Artificial Intelligence in Support of Teaching: Predictive Models and Adaptive Systems for Personalising Learning
Artificial Intelligence (AI) is now a success factor in various business sectors and in the education sector in particular, it can contribute innovative models for personalising higher education. The use of predictive models makes it possible to identify learning difficulties and anticipate student performance with more effective pedagogical actions. AI-based adaptive systems also allow content and teaching methodologies to be aligned with the needs of each student, promoting a more efficient and motivating learning path. This article explores the impact of AI in supporting teaching, highlighting the involvement of teachers and students in the use of intelligent technologies. In particular, it analyses the application of algorithms, natural language processing, robotics and digital systems to support academic difficulties and the implementation of adaptive systems for personalising learning. The study contributes to understanding the potential of AI and the importance of integrating it into the school and academic context, promoting a highly reactive and student-centred learning environment, adjusted to the needs and opportunities of the 21st century.
Authors
- Helena F. Gonçalves (ORCID: https://orcid.org/0000-0001-5608-9102)
- Jorge Duque (ORCID: https://orcid.org/0000-0003-4939-6176)
- José Joaquim Moreira (ORCID: https://orcid.org/0000-0002-0291-4864)
- Firmino Silva
Institutions
- Instituto Superior Politécnico Gaya (PT)
- ISLA - Instituto Politécnico de Gestão e Tecnologia
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2026-01-01
- DOI
- https://doi.org/10.1016/j.procs.2026.02.454
- Primary Topic
- Artificial Intelligence in Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00