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Permanent URI for this collectionhttps://hdl.handle.net/11285/636050

Artículos científicos o técnicos preliminares, sujeto a revisión de pares, pero tiene la intención de ser publicado en una publicación periódica, de manera independiente o como un capítulo de libro de naturaleza académica, tal como resultados preliminares de investigación publicados en cuadernillo separado.

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  • Objeto de congreso
    Research plan on the effects of interventions on dropout predictions for higher education institutions
    (2023) Talamás Carvajal, Juan Andrés; Tecnologico de Monterrey; https://ror.org/03ayjn504; Polytechnic Institute of Bragança
    One of the main challenges that Higher Education Institutions face currently is dropout/ student retention. In most cases, identifying this group of stu-dents is no easy task, and doing so on time is even harder. This challenge re-quires both speed and accuracy, which makes it a prime candidate for the use of machine learning models and predictions. We are currently developing a series of models capable of early identification of students at risk of dropping out, with one key difference from classic approaches: we want to not only find out who these students are, but how we can best help them avoid that prediction. By developing methodologies capable of identifying and measur-ing the effects of a series of interventions (academic guidance courses, extra-curricular encouragement, diminished course load, etc.), we intend to devel-op a system capable of providing counterfactuals (what the student needs to change or do to reverse a prediction) based on the causal effects of the previ-ously mentioned interventions. In this manner, we would not only identify groups of students at risk of dropping out, but would be doing so on time, and with a viable and specific strategy for each individual to improve.
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