Hybrid MOOCs and the Future of Learning in the Age of Artificial Intelligence: Analysis and Identification of the Components of Students’ Learning Ecology

Authors
فاطمه شرزه‌ئی 1
Marjan Masoomifard 2
Nazila Khatibzanjani 3
Nasibeh Pourasghar 4
Mohammad Reza Sarmadi 5
1 PhD Graduate of Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran
2 Associate Professor, Department of Educational Sciences, Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran
3 Associate Professor, Department of Educational Sciences, Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran.
4 Assistant Professor, Department of Educational Sciences, Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran.
5 Professor, Department of Educational Sciences, Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran.
10.61838/KMAN.IRPHE.32.2.10
Abstract
Hybrid MOOCs, as a blended educational technology, provide a suitable platform for the application of artificial intelligence in higher education. This study was conducted with the aim of identifying the components of the students’ learning ecology in Hybrid MOOCs, using an inductive qualitative content analysis approach. The research population consisted of electronic documents and expert interviews; through purposive sampling, 41 studies and 7 experts were selected, and the data were collected. The data collection instruments were note-taking and semi-structured interviews. The data were coded and analyzed using MaxQDA software. The findings indicated that the six main categories of the students’ learning ecosystem include audience preparation, interactions, evaluation, course management, content management, and support, all of which can be effectively enhanced by artificial intelligence tools. Thus, Hybrid MOOCs, as a blended educational technology, provide an appropriate foundation for integrating artificial intelligence into higher education. It is recommended that macro-level educational policies be designed in such a way that the use of artificial intelligence is considered not merely as an auxiliary tool but as an integral part of the architecture of the learning ecosystem, with the necessary legal and infrastructural frameworks developed for its expansion.
Keywords
Artificial Intelligence
Hybrid MOOC
Connectivism
Learning Ecology
Massive Open Online Courses
Subjects
Alipour, N., Norouzi, D., & Nourian, M. (2021). Designing a model of key components affecting the quality of e-learning environments. Journal of Educational Technology, 15(3), 503-517.
Anders, A. (2015). Theories and applications of massive online open courses (MOOCs): The case for hybrid design. International Review of Research in Open and Distributed Learning, 16(6). https://doi.org/10.19173/irrodl.v16i6.2185
Ashrafi, S., Arasteh, H., Zeinabadi, H. R., & Abbasian, H. (2022). Analyzing the pedagogical requirements of implementing massive open online courses (MOOCs) at Payame Noor University. Journal of Research and Planning in Higher Education, 27(1), 51-87.
Ashrafi, S., Arasteh, H. R., Zeyn-Abadi, H. R., & Abbasian, H. (2020). Analyzing the implementation requirements of massive open online courses (MOOCs) at Payame Noor University from a technical and technological perspective. Journal of Educational Technology and Learning, 4(41). https://journal.irphe.ac.ir/article_703020_2930976ccf31ef0c71f78f7cb47e2d5d.pdf?lang=en
Ashrafi, S., & Hydarnejad, F. (2021). Identification of learners' readiness for massive open online courses (MOOCs). Information and Communication Technology in Educational Sciences, 45-66.
Buchem, I., & Okatan, E. (2021). Using the ADDIE model to produce MOOCs: Experiences from the Oberred Project. EMOOCs Conference, Germany.
Casiraghi, D., Sancassani, S., & Brambilla, F. (2021). The role of MOOCs in the new educational scenario: An integrated strategy for faculty development. EMOOCs Conference, Germany.
Chegini, H., Zangeneh, H., & Mohammadi, S. (2024). Improving higher education: Examining the impact of artificial intelligence on teaching-learning experiences for students. Journal of Research and Planning in Higher Education. https://doi.org/10.22034/irphe.2025.2022005.1141
Dortaj, F., Zarei Zavarki, E., & Aliabadi, K. (2017). Designing and validating a distance education model based on MOOCs for students. Quarterly Journal of Educational Psychology, 13(44), 38-108.
Farajollahi, M., Esmaeili, Z., Sarmadi, M. R., & Ghanbari, A. (2017). Designing a quality learning model based on Siemens' connectivism theory in distance education universities. Strides in Development of Medical Education, 14(3), 136.
Farzan, N., Shams, G., Rezai Zadeh, M., & Ghahrani, M. (2019). Identification of effective indicators in the design of mobile MOOC system for virtual training of employees. New Approach in Educational Management, 11(4).
García-Peñalvo, F. J., Fidalgo-Blanco, A., & Sein-Echaluce, M. L. (2017). An adaptive hybrid MOOC model: Disrupting the MOOC concept in higher education. Telematics and Informatics. https://doi.org/10.1016/j.tele.2017.09.012
Hosseini Moghadam, M. (2023). Artificial intelligence and the future of university education in Iran. Journal of Research and Planning in Higher Education, 29(1), 1-25. https://doi.org/10.61838/irphe.29.1.1
Huesman, D. A. (2019). Peer interaction in MOOCs for professional development University of Pennsylvania]. https://search.proquest.com/openview/8633319512e48458619e5c92e0c7570f/1?pq-origsite=gscholar&cbl=51922&diss=y
Jung, I. (2019). Open and distance education theory revisited: Implications for the digital era. Springer. https://doi.org/10.1007/978-981-13-7740-2
Kasch, J., Van Rosmalen, P., & Kalz, M. (2021). Educational scalability in MOOCs: Analysing instructional designs to find best practices. Computers & Education, 161, 104054. https://doi.org/10.1016/j.compedu.2020.104054
Khalil, M. (2021). Who are the students of MOOCs? Experience from learning analytics clustering techniques. EMOOCs Conference, Germany.
Koskinen, J., Kairikko, A., & Suonpää, M. (2021). Hybrid MOOCs enabling global collaboration between learners. EMOOCs Conference, Germany.
Koutsakas, P., Karagiannidis, C., Politis, P., & Karasavvidis, I. (2020). A computer programming hybrid MOOC for Greek secondary education. Smart Learning Environments, 7(7). https://doi.org/10.1186/s40561-020-0114-1
McMeans, M. (2021). How academic MOOC instructional designers select appropriate social media as design strategies Capella University]. https://search.proquest.com/openview/2531a4387826e31cabe32bc786e4178c/1?pq-origsite=gscholar&cbl=18750&diss=y
Mohamad, N., Othman, A., Tan, S. Y., & Rajah, N. (2021). The relationship between massive online open courses (MOOCs) content design and students' performance. International Journal of Interactive Mobile Technologies. https://doi.org/10.3991/ijim.v15i04.20201
Nardi, B. A., & O'Day, V. L. (1999). Information ecologies: Using technology with heart. MIT Press. https://doi.org/10.7551/mitpress/3767.001.0001
Naser Sheikholeslami, S. M., & Khatib Zanjani, N. (2020). Designing an optimal MOOC model for Payame Noor University Payame Noor University]. Tehran. https://edj.ajums.ac.ir/article_118724.html?lang=en
Ponce, E., Srinath, S., & Allegue, L. (2021). Integrating community teaching in MOOCs. EMOOCs Conference, Germany.
Rezaei, E., & Nasri, S. (2022). A model for designing interactive electronic content and educational simulations: A goal-based scenario. In Instructional design (Vol. 2). Ministry of Education, Office of Publications and Educational Technology.
Sargsyan, K. (2019). Knowledge management in adaptive learning systems. French University in Armenia.
Seng, C., Carlon, M. K., Gayed, J. M., & Cross, J. S. (2021). Long-term effects of short-term intervention using MOOCs for developing Cambodian undergraduate research skills. EMOOCs Conference, Germany.
Seyid Mohammadkhani, E., & Seyid Mohammadkhani, A. (2021). E-learning and education in schools. Azadi Qalam Publications.
Sharzehee, F., Khatib Zanjani, N., Masoumi Fard, M., Sarmadi, M. R., & Pourasghar, N. (2024). Identifying the components of a personalized learning environment in engineering education with HybridMOOC technology. Iranian Journal of Engineering Education, 26(101), 107-128. https://doi.org/10.22047/ijee.2024.424972.2026
Siemens, G. (2005). Connectivism: A learning theory for the digital age.
Siemens, G. (2017). Connectivism. In Foundations of learning and instructional design technology. Pressbooks. https://lidtfoundations.pressbooks.com/chapter/connectivism/
Sun, G., & Bin, S. (2018). Topic interaction model based on local community detection in MOOC discussion forums and its teaching application. Educational Sciences: Theory & Practice, 18(6), 2922-2931.
Tomkins, S., & Getoor, L. (2019). Understanding hybrid-MOOC effectiveness with a collective socio-behavioral model. Journal of Educational Data Mining, 11(3), 42-77. https://eric.ed.gov/?id=EJ1241619
Wang, M., & Owsiany, N. (2016). Design principles for massive open online courses (MOOCs). In. https://doi.org/10.3233/978-1-61499-690-3-169
Zhu, M. (2019). Designing MOOCs to facilitate participants' self-directed learning Indiana University].
 

  • Receive Date 17 June 2025
  • Revise Date 13 September 2025
  • Accept Date 20 September 2025
  • Publish Date 01 July 2026