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A structure-mapping-guided self-explanation as a computational account of the cognitive biases that reduce search effort and make this inference tractable and a testable hypothesis about human self-explanation from worked examples are proposed.
A new structure-mapping algorithm: SMTB that is 5--15x faster than the structure-mapping engine (SME) and about 50\% better at finding mappings in large nested domains and an evaluation comparing SMTB to SME v4 over 5845 domain pairs from the SME corpus.
A decision-theoretic model is developed to determine time-efficient confirmation point placement and results show that 81% of participants preferred the intermediate confirmation approach over the confirm-at-end approach used by existing systems, and task completion time was reduced by 13.54%.
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