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- W2017004753 abstract "As a step towards scaling personalized instruction, we seek to automatically identify the key features of the interactive learning process teachers use to select the next activity when teaching a single student. Such features could both inform computational student models designed to facilitate instructional decisions, and help enable automated self-improving teaching systems that leverage this identified feature set. We present preliminary results that a very small set of features is almost as good as a much larger set of features at predicting human tutor decisions when teaching students about histograms." @default.
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- W2017004753 date "2015-03-14" @default.
- W2017004753 modified "2023-10-01" @default.
- W2017004753 title "Learning the Features Used To Decide How to Teach" @default.
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- W2017004753 doi "https://doi.org/10.1145/2724660.2728707" @default.
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