ONLINE LEARNING AND ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION

2025-07-02

ONLINE LEARNING AND ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION

2025-06-02

Journal: Society and Economy (SJR 2024: 0.260 (Q3), H-index: 19, Gold Open Access — no article processing fees). See https://www.scopus.com/sourceid/10600153342 for more information.

The Society and Economy editorial team invites proposals for articles that provide state-of-the-art insights into the relationship between higher education and digitalization / artificial intelligence. Successful articles should not merely summarize existing comprehensive literature (see for example Žáková 2025; Sethi and Singh 2024; or Landers 2024), but contribute to it with new concepts, theories, questions, or data, possibly from a Central and Eastern European perspective.

The rapid evolution of digital technologies has transformed pedagogical practices across higher education institutions. Online learning, broadly understood as the delivery of coursework and student support via internet-enabled platforms, has gained traction not only as an emergency response to crisis situations but as a long-term modality in its own right (Mitev et al. 2024). Artificial intelligence (AI), encompassing machine learning, natural language processing, and adaptive algorithms, has been offering new capabilities for personalized instruction, automated assessment, and predictive analytics. By 2025, nearly all universities worldwide shifted components of their curricula to online platforms, accelerating experiments with AI-driven tutoring systems, automated grading, and chatbots for student services (Periasamy – Abirami 2025). Institutional and student answers include new learning habits (Vaszkun – Mihalkov Szakács 2025), adaptive learning (Smyrnova-Trybulska et al. 2022), smart education (Zhuang et al. 2023), the increasing use of LLM models (Rajki et al. 2025), and raising performance expectations (Nagy et al. 2024).

While research highlights improvements in learner engagement and retention through adaptive learning pathways, concerns remain regarding equity, data privacy, and algorithmic bias (Memarian – Doleck 2023). European policy initiatives have sought to integrate digital strategies into national higher education frameworks, yet institutional capacity and faculty readiness vary widely (Justo-Hanani 2022). As AI continues to permeate administrative processes—ranging from predictive modelling of dropout risk to automated generation of course materials—there is an urgent need to assess both the potential and pitfalls of these innovations. Moreover, debates around the “automation of teaching” raise critical questions about the future of academic labour (Yang et al. 2023). Will AI augment faculty roles, allowing instructors to focus more on mentorship and critical thinking, or will it supplant certain teaching functions altogether? How do students perceive AI-mediated feedback compared to traditional grading? What regulatory frameworks are necessary to ensure transparency and accountability when decisions about admissions or scholarship awards are informed by algorithmic insights?

Our special issue seeks to explore, among others, these intersections of online learning and AI in higher education by soliciting contributions from a wide range of researchers, educators, policymakers, and computer scientists. We invite submissions that critically engage with conceptual definitions, empirical analyses, and theoretical reflections on the evolving roles of faculty, students, administrators, or learning itself. Contributions employing qualitative, quantitative, or mixed methods are welcome. Comparative studies on various learning methods or regional differences are of special interest, as are examinations of ethical considerations in deploying AI-driven tools for assessment, admissions, or student support. Furthermore, submissions may focus on (but are not limited to) the following aspects:

  • The evolution and potential future of MOOCs,
  • The relation between online learning and learning theories,
  • Student performance prediction with AI,
  • The role of digital competences in learning in a digital age,
  • Regional frameworks of digital competences,
  • Other AI-driven aspects of creating content and guiding students’ attention.

 

Submissions:

  • https://akjournals.com/view/journals/204/204-overview.xml
  • Manuscripts should be between 6,000 and 8,000 words, including references.
  • On the first page of the submission process, please add a note to the Editor stating that you are submitting for the special issue ‘Online Learning and Artificial Intelligence in Higher Education’.
  • All submissions will be scanned against plagiarism using the iThenticate tool and undergo double-blind peer review.
  • Deadline for full paper submissions: 2025-09-01.

 

Contact: Special Issue Editor Balázs Vaszkun (Associate Professor, Corvinus University) at balazs.vaszkun@uni-corvinus.hu. We encourage you to contact the SI Editor before your submission.

 

 

 

References:

Justo-Hanani, R. (2022): The politics of Artificial Intelligence regulation and governance reform in the European Union. Policy Sci 55, 137–159. https://doi.org/10.1007/s11077-022-09452-8

Landers, M. (2024): Adapting to the Unsanctioned Use of AI-Supported Technologies in Student Assessments. Higher Education for the Future, 12(1), 76-96. https://doi.org/10.1177/23476311241300608

Memarian, B. – Doleck, T. (2023): Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review. Computers and Education: Artificial Intelligence 5, 100152. https://doi.org/10.1016/j.caeai.2023.100152

Mitev, A.Z. – Tóth, R. – Vaszkun, B. (2024): Role transition of higher education teachers due to disruptive technological change: Identity reconstruction for a better teacher-student relationship. The International Journal of Management Education 22, 100978. https://doi.org/10.1016/j.ijme.2024.100978

Nagy, A.S. –  Tumiwa, J.R. –  Arie, F.V. –  Erdey, L. (2024): An exploratory study of artificial intelligence adoption in higher education. Cogent Education 11, 2386892. https://doi.org/10.1080/2331186X.2024.2386892

Periasamy, K. – Abirami, A.M. (2025): ADOPTING ARTIFICIAL INTELLIGENCE TOOLS IN HIGHER EDUCATION: student assessment. CRC PRESS, BOCA RATON. https://doi.org/10.1201/9781003470304

Rajki, Z. –  Dringo, -Horvath Ida –  Nagy, J.T. (2025): Artificial Intelligence in higher education: Students’ Artificial Intelligence use and its influencing factors. Journal of University Teaching and Learning Practice 22, 1–21. https://doi.org/10.3316/informit.T2025060500008701690697530

Sethi, S. –  Singh, M. (2024): Blended Learning and AI in Higher Education: Adapt, Evolve, Thrive. Cambridge Scholars Publishing.

Smyrnova-Trybulska, E. – Morze, N. – Varchenko-Trotsenko, L. (2022): Adaptive learning in university students’ opinions: Cross-border research. Educ Inf Technol 27, 6787–6818. https://doi.org/10.1007/s10639-021-10830-7

Vaszkun, B. – Mihalkov Szakács, K. (2025): Looking for student success factors outside of the educators’ scope: The effect of digital literacy, personal skills, and learning habits and conditions on self-evaluated online learning effectiveness in management education. The International Journal of Management Education 23, 101188. https://doi.org/10.1016/j.ijme.2025.101188

Yang, Q.-F. – Lian, L.-W. – Zhao, J.-H. (2023): Developing a gamified artificial intelligence educational robot to promote learning effectiveness and behavior in laboratory safety courses for undergraduate students. Int J Educ Technol High Educ 20, 18. https://doi.org/10.1186/s41239-023-00391-9

Žáková, K. – Urbano, D. – Cruz-Correia, R. – Guzmán, J.L. – Matišák, J. (2025): Exploring student and teacher perspectives on ChatGPT’s impact in higher education. Educ Inf Technol 30, 649–692. https://doi.org/10.1007/s10639-024-13184-y

Zhuang, R., Liu, D., Sampson, D., Mandic, D., Zou, S., Huang, Y., Huang, R. (Eds.), 2023. Smart Education in China and Central & Eastern European Countries, Lecture Notes in Educational Technology. Springer Nature Singapore, Singapore. https://doi.org/10.1007/978-981-19-7319-2