As the modal sources of data in education have shifted over the past few decades, so too have the modeling paradigms applied to these data. In this paper, we overview the principle foci of modeling in the areas of standardized testing, computer tutoring, and online courses from whence these big data have come, and provide a rationale for their adoption in each context. As these data become more behavioral in nature, we argue that a shift to connectionist paradigms of modeling is called for as well as a reaffirming of the ethical responsibilities of big data analysis in education.