An applied data science project has identified a series of academic and psychological factors that impact performance school of children and that could contribute to school dropouts. Some variables that affect are emotional stability, few hours of sleep and the study environment.
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The project was carried out by BREIT students, in collaboration with Perú Champs, a non-profit association that grants school scholarships to low-income boys and girls with exceptional talents. The students developed a Clusterization Model that identified factors that influence good academic performance.
“It is feasible to extend this research towards the prediction of school dropouts, since the model has revealed factors associated with a greater probability of dropping out. These include academic and psychological risks that both our scholarship recipients and other students face, providing us with a solid basis to implement preventive actions,” says Alberto Cárdenas, executive director of Perú Champs.
John Poma, a BREIT student and part of the team that developed the model, highlights the relevance of Data Science in solving social problems. For him, the experience of working on this initiative was “challenging and exciting.” “One of the biggest challenges was crossing information from ‘hard’ variables, such as grades, with psychological and environmental variables. This crossing of data was key to understanding how factors such as emotional stability, hours of sleep and the study environment affect the risk of dropping out of school,” he explains.
Within the framework of the global celebration of Children’s Day, these results underline the importance of continuing to work on projects that contribute to successfully improving the study conditions of thousands of schoolchildren in the country. “Data Science in social projects is fundamental, since it provides deep and well-founded knowledge about the situations that students face. This allows us to develop solutions tailored to their needs, eliminating subjective assumptions and personalizing support strategies,” concludes Poma.
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