Present and Future of Artificial Intelligence: A Case Study on Prospective Teachers

Yıl 2024, Cilt: 14 Sayı: 2 (Special Issue-Artificial Intelligence Tools and Education), 194 - 212, 26.07.2024

Mehmet Uymaz

https://doi.org/10.19126/suje.1466052

Öz

This study investigates prospective teachers' perspectives on the present status of artificial intelligence (AI) and their predictions regarding its future development. The study utilized a case study approach to select a group of 64 prospective teachers from the faculty of education at a state university in Türkiye. The study participants comprised 34 female and 30 male prospective teachers. The researchers employed a purposive sampling technique, specifically the criterion sampling approach, to select the prospective teachers included in the study. The researchers collected data for the study using the "AI Perception Interview Form" and the "AI Future Foresight Determination Form," and then analyzed the data using descriptive and content analysis techniques. The results showed that prospective teachers obtained information about AI primarily from social media, internet/news websites, and applications. Analyzing the definitions and explanations provided by the prospective teachers revealed that they particularly emphasized the uploading of human intelligence to computer systems, the acquisition of human-like abilities by machines, and the ability of AI to learn independently. Additionally, prospective teachers identified health, education, accounting, and finance as domains with significant potential for the advancement of AI. In education, the initial applications prospective teachers thought AI could be used for included determining students' mental states, assessing student levels, and providing personalized content. The data obtained from the study indicate that prospective teachers produced both utopian and dystopian content regarding the future of AI. This production of varied content reveals that prospective teachers have diverse perspectives on the future of AI.

Anahtar Kelimeler

Prospective Teachers, Artificial Intelligence, AI Perceptions, Education, AI Future Predictions

Kaynakça

• Acar, O. (2020). AI: opportunity or threat? Istanbul, Kriter Publishing.
• Ağkaya, O. (2016). Utopia and dystopia: the influence of politics on literature. Manisa Celal Bayar University Journal of Social Sciences, 14(4), 4-23. https://doi.org/10.18026/cbayarsos.280053
• Al-Matari, A. S. (2023). AI and the future of teaching and learning. Conference: Pelita Internasional Conference (PIC). DOI: 10.13140/RG.2.2.28132.76160
• Altun, D. (2019). Virtual reality and AI. In G. Telli (Ed.), AI and the future (pp. 139-157). Istanbul, Eastern Publishing House.
• Atasoy, S. (2012). Modeling performance management in human resources with artificial neural networks and neural fuzzy networks (Master's thesis No. 322637). Yildiz Technical University Institute of Science. YOK National Thesis Center.
• Aydın, Ş. E. (2017). AI technology (yesterday, today, tomorrow) [Master's Semester Project, Çukurova University].
• Balaban, M. E., & Kartal, E. (2015). Data mining and machine learning. İstanbul: Caglayan Publishing House. Becker, A. S., Brown, M., Dahlstrom, E., Davis, A., DePaul, K., Diaz, V., & Pomerantz, J. (2018). Horizon report: 2018 Higher Education. EDUCASE.
• Boucher, P. (2019). How AI works. EPRS. Panel for the Future of Science and Technology.http://www.europarl.europa.eu/RegData/etudes/BRIE/2019/634420/EPRS_BRI(2019)634420_EN.pdf
• Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27-40.
• Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., Henke, N., & Trench, M. (2017). AI: The next digital frontier? McKinsey Global Institute.
• Büyüköztürk, Ş., Kılıç Çakmak, E., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2014). Research methods in science (17th Edition). Ankara: Pegem Publishing.
• Chmiliar, L. (2010). Multiple-case designs. In A. J. Mills, G. Eurepas, & E. Wiebe (Eds.), Encyclopedia of Case Study Research (pp. 582-583). New York: SAGE Publications.
• Cibaroğlu, M. O., & Yalçinkaya, B. (2019). Big data analytics and AI applications in document and archive management processes. Information Management, 2(1), 44-58.
• Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education (5th Edition). Londra: Routledge Falmer.
• Coppin, B. (2004). AI ılluminated. Massachusetts: Jones and Bartlett Publishers.
• Creswell, J. W. (2007). Qualitative inquiry & research design: choosing among five approaches (2nd Edition). New York: SAGE Publications.
• Çam, M. B., Çelik, N. C., Turan Güntepe, E., & Durukan, Ü. G. (2021). Determination of teacher candidates' awareness of AI technologies. Hatay Mustafa Kemal University Journal of Social Sciences Institute, 18(48), 263-285.
• ElAzab M. (2023). The future of teaching and learning in the AI era. International Journal of Internet Education, 1(1), 1-8.
• Ertel, W. (2011). Introduction to AI. Berlin: Springer.
• Fast, E., & Horvitz, E. (2020). Long-term trends in public perception of AI. Proceedings of the AAAI Conference on AI, 31(1), 1-7.
• Firschein, O., Fischler, M. A., Coles, L. S., & Tenenbaum, J. M. (1973). Forecasting and assessing the ımpact of AI on society. IJCAI'73: Proceedings of the 3rd International Joint Conference on AI (pp. 105-120).
• Goksel, N., & Bozkurt, A. (2019). AI in education: current ınsights and future perspectives. In S. Sisman-Ugur & G. Kurubacak (Eds.), Handbook of Research on Learning in the Age of Transhumanism (pp. 224-236). Pensilvanya: IGI Global.
• Gondal, K. M. (2018). AI and educational leadership. Annals of King Edward Medical University, 24(4), 1-2.
• Kelley, T., & Knowles, J. (2016). AI. In J. Britt Holbrook (Ed.), encyclopedia of science, technology, and ethics (2nd Edition, Vol. 1, pp. 180-182). Macmillan Reference USA.
• Khare, K., Stewart, B., & Khare, A. (2018). AI and the student experience: an ınstitutional perspective. IAFOR Journal of Education, 6(3), 63-78.
• Komalavalli, K., Hemalatha, R., & Dhanalakshmi, S. (2020). A survey of AI in smartphones and ıts applications among higher education students in and around chennai city. Shanlax International Journal of Education, 8(3), 89-95.
• Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage Publications.
• Luckin, R. (2017). Towards AI-based assessment systems. Nature Human Behaviour, 1(3), 1-3.
• Merriam, S. B. (2013). Qualitative Research: A guide for design and ımplementation (Translation from 3rd Edition, Translation Editor: S. Turan). Ankara: Nobel Publishing.
• Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: an expanded sourcebook. New York: Sage Publication.
• Nabiyev, V., & Erümit, A. K. (2020). Foundations of AI. In V. Nabiyev & A. K. Erümit (Eds.), AI in Education from Theory to Practice (pp. 2-37). Ankara: Pegem Akademi Publishing.
• Obschonka, M., & Audretsch, D. B. (2020). AI and big data in entrepreneurship: A new era has begun. Small Business Economics, 55(3), 529-539.
• Oliveira, M., Lopes, C., Soares, F., Pinheiro, G., & Guimaraes, P. (2020). What can we expect from the future? the ımpact of AI on society. 15th Iberian Conference on Information Systems and Technologies (CISTI), 1-6.
• Özgeldi, M. (2019). AI and Human Resources. In G. Telli (Ed.), AI and the future (pp. 198-222). Istanbul, Eastern Publishing House.
• Öztemel, E. (2020). AI and the future of humanity. Information Technologies and Communication: The Future of Individuals and Society, Turkish Academy of Sciences.
• Popenici, S. A., & Kerr, S. (2017). Exploring the impact of AI on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 22(12).
• Sarıel, S. (2017). "AI today." In M. Karaca (Ed.), Humanized Machines and AI (pp. 21-25). Istanbul Technical University Foundation Journal.
• Sheikh, S. (2020). Understanding the role of AI and ıts future social ımpact. Pensilvanya: IGI Global.
• Singh, G., Mishra, A., & Sagar, D. (2013). An overview of AI. SBIT Journal of Sciences and Technology, 2(1), 1-4.
• Tamer, H. Y., & Övgün, B. (2020). Digital transformation office in the context of AI. Ankara University Faculty of Political Sciences Journal, 75(2), 775-803.
• Taşkın, H., & Adalı, M. R. (2004). Technological intelligence and competition strategies. Sakarya: Degisim Publications.
• Taşçı, G., & Çelebi, M. (2020). A New Paradigm in education: AI in higher education. OPUS–International Journal of Social Research, 16(29), 2346-2370.
• Tekgüç, U., & Adalıer, A. (2019). Deep learning in education and applications. In A. Şişman, H. F. Odabaşi, & B. Akkoyunlu (Eds.), Educational Technology Readings (pp. 243-260). Ankara: Pegem Akademi Publishing.
• Teng, X. (2019). Discussion about AI's advantages and disadvantages compared to natural ıntelligence. Journal of Physics: Conf. Series, 1187, 1-7.
• Uymaz, M. (2023). A Comparative analysis of gifted and typically developing secondary school students' perceptions of the future. Sakarya University Journal of Education, 13(3), 504-526.
• Xu, Z., & Yang, Q. (2012). Analyzing user retweet behavior on twitter. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 46-50).
• van Hooijdonk, R. (2017). 10 Technologies that could one day turn us all into real cyborgs. Retrieved March 1, 2024, from https://www.richardvanhooijdonk.com/blog/en/10-
• Yıldırım, A., & Şimşek, H. (2011). Qualitative research methods in social sciences. Ankara: Seçkin Publishing.
• Yılmaz, İ. (2012). An AI application for staff planning in personnel planning (Master's thesis No. 387319). Gazi University Institute of Science. YOK National Thesis Center.
• Yin, R. K. (2009). Case study methods: design and methods (4th Edition). New York: Sage Publication.