Resumen

CARO PINERES, Manuel Fernando; HERNANDEZ, Jaime  y  JIMENEZ BUILES, Jovani Alberto. DESIGNING A LEARNING OBJECTS RECOMMENDATION SYSTEM FOR REPOSITORIES BASED ON USER'S PERCEPTION: THE RODAS CASE. Cienc. Ing. Neogranad. [online]. 2011, vol.21, n.1, pp.51-72. ISSN 0124-8170.

This paper describes a Learning Objects (LO) Recommendation System (RS) for repositories. The system is based on collaborative filtering using an adaptation of kneighboring algorithm which is supported on user's perception about usability and usefulness rather than downloading LO from repository. It also shows how the k-neighboring algorithm is adapted to user's perception by implementing a voting system of LO. Finally, the RS validation using RODAS repository is given describing some pieces of algorithm and the computational model.

Palabras clave : learning objects; recommendation system; learning object repositories.

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