Abstract
The acquisition of procedural skills requires learning by doing. Ideally, a student would receive real-time assessment and feedback as he attempts practice problems designed to exercise the targeted skills. This paper describes an automated assessment and feedback capability that has been applied to training for a complex software system in widespread use throughout the U.S. Army. The automated assessment capability uses soft graph matching to align a trace of student actions to a predefined gold standard of allowed solutions, providing a flexible basis to evaluate student performance, identify problems, give hints, and suggest pointers to relevant tutorial documentation. Collectively, these capabilities facilitate self-directed learning of the training curriculum.
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Myers, K., Gervasio, M., Jones, C., McIntyre, K., Keifer, K. (2013). Drill Evaluation for Training Procedural Skills. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_60
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DOI: https://doi.org/10.1007/978-3-642-39112-5_60
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