ע 55 מור דשן, ראובן הררי, נועה אהרוני מקורות Al-Abdullatif, A. M. (2024). Modeling teachers' acceptance of generative artificial intelligence use in higher education: The role of AI literacy, intelligent TPACK, and perceived trust. Education Sciences, 14(11), 1209. Bhat, M. A., Tiwari, C. K., Bhaskar, P., & Khan, S. T. (2024). Examining ChatGPT adoption among educators in higher educational institutions using extended UTAUT model. Journal of Information, Communication and Ethics in Society, 22(3), 331-353. Brandão, A., Pedro, L., & Zagalo, N. (2024). Teacher professional development for a future with generative artificial intelligence–an integrative literature review. Digital Education Review, (45), 151-157. Chi, O. H., Gursoy, D., and Chi, C. G. (2022). Tourists' attitudes toward the use of artificially intelligent (AI) devices in tourism service delivery: Moderating role of service value seeking. Journal of Travel Research, Vol. 61(1), 170-185. Chiu, T. K. (2024). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187-6203. Chiu, T. K., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171. Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results" (Doctoral dissertation, Massachusetts Institute of Technology). Elshaer, I. A., Hasanein, A. M., & Sobaih, A. E. E. (2024). The moderating effects of gender and study discipline in the relationship between university students' acceptance and use of ChatGPT. European Journal of Investigation in Health, Psychology and Education, 14(7), 1981-1995. GC, S. B., Bhandari, P., Gurung, S. K., Srivastava, E., Ojha, D., & Dhungana, B. R. (2024). Examining the role of social influence, learning value and habit on students' intention to use ChatGPT: the moderating effect of information accuracy in the UTAUT2 model. Cogent Education, 11(1), 2403287. Granić, A. (2022). Educational technology adoption: A systematic review. Education and Information Technologies, 27(7), 9725-9744. Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers' acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, pp. 157-169. Holmes, W; Bialik, M; Fadel, C; (2019) Artificial Intelligence in Education Promises and Implications for Teaching and Learning. (1st ed.). Center for Curriculum Redesign: MA, USA. Hu, L., Wang, H., & Xin, Y. (2025). Factors influencing Chinese pre-service teachers' adoption of generative AI in teaching: an empirical study based on UTAUT2 and PLS-SEM. Education and Information Technologies, 1-23. Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001. Kelly, S., Kaye, S. A., and Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925. Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). Lu, L., Cai, R., and Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36-51. Ma, X., and Huo, Y. (2023). Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework. Technology in Society, 75, 102362.
RkJQdWJsaXNoZXIy Mjk0MjAwOQ==