Complexity, Emergence, and Synthetic Models in Science Education

2001 ◽  
pp. 173-198
2021 ◽  
Vol 27 ◽  
Author(s):  
Juliana Machado ◽  
Bruna Levy Pestana Fernandes

Abstract: Despite the ubiquity of models in science education, there are several different conceptions about their nature in the scientific community. We sought to investigate understandings about them conveyed in the recent research in science education. To this end, we have reviewed papers published on models and modelling between 2010 and 2019. Our analysis revealed that these different notions on the concept of model could be represented in three main trends: Concrete, Construct and Mathematical. In addition, we found that these studies: are predominantly empirical in nature; involve frameworks arising mainly from science education research itself, but with a considerable influence from Philosophy of Science and cognitive sciences; encompass Physics, Biology and Chemistry domains in relatively similar frequencies, but decreasing in this order. Another outcome of this study was the emergence of different scenarios regarding the journals consulted, revealing the existence of different thought styles in science education research community.


Author(s):  
Jan Winkelmann

AbstractIdealizations are omnipresent in science. However, to date, science education research has paid surprisingly little attention to the use of idealizations in fostering students’ model competence and understanding of the nature of science (NOS). The starting point for the theoretical reflection in this paper is that insufficient consideration of idealizations in the science classroom can lead to learning difficulties. The following discussions should help to clarify the terms idealization and model and their relationship to each other. An example is drawn from physics. At least two cases can apply when considering model usage in the classroom. In the first case, to understand an observed phenomenon, a model (as a representation) of the situation to be explained is constructed. At this point, it is necessary to perform idealization. Seemingly, this step is still neglected in much of the science education literature but is well addressed in the philosophy of science. In the second case, existing models to work with are introduced, perhaps alongside a real experimental situation. This approach is called working with models in science education. This paper focuses primarily on the first case. Against the background of model building, a positioning and conceptual approximation of idealizations take place. To organize the idealization process, a framework of several categories of idealization adopted from science philosophy is offered. The framework is intended to stimulate explicit reflection about how models are constructed. The construction of a model by idealization is illustrated through an example from geometrical optics. Finally, the considerations presented are discussed in the context of the literature, and suggested research topics are provided.


2018 ◽  
Vol 14 (3) ◽  
pp. 239-249 ◽  
Author(s):  
Per-Olof Wickman ◽  
Karim Hamza ◽  
Iann Lundegård

This article reviews what didactic models are, how they can be produced through didactic modelling and how didactic models can be used for analyses of teaching and learning and for educational designs. The article is as an introduction to this Nordina special issue on didactic models and didactic modelling in science education research.


2003 ◽  
Vol 87 (4) ◽  
pp. 618-620
Author(s):  
Barbara Hug

2007 ◽  
Vol 16 (7-8) ◽  
pp. 647-652 ◽  
Author(s):  
Michael R. Matthews

Author(s):  
John K. Gilbert ◽  
Carolyn J. Boulter ◽  
Margaret Rutherford

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