Using Genetic Programming and Linear Regression for Academic Performance Analysis
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{esmeraldo:2022:AIEPLBR,
-
author = "Guilherme Esmeraldo and Robson Feitosa and
Cicero Samuel Mendes and Cicero Carlos Oliveira and
Esdras {Bispo Junior} and Allan Carlos {de Sousa} and
Gustavo Campos",
-
title = "Using Genetic Programming and Linear Regression for
Academic Performance Analysis",
-
booktitle = "Artificial Intelligence in Education. Posters and Late
Breaking Results, Workshops and Tutorials, Industry and
Innovation Tracks, Practitioners' and Doctoral
Consortium",
-
year = "2022",
-
editor = "Maria Mercedes Rodrigo and Noburu Matsuda and
Alexandra I. Cristea and Vania Dimitrova",
-
volume = "13356",
-
series = "LNCS",
-
pages = "174--179",
-
address = "Durham, UK",
-
month = jul # " 27-31",
-
publisher = "Springer",
-
keywords = "genetic algorithms, genetic programming, Academic
performance analysis, Linear regression",
-
isbn13 = "978-3-031-11647-6",
-
URL = "http://link.springer.com/chapter/10.1007/978-3-031-11647-6_30",
-
DOI = "doi:10.1007/978-3-031-11647-6_30",
-
abstract = "The academic evaluation process, even today, is the
subject of much discussion. This process can use
quantitative analysis to indicate the level of learning
of students to support the decision about whether the
student can attend the next curriculum phase. From this
context, this paper analyzes the history of students
grades in the 1st year of a technical course in
informatics integrated to high school, for the years
2020 and 2021, through the linear regression method,
supported by genetic programming, to find out the
influence of the grades of the first two bimesters
concerning the final grade. The main results show that
the genetic programming algorithm favoured the search
for linear regression models with a good fit to the
datasets with students data. The resultant models
proved accurate and explained more than 74percent of
the datasets.",
-
notes = "AIED 2022 https://aied2022.webspace.durham.ac.uk/",
- }
Genetic Programming entries for
Guilherme Esmeraldo
Robson Feitosa
Cicero Samuel Mendes
Cicero Carlos Oliveira
Esdras Bispo Junior
Allan Carlos de Sousa
Gustavo Campos
Citations