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Publication in EndNote Format

%0 Conference Proceedings %A Melinda Gervasio and Karen Myers and Michael Wessel %T Demonstration-based Solution Authoring for Skill Assessment %B Advances in Cognitive Systems %V 5 %D 2017 %K intelligent tutoring, assessment, model authoring %X The high cost of developing content has been a major impediment to the widespread deployment of intelligent training systems. To enable automated skill assessment, traditional approaches have required significant time investment by highly trained individuals to encode first-principles domain models for the training task. In contrast, approaches grounded in example-based methods have been shown to significantly reduce authoring time. This paper reports on an approach to creating solution models for automated skill assessment using an example-based methodology, specifically targeting domains for which solution models must support robustness to learner mistakes. With this approach, a content author creates a baseline solution model by demonstrating a solution instance and then specifies a set of annotations to generalize from that instance to a comprehensive solution model. Results from a user study show that domain experts are comfortable with the approach and capable of applying it to generate quality solution models. %U http://www.ai.sri.com/pubs/files/2174.pdf

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