The outbreak of COVID-19 in 2020 inhibited face-to-face education and constrained exam taking. In many countries worldwide, high-stakes exams happening at the end of the school year determine college admissions. This paper investigates the impact of using historical data of school and high-stakes exams results to train a model to predict high-stakes exams given the available data in the Spring. The most transparent and accurate model turns out to be a linear regression model with high school GPA as the main predictor. Further analysis of the predictions reflect how high-stakes exams relate to GPA in high school for different subgroups in the population. Predicted scores slightly advantage females and low SES individuals, who perform relatively worse in high-stakes exams than in high school. Our preferred model accounts for about 50% of the out-of-sample variation in the high-stakes exam. On average, the student rank using predicted scores differs from the actual rank by almost 17 percentiles. This suggests that either high-stakes exams capture individual skills that are not measured by high school grades or that high-stakes exams are a noisy measure of the same skill.

What is at stake without high-stakes exams? Students' evaluation and admission to college at the time of {COVID}-19

Annalisa Loviglio
Co-primo
2021

Abstract

The outbreak of COVID-19 in 2020 inhibited face-to-face education and constrained exam taking. In many countries worldwide, high-stakes exams happening at the end of the school year determine college admissions. This paper investigates the impact of using historical data of school and high-stakes exams results to train a model to predict high-stakes exams given the available data in the Spring. The most transparent and accurate model turns out to be a linear regression model with high school GPA as the main predictor. Further analysis of the predictions reflect how high-stakes exams relate to GPA in high school for different subgroups in the population. Predicted scores slightly advantage females and low SES individuals, who perform relatively worse in high-stakes exams than in high school. Our preferred model accounts for about 50% of the out-of-sample variation in the high-stakes exam. On average, the student rank using predicted scores differs from the actual rank by almost 17 percentiles. This suggests that either high-stakes exams capture individual skills that are not measured by high school grades or that high-stakes exams are a noisy measure of the same skill.
2021
Andreu Arenas; Caterina Calsamiglia; Annalisa Loviglio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/843644
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