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TRANSFORMING MOOCS WITH AI: CURRENT APPLICATIONS AND PROSPECTIVE PATHWAYS

Eugenia SMYRNOVA– TRYBULSKA*1, Małgorzata PRZYBYŁA-KASPEREK2, Anna ŚLÓSARZ3, *Corresponding Author 4, 5

Język publikacji: angielski

artykuł naukowy

Transformacje Nr 2(125)2025 Data publikacji: 30 czerwca 2025r.

Artykuł Nr 20250630141650619

Słowa kluczowe: AI, MOOC, Trends, Bibliometric analysis, VosViewer

Streszczenie Massive Open Online Courses (MOOCs) have become a central element of global digital education, yet persistent challenges such as high dropout rates, limited personalization, and assessment quality remain unresolved. Recent advances in Artificial Intelligence (AI) offer new opportunities to address these issues by enabling predictive analytics, adaptive learning, automated feedback, and intelligent tutoring. This article reviews contemporary trends in the integration of AI into MOOCs in the last decade, drawing on a total of 60 studies indexed in Web of Science and Scopus. The analysis highlights five dominant areas of application: (1) dropout and retention prediction through machine learning and deep neural models; (2) sentiment analysis of learner feedback and forums using advanced natural language processing; (3) personalized learning and recommendations via knowledge graphs and graph neural networks; (4) conversational agents and large language models as learning assistants; and (5) AI-supported assessment and proctoring. While evidence suggests that AI can enhance learner engagement, satisfaction, and instructional efficiency, concerns remain regarding its ethical use, explainability, and generalization across various platforms. The article concludes with future research directions, emphasizing the need for scalable, transparent, and learner-centered AI solutions to support the next generation of MOOCs.

  1. University of Silesia in Katowice, Faculty of Arts and Educational Sciences, Poland

    ORCID: 0000-0003-1227-014X

    E-mail: esmyrnova@us.edu.pl

  2. University of Silesia in Katowice, Faculty of Science and Technology, Poland

    ORCID: 0000-0003-0616 9694

    E-mail: malgorzata.przybyla-kasperek@us.edu.pl

  3. University of the National Education Commission in Krakow, Podchorążych 2, 30-084 Krakow, Poland

    ORCID: 0000-0001-5524-3227

    E-mail: anna.slosarz@uken.krakow.pl

  4. ORCID: 

    E-mail: 

  5. ORCID: 

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