Modeling of university dropout using Markov chains

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Abstract

Access to higher education is only a first step in achieving equity in education; the following step is improving student retention, or lowering dropout rates, which is the same thing. The present study focused on the definition of an index as an estimator of the risk of individuals dropping out of a university using a Markov chain model, based on the randomness of the occurrence of dropping out. The suggested index was applied to a sample of 5,700 university students from the 2012-2015 annual cohorts of 8 university departments of a public regional university in Chile. The results indicate that the highest average probability of dropping out (slightly more than 39%) occurs in the first 2 semesters of university studies, and then decreases through time. This indicates the need for institutional retention policies that pay particular attention to the first year of university studies. Having this index also allows a formal estimation of changes or temporary variations in the risk, as well as quantifying the impact of interventions, not only for the case under study but for the entire higher education system.

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González-Campos, J. A., Carvajal-Muquillaza, C. M., & Aspeé-Chacón, J. E. (2020). Modeling of university dropout using Markov chains. Uniciencia, 34(1), 129–146. https://doi.org/10.15359/ru.34-1.8

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