Worldwide predictors of science literacy in lower-secondary students: a TIMSS 2019 analysis-Reference-Cited by-同舟云学术

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Worldwide predictors of science literacy in lower-secondary students: a TIMSS 2019 analysis

Published:2024-09-11 Issue: Volume: Page:1-19
ISSN:0950-0693
Container-title:International Journal of Science Education
language:en
Short-container-title:International Journal of Science Education

Author:

Marôco João¹^ORCID,Harju-Lukkainnen Heidi²³^ORCID,Rautopuro Juhani⁴^ORCID

Affiliation:

1. William James Centre for Research, ISPA – Instituto Universitrio, Lisbon, Portugal

2. University of Jyväskylä, Jyväskylä, Finland

3. Nord University, Bodø, Norway

4. Finnish Institute for Educational Research, University of Jyväskylä, Jyväskylä, Finland

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09500693.2024.2394239

Reference39 articles.

1. Bailey P. Webb B. Kelley C. Nguyen T. & Huo H. (2023). WeMix: Weighted mixed-effects models using multilevel pseudo maximum likelihood estimation (Version 4.0.0) [R package]. CRAN.

2. intsvy: An R Package for Analyzing International Large-Scale Assessment Data

3. Cohen, J. (1998). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.

4. Dickman, A., Schwabe, A., Schmidt, J., & Henken, R. (2009). Preparing the future workforce: Science, technology, engineering, and math (STEM) policy in K-12 education. Public Policy Forum.

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