Teachers' Perception Scale Towards the Use of Artificial Intelligence Tools in Education
Abstract
The aim of this study is to develop a scale to determine teachers' perceptions of the use of artificial intelligence tools in education. The universe of the study consists of teachers from different branches working in schools affiliated with the Ministry of National Education throughout Türkiyein the 2023-2024 academic year. The sample of the study consists of 530 volunteer teachers. Exploratory factor analysis was conducted to determine the construct validity of the scale with the collected data. Pearson r test was used for the validity of the scale, and in order to determine the discrimination of the items, the difference between the groups was examined by determining the 27% upper group and 27% lower group. In order to obtain reliability, internal consistency coefficients were calculated, and stability tests were conducted with the test-retest method. The scale consists of 3 factors and 37 items. The factors were named considering the item contents. The total Cronbach Alpha value of the factors in the scale was determined as 0.970 and the total Omega value as 0.971. The correlation obtained by the test-retest method varies between 0.660 and 0.509 of the factors. It was determined that the factors determined in the scale explained 64.295% of the total variance. In this study, the validity and reliability of the "Teachers' Perception Scale towards Use of Artificial Intelligence Tools in Education" was evaluated. The results of the research show that the scale is a valid and reliable measurement tool in determining teachers' perceptions about the use of artificial intelligence tools in education.
Keywords
Artificial intelligence in education, perception towards artificial intelligence tools, developing scale
Thanks
Bu prestijli derginin özel sayısına katkıda bulunmak benim için büyük bir onurdur. İlgili çalışmayı bilimsel topluluğa sunma fırsatı verdikleri için tüm dergi ekibine minnettarım.
References
- Akkaya, B., Özkan, A. & Özkan, H. (2021). Artificial intelligence anxiety (AIA) scale: adaptation to Turkish, validity and reliability study. Alanya Academic Review Journal, 5(2), 1125-1146.
- Ahmed, F. M. (2020). The Adoption of Artificial Intelligence in UAE Education Sector. Unpublished Master's thesis, The British University, Dubai
- Bandura, A. (1997). Self-efficacy the exercise of control. New York: H. Freeman & Co. Student Success, 333, 48461.
- Büyüköztürk, Ş. (2002). Sosyal bilimler için veri analizi el kitabı [Data analysis handbook for social sciences]. Ankara: PegemA Pub.
- Bryman, A., & Cramer, D. (1997). Quantitative data Analysis with SPSS for windows: A guide for social scientists. New York: Routledge
- Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278.
- 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.
- Coşkun, F., & Gülleroğlu, H. D. (2021). Development of artificial intelligence in history and its usage in education. Ankara University Journal of Faculty of Educational Sciences (Jfes), 54(3), 947-966.
- Çelebi, C., Yılmaz, F., Demir, U. Ve Karakuş, F. (2023). Artificial intelligence literacy: An adaptation study. Instructional Technology and Lifelong Learning, 4(2), 291-306.
- Çam, M. B., Çelik, N. C., Güntepe, E. T., & Durukan, Ü. G. (2021). Determining teacher candidates’ awareness of artificial intelligence technologies. Mustafa Kemal University Journal of Social Sciences Institute. 18(48), 263-285.
