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Abstract.The use of feature selection can improve accuracy, efficiency, applicability and understandability of a learning process. For this reason, many methods of automatic feature selection have been developed. Some of these methods are based on the search of the features that allows the data set to be considered consistent. In a search problem we usually evaluate the search states, in the case of feature selection we measure the possible feature sets. This paper reviews the state of the art of consistency based feature selection methods, identifying the measures used for feature sets. An in-deep study of these measures is conducted, including the definition of a new measure necessary for completeness. After that we perform an empirical evaluation of the measures comparing them with the highly reputed wrapper approach. Consistency measures achieve similar results to those of the wrapper approach with much better efficiency.

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This article deals with the integrated use of online quizzes as a teaching and assessment tool in the general program of the subject Proyectos in the third course of Ingeniero Técnico en Informática de Gestión over five consecutive years. The research undertaken aimed to test quizzes effectiveness on student performance when used, not only as an isolated assessment tool, but also when integrated into a combined strategy, which support the overall programming of the subject. The results obtained during the five years of experimentation using online quizzes shows that such quizzes have a proven positive influence on students' academic performance. Furthermore, surveys conducted at the end of each course revealed the high value students accord to use of online quizzes in course instruction