Open AccessKnowledge Discovery Through Time Series Applied to Students' Grades
Author(s) -
Joaquim Assunção,
Fernando Luiz Cyrino Oliveira,
Claiton Marques Correa
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/encompif.2020.11073
Subject(s) - computer science , cluster analysis , knowledge extraction , process (computing) , data science , mathematics education , time series , series (stratigraphy) , educational data mining , artificial intelligence , machine learning , psychology , paleontology , biology , operating system
Assessment is a constant activity in education, in the school system, and the teaching-learning process. The traditional approach classifies the students learning level through grades. This paper shows an application of knowledge discovery and data mining through classification and clustering via time series modeling on students' grades from high school. We collected historical data from an institute of technology, from this, we created models that can be used to extract patterns to help teachers to understand the profile of the students and provide early warns about possible poor results.