A Case Study: Data Mining Applied to Student Enrollment
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One of the main problems faced by university students is deciding the right learning path based on available information such as courses, schedules and professors. In this context, this paper presents a recommender system based on data mining. This recommender system intends to create awareness of the difficulty and amount of workload entailed by a chosen set of courses. For the purpose of building the underlying model, this paper describes the generation of domain specific variables that are capable of representing students’ past performance. The objective is to improve students’ performance in general, by reducing the rate of misguided enrollment decisions.
How to citeVialardi Sacín, C., Chue Gallardo, J., Barrientos, A., Victoria, D., Estrella, J., Peche, J. P., y Ortigosa, Á. (junio 2010). A case study: data mining applied to student enrollment. In Educational Data Mining 2010.
PublisherEducational Data Mining
Work typeIndexado en Scopus
- Estudios Generales