Under the auspices of the Society for Women's Health Research, a thought leaders' roundtable was convened at the National Institute of Environmental Health Sciences in October 2002 to discuss recent advances in environmental health research, particularly those findings that explain sex differences in response to environmental exposures. Researchers discussed the latest findings on the interacti...

We propose a novel extension of the encoder-decoder framework, called a review network. The review network is generic and can enhance any existing encoderdecoder model: in this paper, we consider RNN decoders with both CNN and RNN encoders. The review network performs a number of review steps with attention mechanism on the encoder hidden states, and outputs a thought vector after each review s...

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We have proposed a novel application of Markov decision processes (MDPs), a reinforcement learning technique, to automatically generate hints using historical student data. Using this technique, we have modified a an existing, non-adaptive logic proof tutor called Deep Thought with a Hint Factory that provides hints on the next step a student might take. This paper presents the results of our p...

This work explores the effects of using automatically generated hints in Deep Thought, a propositional logic tutor. Generating hints automatically removes a large amount of development time for new tutors, and it also useful for already existing computer-aided instruction systems that lack intelligent feedback. We focus on a series of problems, after which, the control group is known to be 3.5 ...

The interactions of concepts and problem-solving techniques needed to solve open-ended proof problems are varied, making it difficult to select problems that improve individual student performance. We have developed a system of datadriven ordered problem selection for Deep Thought, a logic proof tutor. The problem selection system presents problem sets of expert-determined higher or lower diffi...