Many model-building learning environments (MBEs) have been developed to support students in acquiring the ability to build appropriate models of physical systems. However, they can't explain how the simulated behavior of an erroneous model is unnatural. Additionally, they can't create any feedback when the model is unsolvable. We introduce a MBE which overcomes these problems with two technical ideas: (1) robust simulator which analyzes the consistency of a model and relaxes some constraints if necessary, and (2) semantics of constraints which is a systematic description of physical meanings of constraints and provides heuristics for explaining the behavioral unnaturalness. © 2012 Springer-Verlag.
CITATION STYLE
Horiguchi, T., Hirashima, T., & Forbus, K. D. (2012). A model-building learning environment with explanatory feedback to erroneous models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7315 LNCS, pp. 620–621). https://doi.org/10.1007/978-3-642-30950-2_90
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