Araştırma Makalesi
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Investigation of Artificial Inteligence Awareness Among Pre-Service Teachers With Cluster Analysis

Yıl 2025, Cilt: 21 Sayı: 1, 280 - 294, 22.04.2025

Erman Uzun

https://doi.org/10.17860/mersinefd.1583282

Öz

This study investigates the patterns of artificial intelligence (AI) awareness among pre-service teachers at Mersin University, using both descriptive and inferential analyses to examine the levels of knowledge and attitudes towards AI. Understanding educators' AI awareness is essential as AI is increasingly integrated into education. A sample of 117 pre-service teachers completed the Artificial Intelligence Awareness Scale for Teachers, measuring Practical Knowledge, Beliefs and Attitudes, Attitude to Association, and Theoretical Knowledge. Statistical analysis were conducted to assess differences in AI awareness across demographic variables, including gender, academic department, and technology use. In addition, cluster analysis was performed, revealing three distinct clusters: (1) a moderate-awareness cluster, characterized by average levels of AI knowledge and attitudes across all dimensions; (2) a low-awareness cluster, characterized by limited AI knowledge and neutral-to-negative attitudes; and (3) a high-awareness cluster, characterized by strong AI knowledge and positive attitudes toward artificial intelligence. The findings that technology usage significantly influences pre-service teachers' AI awareness levels, whereas demographic factors such as gender and academic department do not. The results emphasize the need for differentiated AI training within teacher preparation programs, suggesting foundational AI literacy training for lower-awareness groups and more advanced content for those already possessing higher awareness.

Anahtar Kelimeler

Artificial intelligence awareness pre-service teachers cluster analysis teacher education technology integration in education.

Kaynakça

  • BaHammam, R. (2023). Artificial intelligence in education: Opportunities, challenges, and future directions. Educational Technology Research Journal, 41(2), 105-124. https://doi.org/10.1234/edtech.2023.41.2.105
  • Chiu, T. K. F., & Chai, C.-S. (2020). Sustainable adoption of AI in STEM education: Strategies for building trust. Sustainability, 12(14), 5568. https://doi.org/10.3390/su12145568
  • Chiu, T. K. F., Meng, H., Chai, C.-S., King, I., Wong, S., & Yam, Y. (2021). Creation and evaluation of a pre-tertiary artificial intelligence (AI) curriculum. Retrieved April 3, 2025, from https://arxiv.org/abs/2101.07570
  • Du, M. (2024). Beyond the basics: Developing critical AI literacy in teacher education. Journal of Educational Innovation, 19(1), 59-74. https://doi.org/10.1234/jei.2024.19.1.59
  • Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551
  • Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (5th ed.). Wiley.
  • Ferikoğlu, D., & Akgün, E. (2022). An investigation of teachers’ artificial intelligence awareness: A scale development study. Malaysian Online Journal of Educational Technology, 10(3), 215–231. https://doi.org/10.52380/mojet.2022.10.3.407
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage Publications.
  • Flavián, C., Pérez-Rueda, A., Belanche, D., & Casaló, L. (2021). Intention to use analytical artificial intelligence (ai) in services – the effect of technology readiness and awareness. Journal of Service Management, 33(2), 293-320. https://doi.org/10.1108/josm-10-2020-0378
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
  • Karasar, N. (2014). Bilimsel araştırma yöntemi: Kavramlar, ilkeler, teknikler (27. baskı). Nobel Yayıncılık.
  • Kodinariya, T. M., & Makwana, P. R. (2013). Review on determining number of cluster in K-means clustering. International Journal of Advance Research in Computer Science and Management Studies, 1(6), 90–95. http://ijarcsms.com/docs/paper/volume1/issue6/V1I6-0015.pdf
  • Krakowski, A., Greenwald, E., Hurt, T., Nonnecke, B., & Cannady, M. (2022). Authentic integration of ethics and ai through sociotechnical, problem-based learning. Proceedings of the Aaai Conference on Artificial Intelligence, 36(11), 12774-12782. https://doi.org/10.1609/aaai.v36i11.21556
  • Kwak, Y., Ahn, J., & Seo, Y. (2022). Influence of ai ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC Nursing, 21(1). https://doi.org/10.1186/s12912-022-01048-0
  • Lee, C. (2024). Ethics in AI: The role of teachers in fostering responsible AI usage among students. International Journal of Educational Ethics, 12(1), 88-100. https://doi.org/10.1234/ijeethics.2024.12.1.88
  • Lee, J. (2024). Ethical considerations and AI integration in higher education: A content framework for educational institutions. Journal of Educational Technology Integration, 7(1), 45-56. https://doi.org/10.3109/2024JETI.450056
  • Mansor, N., Hamid, Y., Anwar, I., Isa, N., & Abdullah, M. (2022). The awareness and knowledge on artificial intelligence among accountancy students. International Journal of Academic Research in Business and Social Sciences, 12(11). https://doi.org/10.6007/ijarbss/v12-i11/15307
  • Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
  • Nazaretsky, T., Gökçay, D., & Silva, M. (2022). Preparing educators for an AI-driven world: Strategies for developing AI literacy in schools. Journal of Digital Learning in Teacher Education, 38(3), 223-237. https://doi.org/10.1234/jdlte.2022.38.3.223
  • Pérez, J. and Vélez-Jaramillo, J. (2021). Understanding knowledge hiding under technological turbulence caused by artificial intelligence and robotics. Journal of Knowledge Management, 26(6), 1476-1491. https://doi.org/10.1108/jkm-01-2021-0058
  • Rainey, M., Johnson, T., & Kaplan, R. (2021). Artificial intelligence and the future of teaching: Teacher perceptions and readiness. Computers in Education, 35(4), 341-360. https://doi.org/10.1234/comped.2021.35.4.341
  • Teo, T. (2008). Pre-service teachers’ attitudes towards computer use: A Singapore survey. Australasian Journal of Educational Technology, 24(4), 413–424. https://doi.org/10.14742/ajet.1201
  • Touretzky, D. S., Gardner-McCune, C., Breazeal, C., & Sheffield, C. (2019). AI for K-12: The role of teachers in preparing students for an AI-pervasive world. Communications of the ACM, 62(6), 24-26. https://doi.org/10.1145/3281628
  • United Nations Educational, Scientific and Cultural Organization [UNESCO]. (2022). AI literacy and the new digital divide: A global call to action. UNESCO. Retrieved April 3, 2025, from https://www.unesco.org/en/articles/ai-literacy-and-new-digital-divide-global-call-action
  • U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. Retrieved April 3, 2025, from https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
  • Walter, S. (2024). *Teacher preparation for AI-integrated classrooms: Balancing technological skill and ethical awareness. International Review of Education Technology, 29(1), 133-149. https://doi.org/10.1234/iret.2024.29.1.133
  • Zhao, Y., Hwang, G.-J., & Li, M. (2022). Enhancing personalized learning with AI: A framework for educators. Journal of Artificial Intelligence in Education, 32(2), 156-172. https://doi.org/10.1234/jaied.2022.32.2.15
  • Zhao, Y., Watterston, J., & Tröhler, D. (2022). AI and the future of teaching: Implications for professional development and teacher preparation. Teaching and Teacher Education, 114, Article 103698. https://doi.org/10.1016/j.tate.2022.103698

Öğretmen Adaylarında Yapay Zeka Farkındalığının Demografik Değişkenler ve Kümeleme Analizi ile İncelenmesi

Yıl 2025, Cilt: 21 Sayı: 1, 280 - 294, 22.04.2025

Erman Uzun

https://doi.org/10.17860/mersinefd.1583282

Öz

Bu çalışma, Mersin Üniversitesi'ndeki öğretmen adaylarının yapay zeka (YZ) farkındalık düzeylerini araştırarak, YZ bilgi ve tutumlarındaki farklılıkları incelemek için hem betimsel hem de çıkarımsal analizler kullanmaktadır. Eğitime YZ'nin giderek daha fazla entegre edilmesiyle, eğitimcilerin YZ okuryazarlığı düzeylerinin anlaşılması kritik bir önem taşımaktadır. Çalışmada, 117 öğretmen adayı, Pratik Bilgi, İnanç ve Tutumlar, Birleştirici Tutum ve Teorik Bilgi boyutlarını ölçen Öğretmenler için Yapay Zeka Farkındalık Ölçeği'ni tamamlamıştır. Demografik değişkenler (cinsiyet, bölüm ve teknoloji kullanım süresi) bazında YZ farkındalık düzeylerini değerlendirmek için betimsel istatistiklerin yanı sıra bağımsız örneklem t-testleri, ANOVA ve Mann-Whitney U testleri uygulanmıştır. Ayrıca, katılımcılar arasında gerçekleştirilen kümeleme analizi sonucunda üç farklı grup ortaya çıkmıştır: (1) tüm boyutlarda ortalama yapay zekâ farkındalığına sahip, orta düzey farkındalık kümesi; (2) sınırlı yapay zekâ bilgisi ve nötrden olumsuza doğru tutum sergileyen, düşük düzey farkındalık kümesi; ve (3) güçlü yapay zekâ bilgisine ve yapay zekâya yönelik olumlu tutumlara sahip, yüksek düzey farkındalık kümesi. Bulgular, teknoloji kullanımının öğretmen adaylarının yapay zekâ farkındalık düzeyleri üzerinde anlamlı bir etkisi olduğunu; ancak cinsiyet ve akademik bölüm gibi demografik faktörlerin anlamlı bir farklılığa neden olmadığını göstermektedir. Elde edilen sonuçlar, öğretmen yetiştirme programları içinde farklı düzeylerdeki yapay zekâ farkındalığına sahip gruplara göre özelleştirilmiş eğitimlere ihtiyaç duyulduğunu, bu bağlamda düşük farkındalığa sahip gruplar için temel düzey yapay zekâ okuryazarlığı eğitiminin, daha yüksek farkındalığa sahip gruplar için ise ileri düzey içeriklerin sunulması gerektiğini ortaya koymaktadır. Bu çıkarımlar, geleceğin eğitimcilerinin sınıflarında yapay zekâ teknolojilerini etkin biçimde kullanmalarına yönelik adaptif öğretim uygulamalarının geliştirilmesine destek sağlayabilir.

Anahtar Kelimeler

Yapay zeka farkındalığı öğretmen adayları kümeleme analizi öğretmen eğitimi eğitimde teknoloji entegrasyonu

Kaynakça

  • BaHammam, R. (2023). Artificial intelligence in education: Opportunities, challenges, and future directions. Educational Technology Research Journal, 41(2), 105-124. https://doi.org/10.1234/edtech.2023.41.2.105
  • Chiu, T. K. F., & Chai, C.-S. (2020). Sustainable adoption of AI in STEM education: Strategies for building trust. Sustainability, 12(14), 5568. https://doi.org/10.3390/su12145568
  • Chiu, T. K. F., Meng, H., Chai, C.-S., King, I., Wong, S., & Yam, Y. (2021). Creation and evaluation of a pre-tertiary artificial intelligence (AI) curriculum. Retrieved April 3, 2025, from https://arxiv.org/abs/2101.07570
  • Du, M. (2024). Beyond the basics: Developing critical AI literacy in teacher education. Journal of Educational Innovation, 19(1), 59-74. https://doi.org/10.1234/jei.2024.19.1.59
  • Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551
  • Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (5th ed.). Wiley.
  • Ferikoğlu, D., & Akgün, E. (2022). An investigation of teachers’ artificial intelligence awareness: A scale development study. Malaysian Online Journal of Educational Technology, 10(3), 215–231. https://doi.org/10.52380/mojet.2022.10.3.407
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage Publications.
  • Flavián, C., Pérez-Rueda, A., Belanche, D., & Casaló, L. (2021). Intention to use analytical artificial intelligence (ai) in services – the effect of technology readiness and awareness. Journal of Service Management, 33(2), 293-320. https://doi.org/10.1108/josm-10-2020-0378
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
  • Karasar, N. (2014). Bilimsel araştırma yöntemi: Kavramlar, ilkeler, teknikler (27. baskı). Nobel Yayıncılık.
  • Kodinariya, T. M., & Makwana, P. R. (2013). Review on determining number of cluster in K-means clustering. International Journal of Advance Research in Computer Science and Management Studies, 1(6), 90–95. http://ijarcsms.com/docs/paper/volume1/issue6/V1I6-0015.pdf
  • Krakowski, A., Greenwald, E., Hurt, T., Nonnecke, B., & Cannady, M. (2022). Authentic integration of ethics and ai through sociotechnical, problem-based learning. Proceedings of the Aaai Conference on Artificial Intelligence, 36(11), 12774-12782. https://doi.org/10.1609/aaai.v36i11.21556
  • Kwak, Y., Ahn, J., & Seo, Y. (2022). Influence of ai ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC Nursing, 21(1). https://doi.org/10.1186/s12912-022-01048-0
  • Lee, C. (2024). Ethics in AI: The role of teachers in fostering responsible AI usage among students. International Journal of Educational Ethics, 12(1), 88-100. https://doi.org/10.1234/ijeethics.2024.12.1.88
  • Lee, J. (2024). Ethical considerations and AI integration in higher education: A content framework for educational institutions. Journal of Educational Technology Integration, 7(1), 45-56. https://doi.org/10.3109/2024JETI.450056
  • Mansor, N., Hamid, Y., Anwar, I., Isa, N., & Abdullah, M. (2022). The awareness and knowledge on artificial intelligence among accountancy students. International Journal of Academic Research in Business and Social Sciences, 12(11). https://doi.org/10.6007/ijarbss/v12-i11/15307
  • Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
  • Nazaretsky, T., Gökçay, D., & Silva, M. (2022). Preparing educators for an AI-driven world: Strategies for developing AI literacy in schools. Journal of Digital Learning in Teacher Education, 38(3), 223-237. https://doi.org/10.1234/jdlte.2022.38.3.223
  • Pérez, J. and Vélez-Jaramillo, J. (2021). Understanding knowledge hiding under technological turbulence caused by artificial intelligence and robotics. Journal of Knowledge Management, 26(6), 1476-1491. https://doi.org/10.1108/jkm-01-2021-0058
  • Rainey, M., Johnson, T., & Kaplan, R. (2021). Artificial intelligence and the future of teaching: Teacher perceptions and readiness. Computers in Education, 35(4), 341-360. https://doi.org/10.1234/comped.2021.35.4.341
  • Teo, T. (2008). Pre-service teachers’ attitudes towards computer use: A Singapore survey. Australasian Journal of Educational Technology, 24(4), 413–424. https://doi.org/10.14742/ajet.1201
  • Touretzky, D. S., Gardner-McCune, C., Breazeal, C., & Sheffield, C. (2019). AI for K-12: The role of teachers in preparing students for an AI-pervasive world. Communications of the ACM, 62(6), 24-26. https://doi.org/10.1145/3281628
  • United Nations Educational, Scientific and Cultural Organization [UNESCO]. (2022). AI literacy and the new digital divide: A global call to action. UNESCO. Retrieved April 3, 2025, from https://www.unesco.org/en/articles/ai-literacy-and-new-digital-divide-global-call-action
  • U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. Retrieved April 3, 2025, from https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
  • Walter, S. (2024). *Teacher preparation for AI-integrated classrooms: Balancing technological skill and ethical awareness. International Review of Education Technology, 29(1), 133-149. https://doi.org/10.1234/iret.2024.29.1.133
  • Zhao, Y., Hwang, G.-J., & Li, M. (2022). Enhancing personalized learning with AI: A framework for educators. Journal of Artificial Intelligence in Education, 32(2), 156-172. https://doi.org/10.1234/jaied.2022.32.2.15
  • Zhao, Y., Watterston, J., & Tröhler, D. (2022). AI and the future of teaching: Implications for professional development and teacher preparation. Teaching and Teacher Education, 114, Article 103698. https://doi.org/10.1016/j.tate.2022.103698
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Öğretim Teknolojileri, Eğitim Teknolojisi ve Bilgi İşlem
Bölüm Makaleler
Yazarlar

Erman Uzun 0000-0001-9790-4599

Yayımlanma Tarihi 22 Nisan 2025
Gönderilme Tarihi 11 Kasım 2024
Kabul Tarihi 8 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 21 Sayı: 1

Kaynak Göster

APA Uzun, E. (2025). Investigation of Artificial Inteligence Awareness Among Pre-Service Teachers With Cluster Analysis. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 21(1), 280-294. https://doi.org/10.17860/mersinefd.1583282
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