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Sao Pedro, Michael A.; Gobert, Janice D.; Baker, Ryan S. – Grantee Submission, 2014
We explore in this paper if automated scaffolding delivered via a pedagogical agent within a simulation can help students acquire data collection inquiry skills. Our initial analyses revealed that such scaffolding was effective for helping students who initially did not know two specific skills, designing controlled experiments and testing stated…
Descriptors: Automation, Scaffolding (Teaching Technique), Intelligent Tutoring Systems, Data Collection
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Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D. – Grantee Submission, 2013
When validating assessment models built with data mining, generalization is typically tested at the student-level, where models are tested on new students. This approach, though, may fail to find cases where model performance suffers if other aspects of those cases relevant to prediction are not well represented. We explore this here by testing if…
Descriptors: Educational Research, Data Collection, Data Analysis, Generalizability Theory
Gobert, Janice Darlene; Sao Pedro, Michael A.; Baker, Ryan S. – Grantee Submission, 2012
In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry skills in another domain (phase change). To do so, we leveraged educational data mining…
Descriptors: Data Collection, Learning Analytics, Inquiry, Science Process Skills