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Conceptual and simulation models can function as useful pedagogical tools,however it is important to categorize different outcomes when evaluating themin order to more meaningfully interpret results. VERA is a ecology-basedconceptual modeling software that enables users to simulate interactionsbetween biotics and abiotics in an ecosystem, allowing users to form and thenverify hypothesis through observing a time series of the species populations.In this paper, we classify this time series into common patterns found in thedomain of ecological modeling through two methods, hierarchical clustering andcurve fitting, illustrating a general methodology for showing content validitywhen combining different pedagogical tools. When applied to a diverse sample of263 models containing 971 time series collected from three different VERA usercategories: a Georgia Tech (GATECH), North Georgia Technical College (NGTC),and ``Self Directed Learners'', results showed agreement between bothclassification methods on 89.38\% of the sample curves in the test set. Thisserves as a good indication that our methodology for determining contentvalidity was successful.

Using Analytics on Student Created Data to Content Validate Pedagogical Tools