Adaptive Learning System for Personalizing Secondary Education using Content-Based Filtering and Matrix Factorization

Estrada D.; Diaz A.; Montero R. · International Conference on Engineering and Emerging Technologies, ICEET (2025) · DOI: 10.1109/iceet67911.2025.11424107

Resumen

The current educational context demands personalized solutions that adapt to the individual needs of students, especially at critical levels such as secondary education. This paper proposes the use of adaptive learning supported by learning analytics techniques to personalize education and improve student performance. An approach combining Content-Based Filtering and Matrix Factorization is used to efficiently analyze interactions between students and educational content, providing an experience that is more tailored to the individual needs of each student and optimizing the teaching-learning process. The results show that combining these techniques significantly improves the accuracy of educational recommendations, optimizing academic performance in secondary school students.

Instituciones: Universidad Peruana de Ciencias Aplicadas