تحول آفرینی هوش مصنوعی در تعالی آموزشی: واکاوی کاربردهای هوش مصنوعی با رویکردی آمیخته
محورهای موضوعی : هوش مصنوعی و رباتیکمونا جامی پور 1 * , الهه خطیبی نوری 2
1 - دانشگاه حضرت معصومه (س)
2 - گروه مدیریت، دانشکده مدیریت و حسابداری، دانشگاه حضرت معصومه (س)، قم، ایران
کلید واژه: هوش مصنوعی, آموزش الکترونیک, آموزش الکترونیک مبتنی بر هوش مصنوعی ,
چکیده مقاله :
در سالهای اخیر، هوش مصنوعی به یکی از مهمترین فناوریهای تحولآفرین در عرصه آموزش بدل شده و ظرفیتهای چشمگیری را برای ارائه خدمات آموزشی شخصیسازیشده و تعاملی فراهم کرده است. با توجه اهمیت بکارگیری چنین فناوریهای نوینی در حوزه آموزش، سرمایهگذاری در این حوزه به اولویتی استراتژیک برای موسسات آموزشی تبدیل شده است. به منظور اثربخشی سرمایهگذاریها، تصمیمگیرندگان میبایست درک روشنی از فرصتها و کاربردهای چنین فناوریهایی داشته باشند تا بهتر بتوانند جهتگیری ابتکارات مبتنی بر هوش مصنوعی در حوزه آموزش را همسو با اهداف کلان آموزشی سازند. علیرغم رشد محبوبیت مطالعات در این حوزه، طراحی چارچوبی یکپارچه از کاربردهای هوش مصنوعی در حوزه آموزشی که به واکاوی فرصتها و نیز اولویتبندی آنها پرداخته باشد مورد غفلت واقع شده است. لذا هدف اصلی پژوهش پرکردن شکاف تئوریک با رویکردی آمیخته میباشد که در مرحله اول، به منظور شناسایی و دستهبندی کاربردها علاوه بر مرور مطالعات این حوزه از روش کیفی گروه کانونی بهره گرفته شده است. در مرحله دوم، با استفاده از رویکرد کمی بهترین-بدترین به اولویتبندی کاربردهای شناسایی شده در مرحله قبل پرداخته شده است. یافتههای پژوهش نشان میدهد که چارچوب پیشنهادی پژوهش شامل سه لایه اصلی ابزارهای مبتنی بر هوش مصنوعی، کاربردها و ذینفعان میباشد. دستهبندی اصلی کاربردها به ترتیب اولویت عبارتند از آموزش و یادگیری شخصیسازیشده، ارتباطات و تعاملات هوشمند آموزشی، برنامهریزی مسیر آموزشی شخصیسازیشده، ارزیابی و بازخور هوشمند و مدیریت و اتوماسیون فرایندهای آموزشی. در این پژوهش با بهرهگیری رویکرد آمیخته علاوه بر استخراج تجارب بینالمللی و با بهرهگیری از جلسات گروه کانونی به واکاوی دانش بومی خبرگان پرداخته شده تا الگویی کلنگرانه از کاربردهای هوش مصنوعی در آموزش طراحی گردد و در نهایت به اولویتبندی آنها پرداخته شده که در ادبیات کمتر به آن پرداخته شده است. چارچوب پیشنهادی به عنوان ابزاری مدیریتی بصیرتی راهبردی برای تصمیمگیران و سیاستگذاران حوزه هوشمندسازی آموزش فراهم سازد.
In recent years, artificial intelligence (AI) has emerged as one of the most transformative technologies in education, offering significant opportunities for delivering personalized and interactive learning experiences. Given the growing importance of adopting such innovative technologies in education, investment in AI-enabled educational initiatives has become a strategic priority for educational institutions. To ensure the effectiveness of these investments, decision-makers require a comprehensive understanding of the opportunities and applications of AI in order to align AI-driven initiatives with broader educational objectives. Despite the increasing volume of research in this field, the development of an integrated framework that systematically identifies, categorizes, and prioritizes AI applications in education has received limited attention. Accordingly, the primary objective of this study is to address this theoretical gap through a mixed-methods approach. In the first phase, AI applications in education were identified and categorized through a comprehensive literature review and focus group discussions involving domain experts. In the second phase, the identified applications were prioritized using the Best-Worst Method (BWM). The findings reveal that the proposed framework comprises three primary layers: AI-based tools, application domains, and stakeholders. The identified application categories, ranked by priority, include personalized teaching and learning, communication and interaction, personalized educational planning, intelligent assessment and feedback, and educational management and process automation. By integrating international evidence from the literature with the contextual knowledge of experts obtained through focus group discussions, this study develops a holistic framework for understanding AI applications in education. Furthermore, it prioritizes these applications, an aspect that has been largely overlooked in previous studies. The proposed framework provides a strategic managerial tool that can support policymakers and educational decision-makers in advancing the intelligent transformation of educational systems.
[1] Chen, X., Xie, H., & Hwang, G. J. (2020). A multi-perspective study on artificial intelligence in education: Grants, conferences, journals, software tools, institutions, and researchers. Computers and Education: Artificial Intelligence, 1, 100005.
[2] Sajja, R., Sermet, Y., Cwiertny, D., & Demir, I. (2025). Integrating AI and learning analytics for data-driven pedagogical decisions and personalized interventions in education. Technology, knowledge and learning, 1-31.
[3] Birgün, M. (2026). Integrating AI into Qur'an learning: Technical advances and pedagogical gaps. Social Sciences & Humanities Open, 13, 102499.
[4] کاظمی راد، ام البنین، جامی پور، مونا و فقیهی، فاطمه، " واکاوی نقش هوش مصنوعی در حوزه حقوق: رویکردی اکتشافی"، دوفصلنامه فناوری اطلاعات و ارتباطات ایران، دوره 17، شماره 63، صص 1-18.
[5] Wang, T., & Cheng, E. C. K. (2021). An investigation of barriers to Hong Kong K-12 schools incorporating Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 2, 100031.
[6] Shaikh, A. A., Kumar, A., Jani, K., Mitra, S., García-Tadeo, D. A., & Devarajan, A. (2022). The role of machine learning and artificial intelligence for making a digital classroom and its sustainable impact on education during COVID-19. Materials Today: Proceedings, 56, 3211-3215.
[7] Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International journal of educational technology in higher education, 18(1), 54.
[8] Demandsage. (2026). 77 AI in Education Statistics 2026 (Global Trends & Facts), Available at: https://www.demandsage.com/ai-in-education-statistics/ (Accessed 17 April 2026).
[9] Hu, C., Li, F., Wang, S., Gao, Z., Pan, S., & Qing, M. (2025). The role of artificial intelligence in enhancing personalized learning pathways and clinical training in dental education. Cogent Education, 12(1), 2490425.
[10] Hadyaoui, A., & Cheniti-Belcadhi, L. (2026). Scalable adaptive assessment framework for collaborative eLearning: a service-oriented AI approach. Smart Learning Environments, 13(1), 8.
[11] Yetik, S. S. (2025). The Impact of Artificial Intelligence on University Teaching Processes: An Analysis Based on Faculty Perspectives. Kastamonu Education Journal, 33(3), 448-468.
[12] Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3, 100049.
[13] Hassan, A. (2026). Leveraging artificial intelligence (AI) to enhance student engagement and academic performance in higher education. Education and Information Technologies, 1-27.
[14] Wang, Q. (2026). Construction and Empirical Analysis of an Artificial Intelligence-Based Educational Assessment Model. International Journal of Information and Communication Technology Education (IJICTE), 22(1), 1-16.
[15] Tlili, A., Saqer, K., Salha, S., & Huang, R. (2025). Investigating the effect of artificial intelligence in education (AIEd) on learning achievement: A meta-analysis and research synthesis. Information Development, 41(3), 825-842.
[16] Kassenkhan, A. M., Moldagulova, A. N., & Serbin, V. V. (2025). Gamification and artificial intelligence in education: A review of innovative approaches to fostering critical thinking. IEEE Access.
[17] Trujillo, F., Pozo, M., & Suntaxi, G. (2025). Artificial Intelligence in Education: A Systematic Literature Review of Machine Learning Approaches in Student Career Prediction. Journal of Technology and Science Education, 15(1), 162-185.
[18] Garzón, J., Patiño, E., & Marulanda, C. (2025). Systematic review of artificial intelligence in education: Trends, benefits, and challenges. Multimodal Technologies and Interaction, 9(8), 84.
[19] Saputra, I., Astuti, M., Sayuti, M., & Kusumastuti, D. (2023). Integration of Artificial Intelligence in Education: Opportunities, Challenges, Threats and Obstacles. A Literature Review. The Indonesian journal of computer science, 12(4).
[20] 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), 39.
[21] Liang, J., Stephens, J. M., & Brown, G. T. (2025, April). A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment. In Frontiers in Education (Vol. 10, p. 1522841). Frontiers Media SA.
[22] Ait Baha, T., El Hajji, M., Es-Saady, Y., & Fadili, H. (2024). The impact of educational chatbot on student learning experience. Education and Information Technologies, 29(8), 10153-10176.
[23] Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success. Information Systems Frontiers, 25(1), 161-182.
[24] Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions. Computers and Education: Artificial Intelligence, 3, 100072.Abduljabbar, I. A., & Abdullah, S. M. (2022). An evolutionary algorithm for solving academic courses timetable scheduling problem. Baghdad Science Journal, 19(2), 11.
[25] Marrella, D., Anttila, T., Ryhänen, J., Miller, R., Liu, B., & Liverneaux, P. (2026). The balance between artificial and human intelligence in clinical practice. Journal of Hand Surgery (European Volume), 51(6), 685-697.
[26] Bešinović, N., De Donato, L., Flammini, F., Goverde, R. M., Lin, Z., Liu, R., ... & Vittorini, V. (2021). Artificial intelligence in railway transport: Taxonomy, regulations, and applications. IEEE Transactions on Intelligent Transportation Systems, 23(9), 14011-14024.
[27] Goel, A. K., & Polepeddi, L. (2018). Jill Watson. Learning engineering for online education: Theoretical contexts and design-based examples. Routledge.
[28] Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial intelligence in education: AIEd for personalised learning pathways. Electronic Journal of e-learning, 20(5), 639-653.
[29] Luckin, R. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, 1(3), 0028.
[30] Murphy, R. F. (2019). Artificial intelligence applications to support K-12 teachers and teaching. Rand Corporation, 10(1), 1-20.
[31] Karamuk, E. (2025). The automation trap: Unpacking the consequences of over-reliance on AI in education and its hidden costs. In Pitfalls of AI integration in education: Skill obsolescence, misuse, and bias (pp. 147-170). IGI Global Scientific Publishing.
[32] George, B., & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13(9), 196.Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252, 124167.
[33] Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252, 124167.
[34] Lima, G. D. O., Costa, J. A., Dorça, F. A., & Araújo, R. D. (2026). An AI‐Supported Pedagogical Architecture to Foster Self‐Regulated Learning in Virtual Environments. Computer Applications in Engineering Education, 34(1), e70118.
[35] Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54(5), 977-997.
[36] Li, X., & Jiang, Y. (2024). Artificial intelligence in education: Opportunities, current status, and prospects. Geographical Research Bulletin, 3, 146-174.
[37] Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000366994.pdf (Accessed 25 June 2026).
[38] Yurt, E., & Kasarci, I. (2024). A Questionnaire of Artificial Intelligence Use Motives: A contribution to investigating the connection between AI and motivation. International Journal of Technology in Education, 7(2).
[39] Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8, 100355.
[40] Liang, J., Wang, L., Luo, J., Yan, Y., & Fan, C. (2023). The relationship between student interaction with generative artificial intelligence and learning achievement: serial mediating roles of self-efficacy and cognitive engagement. Frontiers in psychology, 14, 1285392.
[41] Liu, X., & Zhong, B. (2025). Integrating generative Artificial Intelligence into student learning: A systematic review from a TPACK perspective. Educational Research Review, 100741.
[42] 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.
[43] Dong, L., Tang, X., & Wang, X. (2025). Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis. Computers and Education: Artificial Intelligence, 8, 100400.
[44] Hwang, S. (2022). Examining the effects of artificial intelligence on elementary students’ mathematics achievement: A meta-analysis. Sustainability, 14(20), 13185.
[45] Oran, B. B. (2023). Correlation between artificial intelligence in education and teacher self-efficacy beliefs: A review. RumeliDE Dil ve Edebiyat Araştırmaları Dergisi, (34), 1354-1365.
[46] Hennink, M., & Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social science & medicine, 292, 114523.
[47] Castro-Schez, J. J., Glez-Morcillo, C., Albusac, J., & Vallejo, D. (2021). An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning. Information Sciences, 544, 446-468.
[48] Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), 37.
[49] 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.
[50] Bhutoria, A. (2022). Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model. Computers and Education: Artificial Intelligence, 3, 100068.
[51] Embarak, O. H. (2022). Internet of Behaviour (IoB)-based AI models for personalized smart education systems. Procedia Computer Science, 203, 103-110.
[52] Muangprathub, J., Boonjing, V., & Chamnongthai, K. (2020). Learning recommendation with formal concept analysis for intelligent tutoring system. Heliyon, 6(10).
[53] Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., ... & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence, 3, 100075.
[54] Qin, Y., Huang, Z., Yu, J., Qing, P., Lui, S., Liu, R., ... & Hu, N. (2022). Practice-based learning using smart class: a competency-based model in undergraduate radiology education. Academic Radiology, 29(1), 150-157.
[55] Abduljabbar, I. A., & Abdullah, S. M. (2022). An evolutionary algorithm for solving academic courses timetable scheduling problem. Baghdad Science Journal, 19(2), 11.
[56] Ghaffar, A., Din, I. U., Tariq, A., & Zafar, M. H. (2025). Hybridization and artificial intelligence in optimizing university examination timetabling problem: A systematic review. Review of Education, 13(2), e70071.
[57] Gao, P. P., Nagel, A., & Biedermann, H. (2020). Categorization of Educational Technologies as Related to. Pedagogy in basic and higher education: Current developments and challenges, 167.
[58] Yim, I. H. Y., & Su, J. (2025). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. Journal of Computers in Education, 12(1), 93-131.
[59] Bh, M. P., Yellapurkar, S., Chengappa, K., & Pentapati, K. C. (2026). Personalized Learning With Artificial Intelligence in Dental Education: An Integrative Review. International Journal of Dentistry, 2026(1), 8928166.
[60] Amin, M. R. M., Ismail, I., & Sivakumaran, V. M. (2025). Revolutionizing education with artificial intelligence (AI)? Challenges, and implications for open and distance learning (ODL). Social Sciences & Humanities Open, 11, 101308.
[61] Katalinic, A., Slavuj, V., & Jaksic, D. (2026). Artificial Intelligence in online education: A systematic review of its impact on learner engagement and satisfaction. Education sciences, 16(3), 389.
[62] Brada, A., & Dahmani, F. (2024). Artificial intelligence technologies and their significance in enhancing the quality of adaptive e-learning. Journal of Science and Knowledge Horizons, 4(02), 30-47.
[63] Ahmed, S., Rahman, M. S., Kaiser, M. S., & Hosen, A. S. (2025). Advancing personalized and inclusive education for students with disability through artificial intelligence: perspectives, challenges, and opportunities. Digital, 5(2), 11.