Crossmark

Machine Learning Approaches for Predicting U.S. Students’ Scientific Literacy: An Analysis of Key Factors Across Performance Levels and Socioeconomic Statuses

Crossref DOI link: https://doi.org/10.1007/s10763-025-10545-y

Published Online: 2025-01-24

Published Print: 2025-10

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

You, Hyesun https://orcid.org/0000-0002-5835-5053
Hong, Minju https://orcid.org/0000-0002-4116-9908
Zhu, Li https://orcid.org/0009-0003-4453-6165
Zhenhan, Fang https://orcid.org/0009-0008-0420-2175
License Information

Text and Data Mining valid from 2025-01-24

Version of Record valid from 2025-01-24
More Information

Article History

Received: 20 August 2024

Accepted: 8 January 2025

First Online: 24 January 2025

Declarations

:

: This research is carried out in accordance to ethics recommendations. Because this research used secondary data and its analysis, ethics approval by the University ethics committee does not apply.

Document is current

Any future updates will be listed below