Heatmap of the Area discrepancy based on the Observed ICC. The color of each square indicates the value of Area discrepancy and the symbol indicates the group with the highest area. As the importance of the indicated grows with the discrepancy, the symbols' visibility also grows with the color.
Abstract
Several studies adopt different approaches to examining how economic, racial, and gender circumstances influence student performance in large-scale entrance exams, such as the National High School Exam (ENEM). Using a methodology based on Item Response Theory, ENEM's exam attempts to assess, for each item (question), the curve (function) that relates the participants' abilities to their probabilities of correctly answering the item, which is assumed to hold whichever subgroup, a fundamental premise of IRT called invariance. This work analyzes whether the ENEM 2019 test presented similar curves for subpopulations defined by gender, race, and income, regardless of the participant's actual abilities. Our approach is to analyze the properties of the observed curve for each group and then perform a nonparametric ranking test to compare the equity of each item (question) for each analyzed characteristic. We found that the ”Languages and Codes” questions consistently favored male, white, and high-income participants. At the same time, the other three sets of questions (Mathematics, Natural Sciences, and Human Sciences) were considerably more egalitarian.
BibTeX
@inproceedings{2022-AnalyzingENEM,
title = {Analyzing the Equity of the Brazilian National High School Exam by Validating the Item Response Theory's Invariance},
author = {Vitória Guardieiro AND Marcos Medeiros Raimundo AND Jorge Poco},
booktitle = {International Conference on Educational Data Mining},
year = {2022},
url = {http://www.visualdslab.com/papers/AnalyzingENEM},
}