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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
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Gobert, Janice D.; Sao Pedro, Michael; Raziuddin, Juelaila; Baker, Ryan S. – Journal of the Learning Sciences, 2013
We present a method for assessing science inquiry performance, specifically for the inquiry skill of designing and conducting experiments, using educational data mining on students' log data from online microworlds in the Inq-ITS system (Inquiry Intelligent Tutoring System; www.inq-its.org). In our approach, we use a 2-step process: First we use…
Descriptors: Intelligent Tutoring Systems, Science Education, Inquiry, Science Process Skills