The incorporation of Artificial Intelligence (AI) into academia has brought about a revolution on multiple fronts, from research to teaching and administration. This paradigm shift presents both opportunities and challenges, prompting deep reflection on traditional methodologies and existing institutional structures.
The ability of large language models (LLMs) to process and generate information on previously unimaginable scales raises fundamental questions about the role of education and research in the digital age. The integration of AI in universities and libraries not only optimizes existing processes but also opens new pathways for knowledge access and management, transforming pedagogical and research practices.
However, the adoption of such technologies entails significant ethical considerations, particularly concerning data privacy and intellectual autonomy. Likewise, the effectiveness of AI in academia depends on the establishment of regulatory frameworks that ensure its responsible and equitable use.
This call for papers aims to explore these dimensions, providing a forum for critical analysis and discussion on how AI is reshaping the academic landscape. Without attempting to offer an exhaustive or restrictive list of topics, we welcome contributions related to the following issues:
- Teaching and research competencies in AI tools: Strategies for professional development in the use of AI technologies.
- Automation in research: The use of AI in research processes, from minor text editing tasks to advanced methodological development.
- Impact of AI on academic publishing: Transformations in editorial processes (peer review) and knowledge dissemination practices.
- Impact of AI on academic integrity: Challenges and solutions regarding AI-generated academic work (undergraduate and master’s theses, doctoral dissertations) and scientific publications (articles, books, etc.).
- Automated student assessment through AI: Implications and effectiveness of evaluation systems in relation to AI-generated content, as well as the implementation of AI-assisted assessment techniques.
- Personalization of teaching: Implementation of systems that tailor content and learning pace to individual needs.
- AI in academic administration: Analysis of how AI contributes to operational efficiency and management tasks in academic contexts.
- Development of AI tools for libraries: Innovations in collection management, search queries, and access to resources or other documentary applications.
- AI and ethics in academia: Discussions on equity, transparency, and privacy in the use of these emerging technologies.
We look forward to receiving contributions that critically engage with these themes and shed light on the evolving role of AI in academia.