ICPS

2019 International Convention of Psychological Science · 2019

Identifying Reliable Predictors of Math Performance through Machine-Learning Predictive Modeling.

Paris, France · March 2019

Posters · Cognitive Science

  • Mariel Musso
    UADE
  • Mariel Musso
    CONICET/ University of Granada
  • Eduardo Cascallar
    KU Leuven
  • Neda Bostani
    World Bank Group
  • Michael F. Crawford
    World Bank Group

Abstract

The objective was to develop valid and accurate models predicting low and high levels of math performance, using machine-learning algorithms, as part of an international large-scale project in primary education in Vietnam. Interesting patterns of variables have been identified for both levels, providing a guide for more focused educational interventions.

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