رجبیان ده زیره، مریم. (1403). شناسایی چالشها و قابلیتهای هوش مصنوعی در آموزش و یادگیری با ارائه راهکارها. فناوری آموزش، 18(4)، 921-950. https://doi.org/10.22061/tej.2024.10777.3058
زنگانه، امیرحسین، حجازی، الهه و صالحی، کیوان. (1404). عوامل مؤثر بر پذیرش فناوری هوش مصنوعی در بین اعضای هیئتعلمی دانشگاه تهران. فناوری و دانشپژوهی در تعلیم و تربیت 5 (1)، 65-80. https://doi.org/10.30473/t-edu.2025.73017.1228
صفری، احرام و انصاری، علیاصغر. (1401). شناسایی و رتبهبندی عوامل مؤثر بر پذیرش هوش مصنوعی در بخش دولتی و خصوصی. مطالعات مدیریت کسبوکار هوشمند 11(41)،221-254. https://doi.org/10.22054/IMS.2022.66402.2131
محمدزاده ونستان، سهیلا و عابدی، رحیم. (1403). بررسی نقش توانمندسازهای هوش مصنوعی و آمادگی هوش مصنوعی شرکتها در پذیرش سیستم مدیریت روابط با مشتری ادغامشده با هوش مصنوعی. مدیریت بازرگانی، 16(1), 34-58. https://doi.org/10.22059/jibm.2023.352689.4509
میرمعصومی، مهدی. (1403). تجزیهوتحلیل پذیرش استفاده از هوش مصنوعی در مراکز آموزشی. فصلنامه پیشرفتهای نوین در مدیریت آموزشی 5(1)، 45-46.
Akimov, N., Kurmanov, N., Uskelenova, A., Aidargaliyeva, N., Mukhiyayeva, D., Rakhimova, S., Raimbekov, B., & Utegenova, Z. (2023). Components of education 4.0 in open innovation competence frameworks: Systematic review.
Journal of Open Innovation: Technology, Market, and Complexity, 9(2), Article 100037.
https://doi.org/10.1016/j.joitmc.2023.100037
Al Darayseh, A. (2023). Acceptance of artificial intelligence in teaching science: Science teachers' perspective.
Computers and Education: Artificial Intelligence, 4, Article 100132.
https://doi.org/10.1016/j.caeai.2023.100132
Al-Abdullatif, A. M. (2023). Modeling students' perceptions of chatbots in learning: Integrating technology acceptance with the value-based adoption model.
Education Sciences, 13(11), Article 1151.
https://doi.org/10.3390/educsci13111151
Almahri, F. A. J., Bell, D., & Merhi, M. (2020, March). Understanding student acceptance and use of chatbots in the United Kingdom universities: A structural equation modelling approach. In
2020 6th International Conference on Information Management (ICIM) (pp. 284–288). IEEE.
https://doi.org/10.1109/ICIM49319.2020.244712
Alzahrani, L. (2023). Analyzing students' attitudes and behavior toward artificial intelligence technologies in higher education. International Journal of Recent Technology and Engineering, 11(6), 65–73.
Amani, H., Matlabi Nejad, A., Choupani, F., & Zare Gachi, M. (2024). Systematic analysis of the effects of ChatGPT application in education. Quarterly Journal of Technology and Knowledge Research in Education, 4(2), 9–23. [In Persian]
Asadzadeh, A., Mahdiyoun, R., & Yarmohammadzadeh, P. (2021). Identifying obstacles to the use of information and communication technology in students' educational activities: A case study of Urmia University.
Information Management Sciences, 7(2), 175–198.
https://sid.ir/paper/1005872/fa [In Persian]
Azizi, M., Izadi, S., & Babaeian, F. (2020). Barriers to adoption and use of ICT in elementary schools. Rahyafte No in Educational Management, 11(41), 117–134. [In Persian]
Bervell, B., & Umar, I. N. (2017). Validation of the UTAUT model: Re-considering non-linear relationships of exogeneous variables in higher education technology acceptance research.
Eurasia Journal of Mathematics, Science and Technology Education, 13(10), 6471–6490.
https://doi.org/10.12973/ejmste/78076
Bhatia, P. (2023). ChatGPT for academic writing: A game changer or a disruptive tool?
Journal of Anaesthesiology Clinical Pharmacology, 39(1), 1–2.
https://doi.org/10.4103/joacp.joacp_84_23
Cabero-Almenara, J., Palacios-Rodríguez, A., Loaiza-Aguirre, M. I., & Rivas-Manzano, M. D. R. D. (2024). Acceptance of educational artificial intelligence by teachers and its relationship with some variables and pedagogical beliefs.
Education Sciences, 14(7), Article 740.
https://doi.org/10.3390/educsci14070740
Cai, Z., Fan, X., & Du, J. (2017). Gender and attitudes toward technology use: A meta-analysis.
Computers & Education, 105, 1–13.
https://doi.org/10.1016/j.compedu.2016.11.003
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model.
Frontiers in Psychology, 10, Article 1652.
https://doi.org/10.3389/fpsyg.2019.01652
Chiu, T. K. F., & Churchill, D. (2016). Adoption of mobile devices in teaching: Changes in teacher beliefs, attitudes, and anxiety.
Interactive Learning Environments, 24(2), 317–327.
https://doi.org/10.1080/10494820.2015.1113709
Chrisinger, D. (2019). The solution lies in education: Artificial intelligence & the skills gap.
On the Horizon, 27(1), 1–4.
https://doi.org/10.1108/OTH-03-2019-096
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy.
International Journal of Information Management, 71, Article 102642.
https://doi.org/10.1016/j.ijinfomgt.2023.102642
Dwivedi, Y. K., Rana, N. P., & Chen, H. (2011). A meta-analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT). In
Governance and sustainability in information systems (pp. 155–170). Springer.
https://doi.org/10.1007/978-3-642-24148-2_10
Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Philosophy and Rhetoric, 10(2), 130–132.
Gennari, R., Matera, M., Morra, D., Melonio, A., & Rizvi, M. (2023). Design for social digital well-being with young generations: Engage them and make them reflect.
International Journal of Human–Computer Studies, 173, Article 103006.
https://doi.org/10.1016/j.ijhcs.2023.103006
Herbold, S., Hautli-Janisz, A., Heuer, U., Kikteva, Z., & Trautsch, A. (2023).
AI, write an essay for me: A large-scale comparison of human-written versus ChatGPT-generated essays. arXiv.
https://arxiv.org/abs/2304.14276
Huang, J., Saleh, S., & Liu, Y. (2021). A review on artificial intelligence in education.
Academic Journal of Interdisciplinary Studies, 10(3), 206–217.
https://doi.org/10.36941/ajis-2021-0077
Khorsandi Taskouh, A., Jameh Bozorg, Z., & Askari, A. (2023). Emerging technologies in learning and education: Emphasis on challenges and required policies in the post-COVID era.
Educational Technologies in Learning, 5(19), 106–128.
https://doi.org/10.22054/jti.2023.72262.1364 [In Persian]
Koubaa, A., Boulila, W., Ghouti, L., Alzahem, A., & Latif, S. (2023). Exploring ChatGPT capabilities and limitations: A survey.
IEEE Access, 11, 118698–118721.
https://doi.org/10.1109/ACCESS.2023.3326474
Lin, H. C., Ho, C. F., & Yang, H. (2022). Understanding adoption of artificial intelligence-enabled language e-learning system: An empirical study of UTAUT model.
International Journal of Mobile Learning and Organisation, 16(1), 74–94.
https://doi.org/10.1504/IJMLO.2022.119966
Lund, B., & Wang, T. (2023).
Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Social Science Research Network.
https://doi.org/10.2139/ssrn.4333415
Matlabi Nejad, A., Fazeli, F., & Navai, E. (2023). Systematic review of opportunities and challenges of artificial intelligence for teachers. Quarterly Journal of Technology and Knowledge Research in Education, 3(1), 23–44. [In Persian]
Mizumoto, A., & Eguchi, M. (2023). Exploring the potential of using an AI language model for automated essay scoring.
Research Methods in Applied Linguistics, 2(2), Article 100050.
https://doi.org/10.1016/j.rmal.2023.100050
Nagy, A. S., Tumiwa, J. R., Arie, F. V., & Erdey, L. (2024). An exploratory study of artificial intelligence adoption in higher education.
Cogent Education, 11(1), Article 2386892.
https://doi.org/10.1080/2331186X.2024.2386892
Ragheb, M. A., Tantawi, P., Farouk, N., & Hatata, A. (2022). Investigating the acceptance of applying chat-bot (Artificial intelligence) technology among higher education students in Egypt. International Journal of Higher Education Management, 8(2), 1–15.
Raquel Chocarro, M., Cortiñas, M., & Marcos-Matás, G. (2021). Teachers' attitudes towards chatbots in education: A technology acceptance model approach considering the effect of social language, bot proactiveness, and users' characteristics.
Educational Studies, 49(2), 295–313.
https://doi.org/10.1080/03055698.2020.1850426
Sallam, M. (2023).
The utility of ChatGPT as an example of large language models in healthcare education, research and practice: Systematic review on the future perspectives and potential limitations. medRxiv.
https://doi.org/10.1101/2023.02.19.23286155
Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2017). MLearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model.
Computers in Human Behavior, 72, 644–654.
https://doi.org/10.1016/j.chb.2016.09.061
Sanusi, I. T., Ayanwale, M. A., & Tolorunleke, A. E. (2024). Investigating pre-service teachers' artificial intelligence perception from the perspective of planned behavior theory.
Computers and Education: Artificial Intelligence, 6, Article 100202.
https://doi.org/10.1016/j.caeai.2024.100202
Taghvayi Yazdi, M., Golafshani, A., Aghamirzaei Mahalli, T., Aghatbar Roudbari, J., & Yousefi Saeidabadi, R. (2019). The status of ICT adoption and its impact on faculty members' performance.
Research in Medical Education, 11(2), 64–73.
https://sid.ir/paper/389040/fa [In Persian]
Thomas, J., Larsen, K. R., & Martin, F. (2018). The role of social facilitation and environmental support in technology acceptance. Journal of Social Research in Computer Sciences, 36(4), 102–120.
Tuomi, I. (2018).
The impact of artificial intelligence on learning, teaching, and education. Publications Office of the European Union.
https://doi.org/10.2760/12297
Wand, X., Li, L., Tan, S. C., Yang, L., & Lei, J. (2023). Preparing for AI-enhanced education: Conceptualizing and empirically examining teachers' AI readiness.
Computers in Human Behavior, 146, Article 107796.
https://doi.org/10.1016/j.chb.2023.107796
Wang, Y., Liu, C., & Tu, Y.-F. (2021). Factors affecting the adoption of AI-based applications in higher education: An analysis of teachers' perspectives using structural equation modeling. Educational Technology & Society, 24(3), 116–129.
Wang, Y., Wan, K., & Ren, Y. (2019). Research on factors influencing the acceptance of robot education for primary and secondary school teachers. Research in Visual Education, 40, 105–111.
Zakeri, A., Khajeh Lou, S. R., Afraei, H., & Zangooi, S. (2011). Teachers' attitudes toward the application of educational technologies in teaching.
Educational Technology (Technology and Education), 6(2), 159–165.
https://sid.ir/paper/155394/fa [In Persian]
Zanjani, M. A., Abedi, H., & Nazari Ghazvini, S. (2018). Factors influencing the intention to use social networks based on technology acceptance and social network cognition theories among users. In
National Conference on New and Creative Ideas in Management, Accounting, Legal and Social Studies.
https://sid.ir/paper/898279/fa [In Persian]