Using machine learning to predict student science achievement based on science curriculum type in TIMSS 2019-Reference-Cited by-同舟云学术

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Using machine learning to predict student science achievement based on science curriculum type in TIMSS 2019

Published:2024-06-15 Issue: Volume: Page:1-45
ISSN:0950-0693
Container-title:International Journal of Science Education
language:en
Short-container-title:International Journal of Science Education

Author:

Song Yajie¹,Cutumisu Maria¹^ORCID

Affiliation:

1. Department of Educational and Counselling Psychology, Faculty of Education, McGill University, Montreal, Canada

Funder

Fonds de Recherche du Québec - Santé

Government of Canada

Natural Sciences and Engineering Research Council of Canada

Social Sciences and Humanities Research Council of Canada

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09500693.2024.2359099

Reference66 articles.

1. Factors Affecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques

2. What Schools Need to Know About Fostering School Belonging: a Meta-analysis

3. High-Stakes Testing and Curricular Control: A Qualitative Metasynthesis

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