YAPAY ZEKÂ BAĞLAMINDA OKUL LİDERLERİNİ BEKLEYEN ZORLUKLAR

Yıl 2023, , 74 - 85, 31.12.2023

Mehmet Sincar

https://doi.org/10.56677/mkuefder.1407065

Öz

Eğitimde yapay zekâ kullanımı dünyanın farklı yerlerinde farklı platformlar altında yaygınlaşmaktadır. Eğitimde yapay zekâ kullanımı derinleştikçe, görevlerinin doğası gereği, karşılaşılan fırsatları değerlendirecek ve çok daha önemlisi, olası zorlukların üstesinden gelecekler arasında ilk sırayı okul liderleri alacaktır. Yapay zekâ teknolojileri eğitimde daha fazla rol oynamaya başladıkça, okul liderleri de bu yeni durum için hazır olmalıdırlar. Bu bağlamda bu makalenin amacı, yapay zekânın eğitimde kullanılmasının okul liderleri için getireceği zorlukları tartışılarak, eğitim dünyasındaki yeni bir aktörü anlamayı ve konuya ilişkin bir farkındalık oluşturmayı amaçlamaktadır. Okul liderleri, eğitimde yapay zekâ teknolojilerinin etkin bir şekilde kullanılabilmesi için çeşitli zorlukları aşmak zorundadırlar. Bunlar, yapay zekânın okul liderleri tarafından benimsenmesi, okulda yapay zekânın nasıl kullanılacağına ilişkin paydaşlarla ortak hareket edilmesi, karar verme, etik ilkelerin gözetilmesi ve veri güvenliğinin sağlanmasının sağlıklı olmadığı durumlarda kendini gösterir. Beraberinde getirdiği zorluklardan dolayı eğitimde yapay zekânın kullanılmasına konulacak mesafe, özellikle dezavantajlı grupların olası erişim ve eşitlik fırsatlarından mahrum kalması anlamına gelebilir. Bu nedenle okul liderlerinin yapay zekâ bağlamında karşılaşabilecekleri zorlukların üstesinden gelmek için daha fazla bilimsel bilgiye ihtiyaç vardır.

Anahtar Kelimeler

Yapay zekâ, Okul liderliği, Eğitim liderliği

Kaynakça

• ALEKS (2023). About ALEKS. Retrieved December 17, 2023, from https://www.aleks.com/about_aleks Aoun, J. (2017). Robot-proof: Higher education in the age of artificial intelligence. The MIT Press. Bostrom, N. (2014). Superintelligence: paths, dangers, strategies. Oxford University Press.
• Carnegie Learning (2023). Why CL. Retrieved December 17, 2023, from https://www.carnegielearning.com/why-cl/
• Castelvecchi, D. (2016). Can we open the black box of AI? Nature, 538(7623), 20-23.
• Chan, Z.S. & Zary, N. (2019). Applications and Challenges of Implementing Artificial Intelligence in Medical Education: Integrative Review. JMIR Med Educ 2019, 5(1), 1-15.
• Coccoli, M.M., Maresca, P.P. & Stanganelli, L. (2016). Cognitive computing in education. Journal of E-Learning and Knowledge Society, 12(2), 55-69.
• Cook, V.S. & Gregory, R.L. (2018). Emerging technologies: It’s not what yobattu say – it’s what they do. Online Learning, 22(3), 121-130.
• Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology 32(3), 444–452. https://doi.org/10.1007s10956-023-10039-y
• Davenport, T.H. (2018). The AI advantage: How to put the artificial intelligence revolution to work. The MIT Press.
• Di Battista, A., Grayling, S., & Hasselaar, E. (2023). Future of jobs report 2023. World Economic Forum, Geneva, Switzerland.
• Dickson, B. (2017). How artificial intelligence is shaping the future of education. PC Magazine, 20, 105-115.
• Dobrin, S. (2023). AI and writing (1st ed.). Broadview Press.
• Duke, D. (2019). Judgment and the preparation of educational leaders. Journal of Research on Leadership Education, 14(3), 191-211.
• Ford, M. (2015). Rise of the robots: Technology and the threat of a jobless future. Perseus Books Group.
• Fullan, M., Azorin, C., Harris A. & Jones, M. (2023). Artificial intelligence and school leadership: challenges, opportunities and implications, School Leadership & Management, DOI:10.1080/13632434.2023.2246856
• García-Peñalvo, F. J. (2023). The perception of artificial intelligence in educational contexts after the launch of ChatGPT: Disruption or panic. Education in the Knowledge Society, 24: 1–9.
• Hagendorff, T. (2019). From privacy to anti-discrimination in times of machine learning. Ethics and Information Technology, 1–13. https://doi-org.proxy.lib.wayne.edu/10.1007/s10676-019-09510-5.
• Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds and Machines, 99–120. https://doi.org/10.1007/s11023-020-09517-8.
• Harris, A. & Jones, M. (2023) Compassionate leadership, School Leadership & Management, 43(3), 185-188.
• Hu, J. (2021). Teaching Evaluation System by use of Machine Learning and Artificial Intelligence Methods. International Journal of Emerging Technologies in Learning, 16(5), 87-101.
• Huang, M.H., Rust, R. & Maksimovic, V. (2019). The feeling economy: managing in the next generation of artificial intelligence (AI). California Management Review, 61(4), 43-65.
• Jarrahi, M.H. (2018). Artificial intelligence and the future of work: human-AI symbiosis in organizational decision-making. Business Horizons, 61(4), 577-586.
• Khan, I., Ahmad, A. R., Jabeur, N., & Mahdi, M. N. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environments, 8(1), 1-18. https://doi.org/10.1186/s40561-021-00161-y
• Krakovsky, M. (2018). Artificial (emotional) intelligence: enabled by advances in computing power and neural networks, machines are getting better at recognizing and dealing with human emotions. Communications of the ACM, 61(4) 18-19.
• Kumar, N. S. (2019). Implementation of artificial intelligence in imparting education and evaluating student performance. Journal of Artificial Intelligence, 1(01), 1-9. https://doi.org/10.36548/jaicn.2019.1.001
• Lechuga, C.G. & Doroudi, S. (2022). Three Algorithms for Grouping Students: A Bridge Between Personalized Tutoring System Data and Classroom Pedagogy. International Journal of Artificial Intelligence in Education, 1-42.
• Lee, K. (2018). AI superpowers: China, Silicon Valley, and the new world order. Huili Shi.
• Lin, P. Y., Chai, C. S., Jong, M. S. Y., Dai, Y., Guo, Y., & Qin, J. (2021). Modelling the structural relationship among primary students’ motivation to learn artificial intelligence. Computers and Education: Artificial Intelligence, 2, https://doi.org/10.1016/j.caeai.2020.100006
• Luo, Y., Han, X., & Zhang, C. (2022). Prediction of learning outcomes with a machine learning algorithm based on online learning behavior data in blended courses. Asia Pacific Education Review. https://doi.org/10.1007/s12564-022-09749-6
• Mandinach, E. B., Friedman, J. M., & Gummer, E. S. (2015). How can schools of education help to build educators’ capacity to use data? A systemic view of the issue. Teachers College Record, 117(4), 1–50.
• Matayoshi, J. & Uzun, H. (2022). Learning, forgetting, and the correlation of knowledge in knowledge space theory. Journal of Mathematical Psychology, 109, 1-18.
• McDuff, D., & Czerwinski, M. (2018). Designing emotionally sentient agents. Communications of the ACM, 61(12), 74–83.
• Nabiyev, V., Karal, H., Arslan, S., Erumit, A.K. & Cebi, A. (2013). An artificial intelligence-based distance education system: Artimat. The Turkish Online Journal of Distance Education, 14(2), 81-98.
• Naqvi, A. (2020). Artificial intelligence for audit, forensic accounting, and valuation: A strategic perspective. John Wiley & Sons. https://doi.org/10.1002/978111960 1906
• Nguyen, D.N. (2023). Exploring the role of AI in education. London Journal of Social Sciences, 6, 84-95. Oplatka, I. (2010). The legacy of educational administration: A historical analysis of an academic field. Peter Lang.
• Pane, J. F., Griffin, B. A., McCaffrey, D. F., & Karam, R. (2014). Effectiveness of cognitive tutor algebra I at scale. Educational Evaluation and Policy Analysis, 36(2), 127–144.
• Papa, R. & Jackson, K.M. (2021). Artificial intelligence, human agency, and the educational leader. Springer.
• Pearson. (2023). Why we’re thoughtfully optimistic about Generative AI in education? Retrieved December 17, 2023, from https://plc.pearson.com/en-GB/insights/why-were-thoughtfully-optimistic-about-generative-ai-education
• Phillips, A., Pane, J. F., Reumann-Moore, R., & Shenbanjo, O. (2020). Implementing an adaptive intelligent tutoring system as an instructional supplement. Educational Technology Research and Development, 1–29.
• Russell, S. (2019). Human compatible: Artificial intelligence and the problem of control. Penguin.
• Shubhendu, S.S. & Vijay, J. (2013). Applicability of artificial intelligence in different fields of life. International Journal of Scientific Engineering and Research, 1(1), 28-35.
• Sparks, S.D. (2017). How ‘Intelligent’ Tutors Could Transform Teaching. Retrieved December 17, 2023, from https://www.edweek.org/leadership/how-intelligent-tutors-could-transform-teaching/2017/09
• Stahl, C., & Hockemeyer, C. (2022). Knowledge space theory. The Comprehensive R Archive Network, 1-12.
• Tajik, E., & Tajik, F. (2023). A comprehensive examination of the potential application of ChatGPT in Higher Education Institutions. TechRxiv. 1–10. https://doi.org/10.36227/techrxiv.22589497.v1
• Tyson, M.M. & Sauers, N. J. (2021). School leaders’ adoption and implementation of artificial intelligence. Journal of Educational Administration, 59(3), 271-285.
• UNESCO (2023). Global Education Monitoring Report. Technology in Education. A Tool on Whose Terms? Paris: UNESCO.
• Wang, Y. (2021a). Artificial intelligence in educational leadership: a symbiotic role of human-artificial intelligence decision-making. Journal of Educational Administration, 59(3), 256-270.
• Wang, Y. (2021b). When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale. Studies in Educational Evaluation, 69, 1-9.
• Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). ChatGPT: A revolutionary tool for teaching and learning mathematics. EURASIA Journal of Mathematics, Science and Technology Education, 19(7). https://doi.org/10.29333/ejmste/13272
• Wooldridge, M. (2021). A Brief History of Artificial Intelligence: What it is, where we are, and where we are going. Flatiron Books.
• Xia, Q., Chiu, T. K. F, Lee, M., Temitayo I., Dai, Y., & Chai, C. S. (2022). A self-determination theory design approach for inclusive and diverse artificial intelligence (AI) K-12 education. Computers & Education, 189. https://doi.org/10.1016/j.compedu.2022.104582
• Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(39), 1-27.