Events and Meetings of Italian Statistical Society, Statistics and Demography: the Legacy of Corrado Gini

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A multistep approach to detect and correct the cheating in Italian students data.
Patrizia Falzetti, Sergio Longobardi, Paolo Sestito

Last modified: 2015-09-04

Abstract


We analyze students data carried out by INVALSI and propose a Multi Step Approach (MSA) for cheating detection and correction. This method integrates the "mechanistic" logic of fuzzy clustering with a statistical model based approach. The procedure aims to minimize the detection of false positives and to correct test scores at both class and student level. The results show a normalization of the scores and a stronger correction on Southern regions data where the propensity to cheating appears to be highest.

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