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Case study: Forecast in ENADE for the mathematics course at the University of Pernambuco through simple linear regression analysis

Karina Ramos de Lima L;
Aurélio Nascimento da Silva Alves D;
Raimundo Cordeiro L;
Costa Goldfarb M;
Lecília Farias Ribeiro M;
Lopes Pessoa A;
Loureiro Roges D

Leticia Karina Ramos de Lima

Damocles Aurélio Nascimento da Silva Alves

Lauane Raimundo Cordeiro

Mauricio Costa Goldfarb

Miriam Lecília Farias Ribeiro

Antonio Lopes Pessoa

Danielle Loureiro Roges


Keywords

Enade
Simple linear regression
Teaching.

Abstract

ENADE is a mandatory assessment composed of the weighted average of the General Training grades - FG and Specific Components - CE that, in graduates of all graduations, measures performance in characteristics such as skills, content and professional competences about their courses. In this sense, in this work, the objective was to carry out a study with the general purpose of carrying out a statistical modeling in relation to the ENADE grade of the Mathematics course at the University of Pernambuco, identifying the patterns of variation of the grade obtained by the course and, after that, through simple regression analysis, predict values of future exam scores of these courses. For this, the existing relationships between two variables (grades and years) were described using a simple linear regression analysis, taking into account the regression line, Pearson's Correlation Coefficient, the Determination and Analysis of Waste. From the observed results, it was concluded that the Enade grades tend to decrease over the years, since there is a negative linear relationship between the variables, this occurs even with all the CE grades and the Garanhuns grade in FG with a positive linear relationship.

 

DOI: 10.56238/pacfdnsv1-117


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2023 Leticia Karina Ramos de Lima, Damocles Aurélio Nascimento da Silva Alves, Lauane Raimundo Cordeiro, Mauricio Costa Goldfarb, Miriam Lecília Farias Ribeiro, Antonio Lopes Pessoa, Danielle Loureiro Roges

Author(s)

  • Leticia Karina Ramos de Lima
  • Damocles Aurélio Nascimento da Silva Alves
  • Lauane Raimundo Cordeiro
  • Mauricio Costa Goldfarb
  • Miriam Lecília Farias Ribeiro
  • Antonio Lopes Pessoa
  • Danielle Loureiro Roges