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Effect of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths
2009
Artificial Intelligence in Medicine
Preserved Fulltext
both errors and goal differences. However, the rate at which students progress toward the optimal solution path differs between the two domains. Tutoring in superficial perivascular dermatitis, the larger and more complex domain was associated with a slower rate of approximation towards the optimal solution path. Conclusions: Students benefit from a limited-enforcement tutoring system that leverages diagnostic algorithms but does not prevent alternative strategies. Even with limited
doi:10.1016/j.artmed.2009.07.002
pmid:19782544
fatcat:ufdwwbxpwjax3pdt7eaxljdjuu