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- W2342061046 abstract "Data-driven methods have previously been used in intelligent tutoring systems to improve student learning outcomes and predict student learning methods. We have been incorporating data-driven methods for feedback and problem selection into Deep Thought, a logic tutor where students practice constructing deductive logic proofs. In this latest study we have implemented our data-driven proficiency profiler (DDPP) into Deep Thought as a proof of concept. The DDPP determines student proficiency without expert involvement by comparing relevant student rule scores to previous students who behaved similarly in the tutor and successfully completed it. The results show that the DDPP did improve in performance with additional data and proved to be an effective proof of concept." @default.
- W2342061046 created "2016-06-24" @default.
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- W2342061046 date "2016-04-25" @default.
- W2342061046 modified "2023-09-29" @default.
- W2342061046 title "Data-driven proficiency profiling" @default.
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- W2342061046 doi "https://doi.org/10.1145/2883851.2883935" @default.
- W2342061046 hasPublicationYear "2016" @default.
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