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Random Forest Analysis of Factors Predicting Science Achievement Groups: Focusing on Science Activities and Learning in School
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Hong, Jeehye; Kim, Hyunjung; Hong, Hun-Gi – Asia-Pacific Science Education, 2022
This study explored science-related variables that have an impact on the prediction of science achievement groups by applying the educational data mining (EDM) method of the random forest analysis to extract factors associated with students categorized in three different achievement groups (high, moderate, and low) in the Korean data from the 2015…
Descriptors: Science Achievement, Prediction, Teaching Methods, Science Teachers
Educational Data Mining: The Analysis of the Factors Affecting Science Instruction by Clustering Analysis
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Eser, Mehmet Taha; Çobanoglu Aktan, Derya – International Journal of Educational Methodology, 2021
Science literacy, which is included in Programme for International Student Assessment (PISA) as an assessment area, is an important research and discussion area of science education literature with all its dimensions. In this study, the clustering results of the students from 34 Organization for Economic Cooperation and Development (OECD)…
Descriptors: Data Analysis, Learning Analytics, Science Education, Scores