| تعداد نشریات | 32 |
| تعداد شمارهها | 522 |
| تعداد مقالات | 5,085 |
| تعداد مشاهده مقاله | 7,797,488 |
| تعداد دریافت فایل اصل مقاله | 5,802,991 |
فرصتها، چالشها و راهکارهای کاربست هوش مصنوعی در آموزشعالی ایران از منظر خبرگان | ||
| مطالعات برنامه ریزی آموزشی | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 17 آذر 1404 | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22080/eps.2025.29736.2359 | ||
| نویسندگان | ||
| محمد آتشک* 1؛ لیلا خسروی مراد2 | ||
| 1استاد یار، دپارتمان تحقیقات در مدیریت، دانشکده مرکز آموزش مدیریت دولتی، تهران، ایران | ||
| 2دانشجوی دکتری حکمرانی آموزش عالی، دانشگاه تهران. ایران | ||
| تاریخ دریافت: 06 مرداد 1404، تاریخ بازنگری: 17 آبان 1404، تاریخ پذیرش: 17 آذر 1404 | ||
| چکیده | ||
| هدف: در دهههای اخیر، گسترش هوش مصنوعی (AI) فرصتهای جدیدی برای تحول در برنامهریزی درسی آموزش عالی ایجاد کرده است. با وجود اهمیت روزافزون این فناوری در بهبود کیفیت آموزش و یادگیری، استفاده مؤثر از آن در سیستم آموزش عالی ایران با موانع ساختاری، فرهنگی و سیاستی مواجه است. این تحقیق به شناسایی فرصتها، چالشها و استراتژیهای کاربرد هوش مصنوعی در برنامهریزی درسی آموزش عالی در ایران از دیدگاه کارشناسان میپردازد. روششناسی: این مطالعه کیفی از تحلیل تماتیک استفاده میکند تا فرصتها، چالشها و استراتژیهای کاربرد هوش مصنوعی در آموزش عالی ایران را شناسایی کند. شرکتکنندگان شامل حرفهایهایی با حداقل پنج سال تجربه مرتبط در آموزش عالی و برنامهریزی آموزشی بودند. نمونهگیری هدفمند برای اطمینان از تنوع نمایندگی در دانشگاههای دولتی و خصوصی و رشتههای مختلف انجام شد. مصاحبههای نیمهساختاریافته با دوازده کارشناس تا رسیدن به اشباع نظری انجام شد. تحلیل دادهها با استفاده از مدل شش مرحلهای تحلیل تماتیک و با اطمینان از اعتبار از طریق تأیید اعضا و بررسی همتا صورت گرفت. نتایج: یافتهها نشان میدهد که فرصتهای کاربرد هوش مصنوعی در آموزش عالی ایران شامل بهبود تجربه یادگیری از طریق یادگیری شخصی و بهبود فرآیندهای آموزشی از طریق نظارت هوشمند است. با این حال، چالشها در ابعاد مختلف شناسایی شدند: محدودیتهای زیرساختی، ناهماهنگی در آموزش اساتید، نگرانیهای اخلاقی و مسائل مربوط به مسئولیت و نظارت. استراتژیهای پیشنهادی برای ادغام مؤثر هوش مصنوعی شامل توسعه سریع زیرساختها، ترویج یکپارچگی علمی، ایجاد پلتفرمهای یادگیری شخصی و اطمینان از استقرار اخلاقی AI است. نتیجهگیری و پیشنهادات: این مطالعه نتیجهگیری میکند که هوش مصنوعی فرصتها و چالشهای متنوعی برای سیستم آموزش عالی ایران ارائه میدهد. پرداختن به این مسائل نیازمند اصلاحات جامع در سیاستها و استراتژیهای ذینفعان است. تخصیص منابع کافی و همکاری بینسازمانی برای موفقیت در ادغام هوش مصنوعی ضروری است. نوآوری و اصالت: اصالت این مطالعه در طراحی کیفی آن، مشارکت کارشناسان و ادغام ادبیات نظری با یافتههای تجربی برای ارائه راهحلهای عملی و قابل اجرا نهفته است. | ||
| کلیدواژهها | ||
| هوش مصنوعی؛ آموزش عالی؛ برنامهریزی آموزشی؛ سیاستگذاری آموزشی؛ نوآوری آموزشی | ||
| عنوان مقاله [English] | ||
| Opportunities, Challenges and Solutions for Applying Artificial Intelligence in Iranian Higher Education from the Perspective of Experts | ||
| نویسندگان [English] | ||
| mohammad atashak1؛ Leyla Khosravi Morad2 | ||
| 1Assistant Professor, Department of Research in management, Faculty of Statae Mamnagement Training Center, Tehran, Iran | ||
| 2Ph.D. in higher education governance, TehranUniversity, Tehran, Iran | ||
| چکیده [English] | ||
| Aim: In recent decades, the expansion of Artificial Intelligence (AI) has created new opportunities for transformation in higher education curriculum planning. Despite the growing importance of this technology in enhancing teaching and learning quality, its effective utilization in Iran’s higher education system faces various structural, cultural, and policy barriers. This research aims to identify the opportunities, challenges, and strategies for the application of AI in higher education curriculum planning in Iran from the perspective of experts. Methodology: This qualitative study employs thematic analysis to identify opportunities, challenges, and strategies for applying AI in Iranian higher education. Participants included professionals with at least five years of relevant experience in higher education and educational planning. Purposive sampling was used to ensure diverse representation across public and private universities and various disciplines. Semi-structured interviews were conducted with twelve experts until theoretical saturation was reached. Data analysis followed a six-phase thematic analysis model, ensuring credibility through member checking and peer debriefing. Results: Findings reveal that opportunities for AI application in Iranian higher education include enhancing the learning experience through personalized learning and improving educational processes via intelligent monitoring. However, challenges were identified across several dimensions: infrastructure-related limitations, inconsistencies in faculty training, ethical concerns, and issues of accountability and supervision. Proposed strategies for effective AI integration encompass rapid infrastructure development, fostering academic integrity, creating personalized learning platforms, and ensuring ethical deployment of AI. Conclusions and suggestions: The study concludes that AI presents diverse opportunities and challenges for Iran’s higher education system. Addressing these requires comprehensive policy revisions and strategic adaptation by stakeholders. Adequate resource allocation and cross-sector collaboration are essential for the successful integration of AI. Innovation and originality: The originality of this study lies in its qualitative design, expert involvement, and integration of theoretical literature with empirical findings to provide practical solutions. | ||
| کلیدواژهها [English] | ||
| Artificial Intelligence, Higher Education, Educational Planning, Educational Policy-making, Educational Innovation | ||
| مراجع | ||
|
Abedi Jafari, H., Taslimi, M. S., Faghihi, A., & Sheikhzadeh, M. (2011). Thematic analysis and network of themes: A simple and efficient method for explaining existing patterns in qualitative data. Strategic Management Thought, 5(2). [in Persian] Al Ka’bi, A. (2023). Proposed artificial intelligence algorithm and deep learning techniques for development of higher education. International Journal of Intelligent Networks, 4, 68–73. https://doi.org/10.1016/j.ijin.2023.03.002 (ouci.dntb.gov.ua) Alqahtani, T., Badreldin, H. A., Alrashed, M., Alshaya, A. I., Alghamdi, S. S., Bin Saleh, K., & Albekairy, A. M. (2023). The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research. Research in Social and Administrative Pharmacy, 19(8), 1236–1242. https://doi.org/10.1016/j.sapharm.2023.05.016 (CoLab). Bailey, K. D. (1994). Methods of social research (3rd ed.). New York, NY: Free Press. Braun, V. & Clarke, V. (2006), Using thematic analysis in psychology, Qualitative Research in Psychology, 3, 77-101. Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education: Contributors, collaborations, research topics, challenges, and future directions. Educational Technology & Society, 25(1), 28–47. https://doi.org/10.1007/s10639-022-11209-y (ojs.amhinternational.com) Chiu, T. K., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers & Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118 (DergiPark) Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00426-1 Dogan, M. E., Goru Dogan, T., & Bozkurt, A. (2023). The use of artificial intelligence (AI) in online learning and distance education processes: A systematic review of empirical studies. Applied Sciences, 13(5), 3056. https://doi.org/10.3390/app13053056 Donoso Vargas, D. J., & Gallardo Cornejo, A. M. (2024). Closing the gap: Application of AI and Bayesian statistics to traditional training in educational leadership. European Public & Social Innovation Review, 9, 1–19. https://doi.org/10.31637/epsir-2024-916 Farrelly, T., & Baker, N. (2023). Generative artificial intelligence: Implications and considerations for higher education practice. Education Sciences, 13(11), 1109. https://doi.org/10.3390/educsci13111109 George, B., & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13(9), 196. https://doi.org/10.3390/admsci13090196 Hamdi Nasab, S., & Rahimi, S. (2024). Barriers and challenges of implementing artificial intelligence in higher education system. Educational Planning Studies, 13(26), 57–73. https://doi.org/10.22080/eps.2025.28149.2295 [in Persian] https://doi.org/10.10000/stemedu.2023.3.4.288 https://doi.org/10.3390/app13116716 Imran, M., Almusharraf, N., Abdellatif, M. S., & Abbasova, M. Y. (2024). Artificial intelligence in higher education: Enhancing learning systems and transforming educational paradigms. International Journal of Interactive Mobile Technologies, 18(18). https://doi.org/10.3991/ijim.v18i18.??? Khajeh, H., & Ayati, M. (2025). An analysis of the reductive and augmentative aspects of AI chatbots and their multiple applications in higher education: A post-phenomenological approach. Educational Planning Studies, 14(27), 211–236. https://doi.org/10.22080/eps.2025.29615.2355 [in Persian] King, M. R., & ChatGPT. (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and Molecular Bioengineering, 16(1), 1–2. https://doi.org/10.1007/s12195-023-00905-x Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). Exploring generative artificial intelligence preparedness among university language instructors: A case study. Computers & Education: Artificial Intelligence, 5, 100156. https://doi.org/10.1016/j.caeai.2023.100156 Malinka, K., Peresíni, M., Firc, A., Hujnák, O., & Janus, F. (2023, June). On the educational impact of ChatGPT: Is artificial intelligence ready to obtain a university degree? In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V (Vol. 1, pp. 47–53). McGrath, C., Pargman, T. C., Juth, N., & Palmgren, P. J. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education – An experimental philosophical study. Computers & Education: Artificial Intelligence, 4, 100139. https://doi://doi.org/10.1016/j.caeai.2022.100139 Memarian, B., & Doleck, T. (2023). Fairness, accountability, transparency, and ethics (FATE) in artificial intelligence (AI), and higher education: A systematic review. Computers & Education: Artificial Intelligence, 100152. https://doi.org/10.1016/j.caeai.2023.100152 O’Dea, X. C., & O’Dea, M. (2023). Is artificial intelligence really the next big thing in learning and teaching in higher education? A conceptual paper. Journal of University Teaching and Learning Practice, 20(5). https://doi.org/10.53761/10.53761/jutlp.2023.20.5.??? Ocaña-Fernández, Y., Valenzuela-Fernández, L. A., & Garro-Aburto, L. L. (2019). Artificial intelligence and its implications in higher education. Journal of Educational Psychology–Propósitos y Representaciones, 7(2), 553–568. https://doi.org/10.20511/edus eurj v7n2-2019-1173 Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6), 7893–7925. https://doi.org/10.1007/s10639-022-11111-x Saaida, M. B. (2023). AI-driven transformations in higher education: Opportunities and challenges. International Journal of Educational Research and Studies, 5(1), 29–36. https://doi.org/10.20000/ijers.2023.5.1.⁎ Sabzipour, A., Moghaddas, S., & Jadidi Mohammadabadi, A. (2025). The role of artificial intelligence in predicting educational trends. Educational Planning Studies, 14(27), 191–210. https://doi.org/10.22080/eps.2025.28851.2331 [in Persian] Sabzipour, A., Moghaddas, S., & Jadidi Mohammadabadi, A. (2025). The role of artificial intelligence in predicting educational trends. Educational Planning Studies, 14(27), 191–210. https://doi.org/10.22080/eps.2025.28851.2331 [Duplicate entry – same as above] [in Persian] Saki, S., Zeinabadi, H. R., Abbasian, H., & Abdollahi, B. (2025). Faculty members’ perspectives on the use of artificial intelligence in teaching in Iran’s higher education system. Educational Planning Studies, 14(27), 170–191. https://doi.org/10.22080/eps.2025.28831.2330 [in Persian] Shanto, S. S., Ahmed, Z., & Jony, A. I. (2023). PAIGE: A generative AI-based framework for promoting assignment integrity in higher education. STEM Education, 3(4), 288–305. Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Grounded theory procedures and techniques (B. Mohammadi, Trans.). Tehran, Iran: Humanities and Cultural Studies Research Institute. [In Persian]
Talan, T., & Kalınkara, Y. (2023). The role of artificial intelligence in higher education: ChatGPT assessment for anatomy course. Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi, 7(1), 33–40. https://doi.org/10.53761/10.53761/uybisim-2023.7.1.33 Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential impact of artificial intelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences, 13(11), 6716. 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(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0 Zouhaier, S. (2023). The impact of artificial intelligence on higher education: An empirical study. European Journal of Educational Sciences, 10(1), 17–33. https://doi.org/10.20319/ejesc.2023.10.1.17 | ||
|
آمار تعداد مشاهده مقاله: 0 |
||