The transformation of mooc-based online courses through artificial intelligence: personalization, data analytics, and modern digital education

In recent decades, digital education has experienced rapid development due to the emergence of Massive Open Online Course (MOOC) platforms. Platforms such as Coursera or edX provide access to online courses for millions of users worldwide. These platforms enable access to high-quality educational resources, contributing to the democratization of education and the expansion of learning opportunities at a global level.

In recent years, the integration of artificial intelligence (AI) technologies into MOOC platforms has begun to significantly transform the way students learn and interact with educational content. AI enables the analysis of large volumes of user-generated data and the provision of personalized and efficient learning experiences (Chen et al.,, 2020; Bozkurt et al., 2023).

MOOCs represent open online courses designed for a large number of participants. These courses are organized into modules and include video materials, interactive exercises, and online assessments. According to research conducted by Veletsianos and Shepherdson (2016), MOOCs have attracted millions of participants globally, becoming an important component of the digital educational ecosystem.

The main advantages of MOOCs include global accessibility, flexibility in the learning process, reduced costs or free access, and the possibility of obtaining digital certificates.

However, MOOCs also face several challenges, such as high course dropout rates and the difficulty of providing personalized support for each student (Ng et al., 2023).

The integration of artificial intelligence into online education offers solutions to many of these existing challenges. AI enables the analysis of user-generated data and the development of adaptive educational systems.

According to the study conducted by Chen and colleagues (2020), artificial intelligence is used in education for intelligent recommendation systems, educational data analysis (learning analytics), automated assignment assessment, and the development of virtual tutors.

These technologies contribute to improving the learning experience and increasing the efficiency of the educational process.

One of the most important benefits of artificial intelligence in MOOCs is the personalization of the learning process. Machine learning algorithms can analyze user behavior, such as the time spent on lessons, test results, or activity on discussion forums.

Based on these data, systems can recommend additional materials, exercises adapted to the learner’s level of knowledge, and personalized learning pathways.

According to research conducted by Zhao (2025), machine learning models can detect learners’ learning styles and automatically adapt content for different participants, thereby improving student engagement and performance in MOOCs and helping to identify the factors that influence success in the learning process.

MOOC platforms generate large amounts of data regarding user activity. Through the use of learning analytics technologies, these data can be analyzed to identify learning patterns and improve course design. There are predominant MOOC models that incorporate AI into three main typologies: those focused on AI programming, AI learning, and the educational value of AI (Delgado-Algarra et al., 2025).

This information enables the development of more efficient educational systems that are better adapted to students’ needs.

The integration of artificial intelligence into MOOC platforms represents an important step toward the development of modern digital education. In the future, these technologies are expected to enable the development of fully adaptive educational systems capable of providing personalized support for each student.

Furthermore, the use of virtual tutors and intelligent recommendation systems could contribute to reducing dropout rates and improving educational outcomes.

Artificial intelligence is transforming the way MOOC-based online courses are designed and used. Through the personalization of the learning process, the analysis of educational data, and the development of intelligent recommendation systems, AI contributes to the creation of more efficient and accessible educational experiences.

As AI technologies continue to evolve, MOOC platforms will become increasingly sophisticated, offering new opportunities for global education and for the development of digital competencies.

References

Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A., & Rodríguez, M. E. (2023). Artificial intelligence and MOOCs: A systematic review of the literature. Computers and Education: Artificial Intelligence, 4, 100134. https://doi.org/10.1016/j.caeai.2023.100134

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

Delgado-Algarra, E. J., Vela-Romero, J. A., Palomero Ilardia, I. M., & Pastor Blázquez, M. M. (2025). Artificial intelligence in MOOCs: Study of profiles and their socio-educational potential. International Journal of Educational Research and Innovation, 23. https://doi.org/10.46661/ijeri.11110

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2023). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 4, 100125. https://doi.org/10.1016/j.caeai.2021.100041

Veletsianos, G., & Shepherdson, P. (2016). A systematic analysis and synthesis of the empirical MOOC literature. International Review of Research in Open and Distributed Learning, 17(2), 198–221. https://doi.org/10.19173/irrodl.v23i1.5757

Zhao, Z. (2025). AI-driven learning-style detection for personalized MOOC content delivery in lifelong learning. International Journal of Environmental Science and Development. https://doi.org/10.54097/7d530x88

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