Theoretical and Natural Science
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Theoretical and Natural Science
Vol. 19, 08 December 2023
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Assessing the effects of different factors on students’ math grade: evidence from ECLS-K dataset
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Abstract
This study examined the causal effect of the Early Childhood Longitudinal Study, Kindergarten Class of 1998–1999 (ECLS-K) program on students’ academic achievements in math. Moreover, factors heavily impacting students’ fifth grade math score are also explored. The result indicates that the ECLSK program has insignificant negative impact on student’s math score. Kindergarten math score, fine motor skill and gender are top three positive factors and child’s age at k entry, ECLS training program, attended head start are top three negative factors. These results provide a framework for educators to help children improve their math score.
Keywords
Rubin Causal Model, Bayesian Additive Regression Tree, Machine Learning, ECLS-K dataset.
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-203-9
- ISBN (Online)
- 978-1-83558-204-6
- Published Date
- 08 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/19/20230522
- Copyright
- 08 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited