An interactive tool for supporting error analysis for text mining
HLT-DEMO '10 Proceedings of the NAACL HLT 2010 Demonstration Session
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Evaluating the effectiveness of tutorial dialogue instruction in an exploratory learning context
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
DIGITEL '12 Proceedings of the 2012 IEEE Fourth International Conference On Digital Game And Intelligent Toy Enhanced Learning
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SimStudent, an intelligent-agent architecture that generates a cognitive model from worked-out examples, currently interacts with human subjects only in a limited capacity. In our application, SimStudent attempts to solve algebra equations, querying the user about the correctness of each step as it solves, and the user explains the step in natural language. Based on that input, SimStudent can choose to ask further questions that prompt the user to think harder about the problem in an attempt to elicit deeper responses. We show how text classification techniques can be used to train models that can distinguish between different categories of student feedback to SimStudent, and how this enables interaction with SimStudent in a pilot study.