Using Analytics on Student Created Data to Content Validate Pedagogical
  Tools
John Kos Kenneth Eaton Sareen Zhang Rahul Dass Stephen Buckley Sungeun An Ashok Goel
Conceptual and simulation models can function as useful pedagogical tools,
however it is important to categorize different outcomes when evaluating them
in order to more meaningfully interpret results. VERA is a ecology-based
conceptual modeling software that enables users to simulate interactions
between biotics and abiotics in an ecosystem, allowing users to form and then
verify hypothesis through observing a time series of the species populations.
In this paper, we classify this time series into common patterns found in the
domain of ecological modeling through two methods, hierarchical clustering and
curve fitting, illustrating a general methodology for showing content validity
when combining different pedagogical tools. When applied to a diverse sample of
263 models containing 971 time series collected from three different VERA user
categories: a Georgia Tech (GATECH), North Georgia Technical College (NGTC),
and ``Self Directed Learners'', results showed agreement between both
classification methods on 89.38\% of the sample curves in the test set. This
serves as a good indication that our methodology for determining content
validity was successful.