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- W2003554962 abstract "This paper explores the value of eye-tracking data to assess user learning with interactive simulations (IS). Our long-term goal is to use this data in user models that can generate adaptive support for students who do not learn well with these types of unstructured learning environments. We collected gaze data from users interacting with the CSP applet, an IS for constraint satisfaction problems. Two classifiers built upon this data achieved good accuracy in discriminating between students who learn well from the CSP applet and students who do not, providing evidence that gaze data can be a valuable source of information for building user modes for IS." @default.
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- W2003554962 date "2012-01-01" @default.
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- W2003554962 title "Exploring Gaze Data for Determining User Learning with an Interactive Simulation" @default.
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- W2003554962 doi "https://doi.org/10.1007/978-3-642-31454-4_11" @default.
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