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Moonhyun Han; Janghee Uhm – International Journal of Science and Mathematics Education, 2024
This qualitative case study investigated how computational models can help students engage in scientific practice and influence their emotional, epistemic, and conceptual aspects. Twenty-four sixth-graders were guided to conduct scientific practices as they predicted and modified the computational models on food web using StarLogo Nova. Three…
Descriptors: Grade 6, Thinking Skills, Computation, Models
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Nicolaou, Chr. Th.; Evagorou, M.; Lymbouridou, Chr. – Science Education International, 2015
Despite the belief that emotions are important in the learning process, research in the area of emotions and learning, especially in science, is scant. Modelling and SSI argumentation have shared with respect to the emphasis in recent science standards reports as core scientific practices that need to be part of science teaching and learning. Even…
Descriptors: Elementary School Students, Science Instruction, Elementary School Science, Interviews
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Louca, Loucas T.; Zacharia, Zacharias C.; Michael, Michalis; Constantinou, Constantinos P. – Journal of Educational Computing Research, 2011
The purpose of this study was to develop a framework for analyzing and evaluating student-constructed models of physical phenomena and monitoring the progress of these models. Moreover, we aimed to examine whether this framework could capture differences between models created using different computer-based modeling tools; namely, computer-based…
Descriptors: Foreign Countries, Programming, Classification, Student Evaluation
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection