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A Systematic Approach for Providing Personalized Pedagogical Recommendations Based on Educational Data Mining

Ranilson Oscar Araujo Paiva, Ig Ibert Bittencourt Santa Pinto, Alan Pedro da Silva, Seiji Isotani, Patricia Jaques

This work presents an approach to assist teachers, tutors and students from online learning environments. It is a four-steps process called Pedagogical Recommendation Process that uses the coordinated efforts of human actors (pedagogical and technological specialists) and artificial actors (computational artifacts). The process’ objective is to find relevant information in educational data to help creating personalized recommendations. Using the process it was possible to detect issues within a learning environment (UFAL Línguas), and discovered why some students were facing difficulties, and what other students were doing in order to succeed in the course. This information was used to personalize pedagogical recommendations.

The final publication is available at Springer via https://doi.org/10.1007/978-3-319-07221-0_45.