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Educational data mining: Incidence of socioeconomic factors on school achievement

Abstract:

Educational data mining is a compendium of effective methods to detect patterns of situations that affect various aspects of schooling; however, it is not entirely clear at what times of an academic year socioeconomic factors may have more impact on achievement. In this study, a random cross-sectional sample of data from progressive partial grades and socioeconomic factors of students from an Ecuadorian school has been taken, to estimate the influences of these factors on their achievement through classification algorithms. With the use of Association Rules and Decision Trees, it was specified in 90% those socioeconomic factors influence the achievement of students in a special way in the first of the two semesters that make up an academic period, and, in the second the Greater mastery of learning reflected in grades is more related to the grades of the partial components. This model of analysis can be applied to all levels of education.