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Published in:
2015 | OriginalPaper | Chapter
Challenges of Using Observational Data to Determine the Importance of Example Usage
Authors : Yun Huang, José P. González-Brenes, Peter Brusilovsky
Published in: Artificial Intelligence in Education
Publisher: Springer International Publishing
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Educational interventions are often evaluated with randomized control trials, which can be very expensive to conduct. One of the promises of “Big Data” in education is to use non-experimental data to discover insights. We focus on studying the impact of example usage in a Java programming tutoring system using observational data. For this, we compare different formulations of a recently proposed generalized Knowledge Tracing framework called FAST. We discover that different formulations can have the same predictive performance; yet their coefficients may have opposite signs, which may lead researchers to contradictory conclusions. We discuss implications of using fully data-driven approaches to study non-experimental data.