Li, N., Matsuda, N., Cohen, W. W., & Koedinger, K. R. (2010). Towards a computational model of why some students learn faster than others. Proceedings of the AAAI 2010 Fall Symposium on the Cognitive and Metacognitive Educational Systems (pp.40-46). Arlington, VA.
Learners that have better metacognition acquire knowledge faster than others who do not. If we had better models of such learning, we would be able to build a better metacognitive educational system. In this paper, we propose a computational model that uses a probabilistic context free grammar induction algorithm yielding metacognitive learning by acquiring deep features to assist future learning. We discuss the challenges of integrating this model into a synthetic student, and possible future studies in using this model to better understand human learning. Preliminary results suggest that both stronger prior knowledge and a better learning strategy can speed up the learning process. Some model variations generate human-like error pattern.
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