Methodology for obtaining a predictive model academic performance of students from first partial note and percentage of absence

Objectives: This study presents the methodology for a model of multiple linear regression to assess the impact of the first partial grade and the percentage of non - attendance in the final grade students. Methods/Statistical Analysis: Descriptive Statistics and Inferential a program Industrial engineering a university in Colombia. Findings: After the generation and validation of the model was obtained that it explains 83.38% of the variability of the final grade students analyzed (134 students), and this significantly high percentage as a tool to determine the outcome of a student and generate recovery strategies those with a very low projection in its final note, it should be noted that the model was rigorously validated statistically. Application/Improvements: This methodology is proposed as a model for similar studies in other institutions.

• Autores: Viloria Silva, Amelec Jesus; Parody, Alexander
• Tipo de recurso: Article of journal
• Fecha de publicación: 2016
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/1150
• Acceso en línea: https://hdl.handle.net/11323/1150; https://repositorio.cuc.edu.co/
• Palabra clave: College dropout; Multiple linear regression; Prediction
• Rights: openAccess
• License: Atribución – No comercial – Compartir igual