Title: Screening for aberrant school performances in high-stakes assessments using in influential analysis
Authors: Andrés Christiansen; Rianne Janssen; Cristian Luis Bayes
Addresses: Centre for Educational Effectiveness and Evaluation, Katholieke Universiteit Leuven, Dekenstraat 2 (PB 3773), 3000 Leuven, Belgium ' Centre for Educational Effectiveness and Evaluation, Katholieke Universiteit Leuven, Dekenstraat 2 (PB 3773), 3000 Leuven, Belgium ' Department of Science, Pontificia Universidad Católica del Perú, Av. Universitaria 1801, San Miguel 15088, Peru
Abstract: A method is proposed to screen for aberrant school performances in large-scale, high-stakes assessments using influential analysis under a Bayesian approach. Proportions of low and high achievers within a school were modelled via the beta inflated mean regression model (Bayes and Valdivieso, 2016) using school performances in previous years as predictors. The general measure of ϕ-divergence proposed by Peng and Dey (1995) was used to determine aberrancy. A simulation study revealed that the method could recover previously distorted school performances as aberrant. The proposed technique was applied to a Peruvian national reading assessment in grade 4th of primary education for which the government provided a school performance incentive bonus.
Keywords: influential analysis; aberrant school performance; high-stakes assessments; beta inflated mean regression.
International Journal of Quantitative Research in Education, 2020 Vol.5 No.2, pp.173 - 193
Received: 13 Jan 2019
Accepted: 06 Oct 2019
Published online: 11 Nov 2020 *