RIED SPECIAL ISSUE – Vol. 29(2)
University Transformation in the Age of AI: Innovation or Disruption?
INICIAL NOTE: This call for papers is exclusively for submissions directly related to the theme of this Special Issue. Broader or unrelated topics should be reserved for future calls.
INTRODUCTION
The emergence of artificial intelligence (AI) in higher education is not just another incremental development. It is—or should be—a deep disruption of the university’s core structures, everyday practices, and historical purposes. In the era of data, automation, and generative systems, the university finds itself at a crossroads: Are we witnessing a phase of controlled innovation, or are we already facing a structural disruption?
AI does not merely transform tools or media; it reshapes the ways we think, decide, teach, learn, research, and govern. AI systems hold the potential to act as new cognitive and organizational infrastructures capable of shaping academic trajectories, automating assessments, generating content, assisting in strategic decisions, or redrawing the map of scientific production. This transformation demands rigorous, critical, and interdisciplinary research—one that avoids both uncritical techno-enthusiasm and apocalyptic rejection.
In response to these challenges, RIED. Ibero-American Journal of Distance Education invites the international academic community to contribute to its upcoming Special Issue titled: University Transformation in the Age of AI: Innovation or Disruption?
Through this call, we aim to gather scholarly work that EXCLUSIVELY investigates, in depth and with academic rigor, how artificial intelligence is impacting—or could impact—different dimensions of university life. This is not a call for descriptions of applications or systematic reviews, but for critical analyses of the foundations, effects, limitations, and consequences of AI. We welcome empirical, theoretical, or methodological contributions grounded in robust conceptual frameworks, clear research designs, and relevant findings.
The contemporary university must be understood not just as a technology adopter, but as a complex organism being redefined through its interaction with algorithmic logics, data infrastructures, intelligent systems, and predictive models. This Special Issue will offer an opportunity to map, from an academic perspective, this terrain of profound transformation.
AREAS OF CONTRIBUTION
Below are the main research themes and subtopics that may guide article submissions. These do not limit the acceptance of interdisciplinary or emerging approaches, as long as they are clearly related to AI and higher education.
1. Governance, Management, and Institutional Decision-Making with AI
- Case studies and comparative analyses of AI-based systems in university management.
- Predictive institutional analytics using machine learning models.
- Evaluation of transparency, accountability, and algorithmic ethics in strategic decision-making.
- Research on data governance and technological sovereignty in higher education.
2. Teaching and Curriculum Transformation
- Research on AI-driven curricular redesign: new content, competencies, and structures, and their effect on learning.
- Evidence on AI’s impact on teaching mediation: conversational agents, adaptive personalization, human-machine co-teaching.
- Evaluation of AI-powered educational platforms: effectiveness, biases, or unintended effects.
- Critical analyses of theoretical frameworks for automated teaching and their pedagogical limits.
3. Teaching and Curriculum Transformation
- Research on AI-driven curricular redesign: new content, competencies, and structures, and their effect on learning.
- Evidence on AI’s impact on teaching mediation: conversational agents, adaptive personalization, human-machine co-teaching.
- Evaluation of AI-powered educational platforms: effectiveness, biases, or unintended effects.
- Critical analyses of theoretical frameworks for automated teaching and their pedagogical limits.
4. Scientific Production, Academic Evaluation, and Research Innovation
- Use of AI in peer review, scientific writing, and knowledge discovery processes: evidence of benefits and drawbacks.
- Studies on ethical and epistemological implications of co-authorship with generative systems.
- AI as a subject of inquiry in social sciences and education: methods, frameworks, and controversies.
- Research on algorithmic bias, academic integrity, and surveillance in scientific contexts.
5. University Outreach, Societal Engagement, and New Forms of Connection
- Findings on AI applications in technology transfer, cultural outreach, and community engagement.
- Evaluation of AI-based initiatives for democratizing knowledge and fostering social inclusion.
- Analyses of potential dehumanization risks in university-society relationships mediated by AI.
6. Philosophical, Normative, and Critical Perspectives on AI and Higher Education
- Philosophical and sociotechnical inquiries into the role and purpose of universities in AI contexts.
- Studies on national or international regulatory frameworks impacting AI use in higher education.
- Critical analyses of innovation ideology and the disruption narrative: what kind of university are we building?
- Research on AI and core university values: academic freedom, critical thinking, inclusion, and justice.
KEY DATES
- Submission window: During November 2025 (deadline: December 1, 2025). Please do not send articles before November.
- Official publication date: July 1, 2026 (Vol. 29-2).
- OnlineFirst publication: Articles will be published on an OnlineFirst basis (ready to read and cite) as they successfully pass the peer review and production process.
IMPORTANT
- Please, avoid sending articles before November 2025.
- Do not submit your work to RIED unless you are certain it fully complies with all the criteria in this call and the requirements specified in this document and its related links.
- All submissions must be directed to the Special Issue section.
- Any article that does not meet the criteria for publication in Vol. 29(2) will be rejected.