Modeling Competence in the Light of Nature of Science

Abstract

Nature of science encapsulates characteristics of scientific knowledge that make it ``science,'' as opposed to other types of knowledge or ways of understanding the world. Scientific knowledge is generated through practices that are grounded in empirical observations of the natural world. Considering the epistemic nature and functions of models as both products of scientific inquiry, as well as essential to the practices of scientific inquiry, there is a clear connection between the nature of models and the nature of scientific knowledge [NOS]. Modeling competence necessitates an understanding of epistemic practices and epistemic knowledge. This chapter details relationships between NOS principles and modeling competence. For example, the utility of models within scientific research relates to their representation of phenomena or systems. System features are selected based on subjective decisions stemming from scientific questions under study. A requisite for understanding NOS and exhibiting modeling competence is acknowledging both the ontological and epistemological features of models and modeling. That is, a scientific model is not an exact replica of reality, but a representation that serves to explain features and relationships that scientists find curious and significant to their questions. Models also enable prediction and testing; thus, generating new knowledge. Acts of model construction and utility are inherently inferential, creative, and tentative; yet robust due to the empirical basis, and explanatory and predictive power. The chapter also presents examples of models from the scientific community with clear connections to NOS; thus providing insights into the epistemic nature of models and modeling and how scientists are pushing the boundaries of what constitutes ``science'' through modeling efforts.