Hybrid System for Dropout Risk Evaluation of First Year Students
Abstract
This paper proposes a hybrid system for evaluating the dropout risk for students enrolled in the first year of tertiary education, based on data collected from an engineering faculty in Romania. The system determines the profile of the student and matches it against a series of predefined values for certain indicators, checking whether the student’s dropout risk is at an alarming level. The data used in developing the system was collected by means of anonymous online forms, from 1st year students, during the 1st semester. So far, the system was tested using artificial data only, but is currently applied in the Faculty and real results will be available after the beginning of the 2018-2019 academic year.
Keywords
Student dropout profile, College dropout, Tertiary education, Fuzzy logic
DOI
10.12783/dtcse/amms2018/26200
10.12783/dtcse/amms2018/26200
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