Unveiling Goods and Bads: A Critical Analysis of Machine Learning Predictions of Standardized Test Performance in Early Childhood Education-Reference-Cited by-同舟云学术

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Unveiling Goods and Bads: A Critical Analysis of Machine Learning Predictions of Standardized Test Performance in Early Childhood Education

Published:2024-03-18 Issue: Volume:15 Page:608-619
ISSN:
Container-title:Proceedings of the 14th Learning Analytics and Knowledge Conference
language:
Short-container-title:

Author:

Li Lin¹^ORCID,Srivastava Namrata²^ORCID,Rong Jia³^ORCID,Pianta Gina⁴^ORCID,Varanasi Raju⁴^ORCID,Gašević Dragan¹^ORCID,Chen Guanliang¹^ORCID

Affiliation:

1. Centre for Learning Analytics, Monash University, Australia

2. Penn Center for Learning Analytics, University of Pennsylvania, USA and Centre for Learning Analytics, Monash University, Australia

3. Monash University, Australia

4. Catholic Schools Parramatta Diocese, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3636555.3636920

Reference45 articles.

1. Birth Order and Its Sequelae

2. Predicting K-12 Dropout

3. Using Demographic Data as Predictor Variables: a Questionable Choice;Baker S;Journal of Educational Data Mining,2023

4. Algorithmic Bias in Education

5. Early Childhood Education: The Long-Term Benefits

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