A New Methodological Framework for Project Design to Analyse and Prevent Students from Dropping Out of Higher Education

Abstract

The problem of university dropout is a recurring issue in universities that affects students, especially in the first year of studies. The situation is aggravated by the COVID-19 pandemic, which has imposed a virtual education, generating a greater amount of data in addition to historical information, and thus, a greater demand for strategies to design projects based on Educational Data Mining (EDM). To deal with this situation, we present a framework for designing EDM projects based on the construction of a problem tree. The result is the proposal of a framework that merges the six phases of the CRISP-DM methodology with the first stage of the Logical Framework Methodology (LFM) to increase university retention. To illustrate this framework, we have considered the design of a project based on data mining to prevent students from dropping out of a Peruvian university.