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Proportional reasoning is foundational in school mathematics. Despite the importance of proportional reasoning there has been little written about the knowledge needed for teaching proportional reasoning or the organization of that knowledge. In this paper we present a definition for a robust understanding of proportional reasoning for teaching. We also present a coding scheme that has been developed to begin to investigate what knowledge resources teachers evoke when dealing with proportional situations and how those knowledge resources are connected. Our goal is to present the initial steps we have taken to investigate what a robust understanding of proportions for teaching is and how it might be operationalized for data analysis.
Travis Weiland, University of Massachusetts - Dartmouth
Chandra H. Orrill, University of Massachusetts - Dartmouth
Rachael Eriksen Brown, Penn State Abington
Gal Gili Nagar, University of Massachusetts - Dartmouth
James P. Burke, University of Massachusetts - Dartmouth