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Modeling competence in contexts: An explanatory study of the effect of contextual features in modeling processes of preservice biology teachers

Subject Area General and Domain-Specific Teaching and Learning
Term since 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 541190827
 
Developing modeling competence is an important goal of biology education. Therefore, by the end of their studies, preservice biology teachers should be able to develop and use models for scientific problem-solving. Several studies are already available on modeling competence, showing that the performance demonstrated by an individual in a test situation can be strongly influenced by the characteristics of the task at hand (“context dependency”). However, these studies are primarily explorative and descriptive; explanatory studies on modeling competence are scarce. Against this background, the present project aims to investigate the influence of contextual features on modeling performance systematically. Modeling performance is operationalized as a sequence of observable activities whose quality can be quantified by their complexity. The following research question is investigated: To what extent do preservice biology teachers' modeling processes (i.e., modeling performance) in authentic biological problems differ as a function of the epistemological goals conveyed in the problems and the recognizability of the deep structures of the problems? To answer the research question, the present study follows an explanatory, experimental design in which the influence of the independent variables epistemological goal and recognizability of deep structure on participants' modeling processes in two biological problems are investigated. The quality of the modeling processes in relation to observable activities is considered as the dependent variable and quantified as the complexity of the modeling processes. The biological problems will be presented to the participants in a digital elicitation tool and the models will be developed using the digital modeling tool SageModeler.
DFG Programme Research Grants
 
 

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