A Recommender System for Supporting Students in Programming Online Judges
Tipo de publicación: International Conference
Año de publicación: 2017
Autores: Raciel Yera
Director: Rosa María Rodríguez, Jorge Castro, Luis Martínez
Tipo: 4th International Conference on Smart Education and E-Learning
Editorial: Springer
Fecha de publicación: 21st-23rd June
Volumen: 75
Paginación: 215-224
Numero ISSN: 2190-3018
ISBN Number: 978-3-319-59450-7
Lugar de publicación: Switzerland
Resumen: Programming Online Judges (POJs) are tools that contain a large collection of programming problems to be solved by students as a component of their training and programming practices. This contribution presents a recommendation approach to suggest to students the more suitable problems to solve for increasing their performance and motivation in POJs. Some key features of the approach are the use of an enriched user-problem matrix that incorporates specific information related to the user performance in the POJ, and the development of a strategy for natural noise management in such a matrix. The experimental evaluation shows the improvements of the proposal as compared to previous works.
URL: http://www.springer.com/us/book/9783319594507
DOI: 10.1007/978-3-319-59451-4