Models and Modelling in Physics Education: A Critical Re-analysis of Philosophical Underpinnings and Suggestions for Revisions
By Ismo T. Koponen. 2007
159 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, History and Philosophy of Science, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/ff4358823a628580f78686d0549ebfe58994f0a4
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In Cognitive Neuroscience
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Citations in the corpus
- In Quest of Productive Modeling-Based Learning Discourse in Elementary School Science (2011, background): “In this sense, science is viewed as a complex and dynamic network of models, which are the core components of scientific theories and they take a central role in the formation and the justification of scientific knowledge (Koponen, 2007; Pluta, Chinn, & Duncan, 2011; Schwarz et al., 2009; Windschitl”
- What Teachers of Science Need to Know about Models: An overview (2011, background): “But models do not only represent realworld systems by the process of mirroring or mimicking nature (Koponen, 2007).”
- Modelling and representing: An artefactual approach to model-based representation (2011, methodology): “Furthermore, in scientific practice the fitting of experimental data with models is often a bi-directional process in which the model and the data are tailored to fit each other (Cartwright 1999a, Koponen 2007).”
- Modeling-based learning in science education: cognitive, metacognitive, social, material and epistemological contributions (2012, methodology): “Thus, modeling plays a central role in the formation and justification of new knowledge (Halloun 2006; Koponen 2007).”