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Vitale, Jonathan M.; McBride, Elizabeth; Linn, Marcia C. – International Journal of Science Education, 2016
We compared two forms of automated guidance to support students' understanding of climate change in an online inquiry science unit. For "specific" guidance, we directly communicated ideas that were missing or misrepresented in student responses. For "knowledge integration" guidance, we provided hints or suggestions to motivate…
Descriptors: Climate, Change, Comparative Analysis, Science Instruction
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Lee, Young-Jin – Educational Technology & Society, 2015
This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…
Descriptors: Physics, Science Instruction, Computer Software, Accuracy
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Zhang, Lishan; VanLehn, Kurt – Interactive Learning Environments, 2017
The paper describes a biology tutoring system with adaptive question selection. Questions were selected for presentation to the student based on their utilities, which were estimated from the chance that the student's competence would increase if the questions were asked. Competence was represented by the probability of mastery of a set of biology…
Descriptors: Biology, Science Instruction, Intelligent Tutoring Systems, Probability
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Domin, Daniel; Bodner, George – Journal of Chemical Education, 2012
The differences in the types of representations constructed during successful and unsuccessful problem-solving episodes were investigated within the context of graduate students working on problems that involve concepts from 2D-NMR. Success at problem solving was established by having the participants solve five problems relating to material just…
Descriptors: Accuracy, Problem Solving, Graduate Students, Spectroscopy