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Data Collection: 840 student constructed responses to physics questions

Identifying Students’ Gradual Understanding of Physics Concepts Using TagHelper Tools. Nava L. Livne, Oren E. Livne, University of Utah. Driving Research Question: Can a machine identify students’ gradual understanding of physics concepts?.

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Data Collection: 840 student constructed responses to physics questions

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  1. Identifying Students’ Gradual Understanding of Physics Concepts Using TagHelper Tools Nava L. Livne, Oren E. Livne, University of Utah Driving Research Question: Can a machine identify students’ gradual understanding of physics concepts? Hypothesis - IBAT learning model: Students learn in four stages Student Conceptual Learning Transfer principles to complex scenarios Advanced principles Basic notions Ignoring irrelevant data Time Data Collection:840 student constructed responses to physics questions Classified into 4 categories by humans - Can TagHelper Tools automatically classify responses into these categories? ValidationSet: the other 420 DevelopmentSet: 420, randomly selected TagHelper Results:TagHelper correctly classified 70% of the responses into the I, B, A and T categories! (κ = 0.54) Lesson Learned:TagHelper is a powerful text analysis tool, but limited to identifying structural patterns within its feature space PSLC Summer School, June 21, 2007

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