Dropout-permanence analysis of university students using data mining
Pre-Publicación
2019
Universidad de la Costa
Dropout is a rejection method present in every educational system,
related to the various selection processes, academic performance, and the efficiency of the system in general, that is, the result of the combination and effect
of different variables. In this sense, the dropout of university students related to
their academic performance is a matter of concern since several years ago.
Academic information is analyzed in order to identify factors that influence
students´ dropout at the University of Mumbai, India, by using a data mining
technique. The data source contains information provided to the entrance
(personal and educational background) and that is generated during the study
period. The data selection and cleansing are made using different criteria of
representation and implementation of classification algorithms such as decision
trees, Bayesian networks, and rules. the following factors are identified as
influential variables in the desertion: approved courses, quantity and results of
attended courses, origin and age of entry of the student. Through this process, it
was possible to identify the attributes that characterize the dropout cases and
their relationship with the academic performance, especially in the first year of
the career.
- Artículos científicos [3154]
Descripción:
DROPOUT-PERMANENCE ANALYSIS OF UNIVERSITY STUDENTS USING DATA MINING.pdf
Título: DROPOUT-PERMANENCE ANALYSIS OF UNIVERSITY STUDENTS USING DATA MINING.pdf
Tamaño: 6.923Kb
PDFLEER EN FLIP
Título: DROPOUT-PERMANENCE ANALYSIS OF UNIVERSITY STUDENTS USING DATA MINING.pdf
Tamaño: 6.923Kb
PDFLEER EN FLIP
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