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Learning from Learning Curves: Discovering Interpretable Learning Trajectories
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Lujie Chen; Artur Dubrawski – Grantee Submission, 2017
We propose a data driven method for decomposing population level learning curve models into mutually exclusive distinctive groups each consisting of similar learning trajectories. We validate this method on six knowledge components from the log data from an online tutoring system ASSISTment. Preliminary analysis reveals interpretable patterns of…
Descriptors: Learning Trajectories, Learning Processes, Intelligent Tutoring Systems, Cluster Grouping