معرفی و اعتباریابی مقیاس ادراک معلمان از کاربرد هوش مصنوعی در آموزش | ||
| پژوهش در روشهای آموزش | ||
| دوره 3، شماره 5 - شماره پیاپی 13، اسفند 1404، صفحه 214-231 اصل مقاله (1.57 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22091/jrim.2025.13695.1361 | ||
| نویسندگان | ||
| آزاد الله کرمی1؛ خلیل زندی2؛ زهرا معارف وند* 3 | ||
| 1استادیار، گروه آموزشی علوم تربیتی، دانشگاه فرهنگیان، تهران، ایران. | ||
| 2استادیار، گروه مدیریت آموزشی، دانشگاه فرهنگیان، تهران، ایران | ||
| 3استادیار، گروه علوم تربیتی، دانشکده ادبیات و علوم انسانی، دانشگاه قم، قم، ایران | ||
| چکیده | ||
| هدف از این پژوهش معرفی و اعتباریابی ابزار سنجش «ادراک معلمان از کاربرد هوش مصنوعی در آموزش» بود. روش پژوهش، توصیفی پیمایشی بود. جامعه آماری، دانشجومعلمان سال سوم و چهارم دانشگاه فرهنگیان استان کردستان بودند. با استفاده از روش نمونهگیری دردسترس، نمونهای به حجم 321 نفر انتخاب شد. ابزار گردآوری دادهها مقیاس 15 مادهای ادراک معلمان از کاربرد هوش مصنوعی در آموزش بود که توسط اوزوم و همکاران (Üzüm & et al., 2025) تدوین شده است. تجزیه و تحلیل دادهها با استفاده از تحلیل عاملی اکتشافی، تحلیل عاملی تأییدی، ضریب آلفای کرونباخ و آزمون t تک نمونهای انجام شد. نتایج تحلیل عاملی اکتشافی نشان داد که نسخه فارسی مقیاس دقیقاً مشابه با ساختار عاملی نسخه اصلی، قابل تقلیل به سه زیرمقیاس است. بنابراین به پیروی از نسخه اصلی، این زیرمقیاسها به ترتیب «ادراک از تدریس»، «ادراک از یادگیری» و «ادراک از مسائل اخلاقی» نام نهاده شدند. نتایج تحلیل عاملی تأییدی نیز بیانگر برازش خوب مدل سهبعدی ادراک معلمان از کاربرد هوش مصنوعی در آموزش بود. نتایج بررسی پایایی نشان داد که پایایی کل مقیاس با ضریب 89/0 تأیید میشود. پایایی زیرمقیاسها نیز در دامنه 75/0 تا 89/0 بود. سایر یافتهها بیانگر ادراک مثبت افراد نمونه از کاربرد هوش مصنوعی در آموزش بود. بر مبنای یافتههای پژوهش، نسخه فارسی مقیاس ادراک معلمان از کاربرد هوش مصنوعی در آموزش در نمونه ایرانی مورد مطالعه دارای روایی و پایایی مناسبی است و میتوان از این ابزار در پژوهشهای آتی استفاده نمود. | ||
تازه های تحقیق | ||
پژوهش حاضر با هدف اعتباریابی مقیاس ادراک معلمان از کاربرد هوش مصنوعی در آموزش بر اساس مدل سه بعدی اوزوم و همکاران (Üzüm & et al., 2025) انجام گرفت. یافتهها نشان داد که نسخه فارسی مقیاس از روایی و پایایی خوبی در میان نمونه دانشجویان ایرانی برخوردار است. بهطور مشخص نتایج تحلیل عاملی تأییدی، ساختار سهبعدی مقیاس اصلی شامل زیرمقیاسهای «ادراک از تدریس»، «ادراک از یادگیری» و «ادراک از مسائل اخلاقی» و 15 آیتم آن را تأیید نمود. نتایج بررسی پایایی نیز نشان داد که همه زیرمقیاسها از پایایی بسیار خوبی (α=0.74-0.88)برخوردار بودند و پایایی کل مقیاس(α=0.89) نیز عالی بود. همه آیتمهای پرسشنامه دارای بار عاملی بالاتر از 4/0 بودند که نشان میدهد این گویهها شاخصهای معتبری برای سنجش سازه ادراک معلمان از کاربرد هوش مصنوعی در آموزش محسوب میشوند. از میان زیرمقیاسها مقدار ویژه مؤلفه «ادراک از تدریس» برابر با 16/4 است که با 74/27 درصد بیشترین تبیین را از واریانس کل انجام میدهد. این مؤلفه بیش از دو مؤلفه دیگر توانست توصیف کننده ادراک دانشجو معلمان از کاربرد هوش مصنوعی در آموزش باشد که البته این یافته با تعاریف ارائه شده از ادراک از کاربرد هوش مصنوعی سازگار است. | ||
| کلیدواژهها | ||
| هوش مصنوعی؛ آموزش؛ تدریس؛ یادگیری؛ ادراک | ||
| عنوان مقاله [English] | ||
| Introduction and Validation of a Scale Assessing Teachers' Perceptions of the Use of Artificial Intelligence in Education | ||
| نویسندگان [English] | ||
| Azad Allah Karami1؛ Khalil Zandi2؛ Zahra Maarefvand3 | ||
| 1Assistant Professor, Department of Educatiinal Sciences, Farhangian University, Tehran, Iran | ||
| 2Assistant Professor, Department of Educatiinal Sciences, Farhangian University, Tehran, Iran | ||
| 3Assistant Professor, Department of Educational Sciences, Faculty of Literature and Humanities, University of Qom, Qom, Iran | ||
| چکیده [English] | ||
| The aim of this study was to introduce and validate the measurement tool "Teachers' Perception of the Use of Artificial Intelligence in Education". The research method was a descriptive survey. The statistical population was third and fourth year student teachers of Farhangian University of Kurdistan Province. Using the available sampling method, a sample of 321 people was selected. The data collection tool was the 15-item scale of teachers' perception of the use of artificial intelligence in education, which was developed by Ozum et al. (2025). Data analysis was performed using exploratory factor analysis, confirmatory factor analysis, Cronbach's alpha coefficient, and one-sample t-test. The results of the exploratory factor analysis showed that the Persian version of the scale is exactly the same as the factor structure of the original version, which can be reduced to three subscales. Therefore, following the original version, these subscales were named “Perception of Teaching”, “Perception of Learning” and “Perception of Ethical Issues”, respectively. The results of confirmatory factor analysis also indicated a good fit of the three-dimensional model of teachers’ perception of the use of AI in education. The results of the reliability study showed that the reliability of the entire scale was confirmed with a coefficient of 0.89. The reliability of the subscales was also in the range of 0.75 to 0.89. Other findings indicated the positive perception of the sample individuals of the use of AI in education. Based on the research findings, the Persian version of the Teachers’ Perception of the Use of AI in Education Scale in the Iranian sample studied has appropriate validity and reliability, and this tool can be used in future research. | ||
| کلیدواژهها [English] | ||
| artificial intelligence, education, teaching, learning, perception | ||
| مراجع | ||
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Abdulhakovna, E.D. (2025). The Essence of Integrating Artificial Intelligence into The Education System. International Journal of Pedagogics. https://doi.org/10.37547/ijp/volume05issue04-65 Abyaz, A. A. (2024). The role of artificial intelligence in transforming the primary education system: Examining challenges and providing practical solutions. The 2nd International Conference on Modern Research in Education and Schools with a Perspective on Progress and Development, Bu-Ali Sina Research Association, Hamedan, Iran. Ahuja, V. (2019). Artificial intelligence (AI) in drug discovery and medicine. J Clin Cases Rep, 2(3), 76-80. https://doi.org/10.46619/joccr.2019.2-1043 Ali, M., Rehman, S., & Cheema, E. (2025). Impact of artificial intelligence on the academic performance and test anxiety of pharmacy students in objective structured clinical examination: a randomized controlled trial. International Journal of Clinical Pharmacy, 1-8. https://doi.org/10.1007/s11096-025-01876-5 Amofa, B., Kamudyariwa, X. B., Fernandes, F. A. P., Osobajo, O. A., Jeremiah, F., & Oke, A. (2025). Navigating the Complexity of Generative Artificial Intelligence in Higher Education: A Systematic Literature Review. Education Sciences, 15(7), 826. https://doi.org/10.3390/educsci15070826 Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(5), 616–630. https://doi.org/10.1007/s11528-022-00715-y Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510 Dameruppula, S. (2025). The Evolution and Impact of Artificial Intelligence and Machine Learning: A Technical Overview. International Journal of Advanced Research in Science, Communication and Technology. https://doi.org/10.48175/ijarsct-24609 Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). Technology acceptance model. J Manag Sci, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982 Deci, E. L., & Ryan, R. M. (2012). Self-determination theory. Handbook of theories of social psychology, 1(20), 416-436. Derinalp, P., & Ozyurt, M. (2024). Adaptation of the Student Attitudes Toward Artificial Intelligence Scale to the Turkish Context: Validity and Reliability Study. International Journal of Human–Computer Interaction, 41(8), 4653–4667. https://doi.org/10.1080/10447318.2024.2352921 Fahreni, R., Ali, H. S., & Daud, A. (2024). Teachers’ perspective on the use of artificial intelligence in teaching and learning process: A systematic literature review. Scope: Journal of English Language Teaching, 9(1), 417-423. https://doi.org/10.30998/scope.v9i1.21785 Falebita, O. S., & Kok, P. J. (2024). Artificial intelligence tools usage: A structural equation modeling of undergraduates’ technological readiness, self-efficacy and attitudes. Journal for STEM Education Research, 1-26. https://doi.org/10.1007/s41979-024-00132-1 Gayed, J. M. (2025). Educators’ perspective on artificial intelligence: equity, preparedness, and development. Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2024.2447169 Gómez Cano, C. A., & Colala Troya, A. L. (2023). Artificial Intelligence applied to teaching and learning processes. 1, 2. https://doi.org/10.62486/latia20232 Grassini, S. (2023). Development and validation of the AI Attitude Scale (AIAS-4): A brief measure of general attitude toward artificial intelligence. Frontiers in Psychology, 14, 1191628. https://doi.org/10.3389/fpsyg.2023.1191628 Javaid, M., Haleem, A., Singh, R. P., Khan, S., & Khan, I. H. (2023). Unlocking the opportunities through ChatGPT tool towards ameliorating the education system. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 3(2), 100115. https://doi.org/10.1016/j.tbench.2023.100115 Yilmaz, F. G. K., Yilmaz, R., & Ceylan, M. (2024). Generative artificial intelligence acceptance scale: A validity and reliability study. International Journal of Human–Computer Interaction, 40(24), 8703-8715. https://doi.org/10.1080/10447318.2023.2288730 Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir-Kaya, M. (2022). The roles of personality traits, AI anxiety, and demographic factors in attitudes toward artificial intelligence. International Journal of Human–Computer Interaction, 40(2), 497–514. https://doi.org/10.1080/10447318.2022.2151730 Kieslich, K., Lünich, M., & Marcinkowski, F. (2021). The threats of artificial intelligence scale (TAI): Development, measurement, and test over three application domains. International Journal of Social Robotics, 13(7), 1563–1577. https://doi.org/10.1007/s12369-020-00734-w Lee, Y. J., Davis, R. O., & Ryu, J. (2024). Korean in-service teachers’ perceptions of implementing artificial intelligence (AI) education for teaching in schools and their AI teacher training programs. International Journal of Information and Education Technology, 14(2), 214-219.https://doi.org/10.18178/ijiet.2024.14.2.2042 Majkić, Z., & Vranješ, D. (2024). The Integration of Artificial Intelligence across Educational Levels: From Primary School to University. 10th International Scientific Conference Technics, Informatic, and Education. https://doi.org/10.46793/tie24.391m Moor, J. H. (2005). Why we need better ethics for emerging technologies. Ethics and information technology, 7(3), 111-119. https://doi.org/ 10.1007/s10676-006-0008-0 Morales-García, W.C., Sairitupa-Sanchez, L.Z., Morales-García, S.B., & Morales-García, M. (2024). Adaptation and psychometric properties of a brief version of the general self-efficacy scale for use with artificial intelligence (GSE-6AI) among university students. Frontiers in Education. https://doi.org/10.3389/feduc.2024.1293437 Muggleton, S. (2014). Alan Turing and the development of Artificial Intelligence. AI communications, 27(1), 3-10. https://doi.org/10.3233/AIC-130579 Nasni Naseri, R.N., & Abdullah, R.N. (2025). Transforming Education with AI: Insights from Developed Countries. International Journal of Research and Innovation in Social Science. https://doi.org/10.47772/ijriss.2025.90300308 Obschonka, M., & Audretsch, D. B. (2020). Artificial intelligence and big data in entrepreneurship: A new era has begun. Small Business Economics, 55(2), 529–539. https://doi.org/10.1007/s11187-019-00202-4 Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia journal of mathematics, science and technology education, 19(8), em2307. https://doi.org/10.29333/ejmste/13428 Panigrahi, A., & Joshi, V. (2020). Use of Artificial Intelligence in Education. The Management Accountant Journal, 55(5), 64–67. https://doi.org/10.33516/maj.v55i5.64-67p Panjani, H., & Mudgal, P.D. (2024). AI(Artificial Intelligence) Integration in Education: Teachers’ Perspectives, Professional Development and Policy Recommendations. Journal of Information Systems Engineering and Management. https://doi.org/10.52783/jisem.v9i4s.10602 Polydoros, G., Galitskaya, V., Pergantis, P., Drigas, A., Antoniou, A. S., & Beazidou, E. (2025). Innovative AI-Driven Approaches to Mitigate Math Anxiety and Enhance Resilience Among Students with Persistently Low Performance in Mathematics. Psychology International, 7(2), 46. https://doi.org/10.3390/psycholint7020046 Rajabiyan Dehzireh, M. (2024). Identifying the challenges and capabilities of artificial intelligence in teaching and learning by providing solutions. Technical Education Journal, 18(4), 921-950. https://doi.org/10.22061/tej.2024.10777.3058 [In Persian]. Rashid, A. B., & Kausik, M. A. K. (2024). AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications. Hybrid Advances, 7, 100277. https://doi.org/10.1016/j.hybadv.2024.100277 Rostaminezhad, M. A., & Khajeh, H. (2025). A phenomenological analysis of primary school teachers' perception of ChatGPT integration in education. Journal of Educational Planning and Studies, 13(26), 198-220. https://doi.org/10.22080/eps.2025.28671.2322 [In Persian]. Sachdeva, A. (2023). Artificial intelligence in dentistry-a literature review. Biomedical Journal of Scientific & Technical Research, 51(1), 42323-42326. DOI: 10.26717/BJSTR.2023.51.008050 Schellenberg, S. (2018). The Unity of Perception. Oxford Scholarship Online https://doi.org/10.1093/OSO/9780198827702.001.0001 Singh, G., & Thakur, A. (2024). AI in education: Ethical challenges and opportunities. In The ethical frontier of AI and data analysis (pp. 21). IGI Global. https://doi.org/10.4018/979-8-3693-2964-1.ch002 Stankovski, S., & Ostojić, G. (2024). How ready are we to apply artificial intelligence? Veštačka inteligencija-praktična primena i izazovi, (Papers), 109-118. https://doi.org/10.5937/vi24109s Toivanen, J. (2018). Perceptual Experience: Assembling a medieval puzzle. In Philosophy of Mind in the Early and High Middle Ages (pp. 134-156). Routledge.https://doi.org/10.4324/9780429508196-7 Üzüm, B., Elçiçek, M., & Pesen, A. (2025). Development of teachers’ perception scale regarding artificial intelligence use in education: validity and reliability study. International Journal of Human–Computer Interaction, 41(5), 2776-2787. https://doi.org/10.1080/10447318.2024.2385518. Vančová, H. (2023). AI and AI-powered tools for pronunciation training. Journal of Language and Cultural Education, 11(3), 12–24. https://doi.org/10.2478/jolace-2023-0022 Wang, B., Rau, P. L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768 Wang, Y. Y., & Chuang, Y. W. (2023). Artificial intelligence self-efficacy: Scale development and validation. Education and Information Technologies, 29(4), 4785–4808. https://doi.org/10.1007/s10639-023-12015-w Zencirli, B. T., & Altin, M. (2025). The impact of artificial intelligence on workplace dehumanization: a critical review. Journal of Hospitality and Tourism Horizons, 1 (2): 128–149. https://doi.org/10.1108/JHTH-01-2025-0014 Zhou, C. (2024). Teacher’s Perceptions of Applying Artificial Intelligence in Education: A Systematic Review. World J Soc Sci Res, 11(3), 62-72. https://doi.org/10.22158/wjssr.v11n3p62 | ||
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