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Michael Sao Pedro
Researcher at Worcester Polytechnic Institute
Publications - 38
Citations - 815
Michael Sao Pedro is an academic researcher from Worcester Polytechnic Institute. The author has contributed to research in topics: Educational data mining & MicroWorlds. The author has an hindex of 14, co-authored 36 publications receiving 709 citations. Previous affiliations of Michael Sao Pedro include BAE Systems.
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Journal ArticleDOI
From Log Files to Assessment Metrics: Measuring Students' Science Inquiry Skills Using Educational Data Mining
TL;DR: Evidence is presented that this detector developed in 1 scientific domain can be used—with no modification or retraining—to effectively detect science inquiry skill in another scientific domain, density.
Proceedings ArticleDOI
Leveraging Educational Data Mining for Real-time Performance Assessment of Scientific Inquiry Skills within Microworlds
TL;DR: Science Assistments, an interactive environment, which assesses students’ inquiry skills as they engage in inquiry using science microworlds, is presented, which focuses on the student model, the task model, and the evidence model in the conceptual assessment framework.
Journal ArticleDOI
Leveraging machine-learned detectors of systematic inquiry behavior to estimate and predict transfer of inquiry skill
TL;DR: Machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in planning behaviors using two inquiry support tools are generated, and their skill estimates were significant predictors of the two types of inquiry transfer tests.
Journal ArticleDOI
Using educational data mining to assess students’ skills at designing and conducting experiments within a complex systems microworld
TL;DR: Inq-ITS (inquiry intelligent tutoring system) as discussed by the authors uses educational data mining to assess science inquiry skills, as described as 21st century skills, in the context of complex systems.
Proceedings Article
Incorporating scaffolding and tutor context into Bayesian knowledge tracing to predict inquiry skill acquisition
TL;DR: This paper incorporates scaffolding and change of tutor context within the Bayesian Knowledge Tracing framework to track students’ developing inquiry skills and finds that scaffolding appears to be effective at helping students acquire these skills, and that the skills transfer across topics.