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Fatores que podem interferir no desempenho de estudantes no ENEM: uma revisão sistemática da literatura.
- Source :
-
Revista Brasileira de Informática na Educação . 2023, Vol. 31, p323-351. 29p. - Publication Year :
- 2023
-
Abstract
- Evaluating student performance in diverse contexts is a very hard task. This is not different when discussing factors associated with student performance regarding tests such as the National High School Examination (ENEM). Several factors such as the students own knowledge acquired throughout their academic career, as well as other ones arising from their experiences, or even social or economic situation, may impact on diverse results in the test. ENEM historical data made available comprise diverse information about the individual results of students as well as answers obtained by means of questionnaires formulated at registration time. Due to the high dimensionality of the data and the complexity of analyzes that might be carried out from these datasets, an essential question is how to identify which factors are really more relevant for such analyses. Data mining techniques, such as predictive models and feature selection, have been used as a means to help obtaining such analyses. In this light, this work presents a systematic literature review in order to identify the main factors that may influence the performance of students in the ENEM test, considering studies published along the last ten years. The results obtained showed that the most relevant factors are related to socioeconomic issues, with the following attributes being most evident: family income, age, sex and race. Parents' level of education is also highlighted. Attributes related to test scores and characterization of the students' schools of origin with respect to the physical and pedagogical structure are additionally emphasized. This study points out some paths that may be accomplished on complementary research. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DATA mining
*DATA analysis
*STUDENTS
Subjects
Details
- Language :
- Portuguese
- ISSN :
- 14145685
- Volume :
- 31
- Database :
- Academic Search Index
- Journal :
- Revista Brasileira de Informática na Educação
- Publication Type :
- Academic Journal
- Accession number :
- 175733293
- Full Text :
- https://doi.org/10.5753/rbie.2023.3087