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Download full textBozak, Ali; Aybek, Eren Can – International Journal of Contemporary Educational Research, 2020
The present study aims to determine which analysis technique-Artificial Neural Networks (ANNs) or Logistic Regression (LR) Analysis-is better at predicting the science literacy success of the 15-year Turkish students who participated in PISA research carried out in 2015 by using learning time spent on science, test anxiety, environmental…
Descriptors: Artificial Intelligence, Networks, Regression (Statistics), Achievement Tests
Direct linkChen, Jiangping; Zhang, Yang; Wei, Yueer; Hu, Jie – Research in Science Education, 2021
Science excellence is associated not only with a student's inherent aptitude but also a range of contextual factors. The objective of this paper was to identify the most important contextual characteristics of top performers in scientific literacy, by simultaneously considering factors at the PISA questionnaire-based student, family, and school…
Descriptors: Scientific Literacy, Science Achievement, High Achievement, Foreign Countries
Lau, Kwok Chi – Asia-Pacific Forum on Science Learning and Teaching, 2014
The study has integrated the data from PISA 2006 to 2012 to give an overall picture of the cognitive and affective performances and pedagogy of East Asian regions on PISA scientific literacy. Attempts are made to account for their performances based on the PISA data and cultural characteristics. The cognitive science performance of East Asian…
Descriptors: Foreign Countries, Science Education, Scientific Literacy, Achievement Tests
Woods-McConney, Amanda; Oliver, Mary C.; McConney, Andrew; Maor, Dorit; Schibeci, Renato – Research in Science Education, 2013
Previous research has underlined the importance of school students' engagement in science (including students' attitudes, interests and self beliefs). Engagement in science is important as a correlate of scientific literacy and attainment, and as an educational outcome in its own right. Students positively engaged with science are more likely to…
Descriptors: Foreign Countries, Learner Engagement, Regression (Statistics), Models
