Contrasting Classical and Machine Learning Approaches in the Estimation of Value-Added Scores in Large-Scale Educational Data

Contrasting Classical and Machine Learning Approaches in the Estimation of Value-Added Scores in Large-Scale Educational Data

There is no consensus on which statistical model estimates school value-added (VA) most accurately. To date, the two most common statistical models used for the calculation of VA scores are two classical methods: linear regression and multilevel models. These models have the advantage of being relat...

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Bibliographic Details
Main Authors: Jessica Levy, Dominic Mussack, Martin Brunner, Ulrich Keller, Pedro Cardoso-Leite, Antoine Fischbach
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-08-01
Series:Frontiers in Psychology
Subjects:
value-added modeling
school effectiveness
machine learning
model comparison
longitudinal data
Online Access:https://www.frontiersin.org/article/10.3389/fpsyg.2020.02190/full

Internet

https://www.frontiersin.org/article/10.3389/fpsyg.2020.02190/full

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