, 439-451. https://doi.org/10.1111/j.1467-8535.2005.00477.x
8. Gay, L. R., & Airasian, P. (2000). Educational research competencies for analysis and application (6th Edition). Ohio: Merrill an imprint of Prentice Hall.

9. Gokmen, G., Akinci, T. Ç., Tektaş, M., Onat, N., Kocyigit, G., & Tektaş, N. (2010). Evaluation of student performance in laboratory applications using fuzzy logic. Procedia-Social and Behavioral Sciences, 2(2), 902-909.
10. Hwang, G., & Chien, S. (2022) Definition, roles, and potential research issues of the metaverse in education: An artificial intelligence perspective. Computer and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100082
11. Ipsos, (2022). How the world sees the metaverse and extended reality, A 29-country Global Advisor survey. Global Version, Public, 1-12.
12. Lin, H., Wan, S., Gan, W., Chen, J., & Chao, H. C. (2022). Metaverse in education: Vision, opportunities, and challenges. arXiv (Cornell University). https://doi.org/10.48550/arXiv.2211.14951
13. Mehdi, R., & Nachouki, M. (2022). A neuro-fuzzy model for predicting and analyzing student graduation performance in computing programs. Education and Information Technologies. https:// doi. org/ 10. 1007/ s10639- 022- 11205-2
14. Mundy, M. A., Hernandez, J., & Green, M. (2019). Perceptions of the effects of augmented reality in the classroom, Journal of Instructional Pedagogies, 22, 1-15.
15. Namlı, N. A., & Şenkal, O. (2018). Using the fuzzy logic in assessing the programming performance of students. International Journal of Assessment Tools in Education, 5(4), 701-712.
16. Özdemir, A., Vural, M., Süleymanoğulları, M., & Bayraktar, G. (2022). What do university students think about the metaverse?. Journal of Educational Technology and Online Learning, 5(4), 952-962. https://doi.org/10.31681/jetol.1151470
17. Savaş, B. Ç., Karababa, B., & Turan, M. (2022). Metaverse bilgi düzeyi: beden eğitimi ve spor öğretmeni adayları üzerine bir incelenme. Uluslararası Egzersiz Psikolojisi Dergisi, 4(1), 18-29. https://doi.org/10.51538/intjourexerpsyc.1140511
18. Sebastian, G. (2022). A Study on Metaverse Awareness, Cyber Risks, and Steps for Increased Adoption. International Journal of Security and Privacy in Pervasive Computing (IJSPPC), 14(1), 1-11. http://doi.org/10.4018/IJSPPC.308785.
19. Sheehy, K., Ferguson, R., & Clough, G. (2007). Learning and Teaching in the Panopticon: Ethical and Social Issues in Creating a Virtual Educational Environment. International Journal of Human and Social Sciences 2(2), 89-96.
20. Slabeva, K. (2022). Opportunities and challenges of metaverse for education: a literature review EDULEARN22 Proceedings Pages: 10401-10410 doi: 10.21125/edulearn.2022.2527
21. Statista (2022a), Interest in the metaverse in Singapore in 2022, by age group, https://www.statista.com/statistics/1300559/singapore-interest-in-metaverse-by-age-group/ (Erişim Tarihi: 02 Aralık 2023)
22. Statista (2022b). Share of adults in the United States who have heard about the metaverse as of June 2022. https://www.statista.com/statistics/1302650/us-adults-heard-about-themetaverse-generation/ (Erişim Tarih: 20 Kasım 2023).
23. Statista (2022c). Familiarity with the metaverse according to adults in the United States as of January 2022. https://www.statista.com/statistics/1290378/unites-states-adults-familiarity-with-the-metaverse.
24. Süleymanoğulları, M., Özdemir, A., Bayraktar, G., & Vural, M. (2022). Metaverse scale: Study of validity and reliability. Anatolia Sport Research, 3(1), 47-58. http://dx.doi.org/10.17984/adyuebd.495731
25. Talan, T., & Kalınkara, Y. (2022). Students' opinions about the educational use of the metaverse. International Journal of Technology in Education and Science (IJTES), 6(2), 333-346. https://doi.org/10.46328/ijtes.385
26. Taş, M. (2022). Düşük hızlı bir kanat modelinin Anfis ile modellenmesi ve tahmin edilmesi. [Yayınlanmamış Yüksek Lisans Tezi] Erciyes Üniversitesi, Erciyes.
27. Tlili, A.i, Huang R…. (2022). Is Metaverse in education a blessing or a curse: a combined content andbibliometric analysis. Smart Learning Environment 9(24).
28. Turan, M., Mavibaş, M., Savaş, B. Ç., & Çetin, H. (2023). Beden eğitimi öğretmenlerinin metaverse bilgi düzeylerinin çeşitli değişkenlere göre incelenmesi. The Online Journal of Recreation and Sports, 12(1), 25-42. https://doi.org/10.22282/tojras.1201104
29. Uygur, M., Yelken, T. Y., & Akay, C. (2018). Analyzing the views of pre-service teachers on the use of augmented reality applications in education. European Journal of Educational Research, 7(4), 849-860. doi: 10.12973/eu-jer.7.4.849
30. Venugopal, J. P., Vijay Subramanian, A. A., & Peatchimuthu, J. (2023). The realm of metaverse: A survey Comp Anim Virtual Worlds, 34(5). https://doi.org/10.1002/cav.2150
31. Yücel, A. (2010). Tedarikçi Seçimi Probleminde Bütünleşik Sinirsel Bulanık Mantık Yaklaşımı. [Doktora Tezi] Yıldız Teknik Üniversitesi, İstanbul.
32. Wiangkham, A. & Vongvit, R. (2023). Exploring the drivers fort he adoption of metaverse technology in engeineering education using PLS-SEM and ANFIS. Education and Information Technologies. doi.org/10.1007/s10639-023-12127-3
33. Wu, J., & Gao, G. (2022) Edu-Metaverse: Internet Education Form with Fusion of Virtual and Reality. Advances in Social Science, Education and Humanities Research, volume 664 Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)