Purpose: The KBIT tutorial approach presents many (>50) case examples of a target presentation, such as chest pain, to sharpen students’ ability to recognize and discriminate different diagnostic categories. In a previous study, study booklets highlighting particular symptoms’ ability to discriminate confusable diagnoses improved students’ diagnostic accuracy. Here we compared three formats of computer-generated error feedback, varying their focus on symptoms that discriminate right case diagnosis from student’s wrong answer.
Method: 53 physician assistant students (Study 1) and 54 PA, 15 MD, and 15 other students (Study 2) completed pretest, tutorial, posttest, and 2 week follow-up test. The students studied each of 9 diagnoses’ symptom lists, then diagnosed 49 practice cases described in terms of history and physical, with multiple choice response and immediate error feedback. Students were randomized to receive different error feedback for misdiagnosed cases: prototype of right answer (1 column feature list); features common to both right answer and student’s wrong answer plus features unique to right answer (2 column); or common features plus those unique to each disease (3 column). Study 1 participants saw 3 diseases in each of the three formats, counterbalanced. Study 2 participants saw just one format. Tests presented similar cases, without feedback, with 17 items repeated on all three occasions. Cases’ surface details and case order were varied upon repetition.
Result: In Studies 1&2, participants diagnosed significantly more of the 17 repeated cases on post test (74%/67%) and 2-week follow up (59%/49%) than on pretest (43%/36%). At each time point, students diagnosed correctly more items considered “easier” on the basis of KBIT’s underlying prototype theory of category learning. The expected differences in accuracy gain due to the format of error feedback were not observed.
Conclusion: The study demonstrated that the tutorial, with its error feedback for many cases, using any of the three forms of error feedback, contributes to student learning of chest pain diagnosis. Contrary to expectation, students did not learn more about those diseases for which they had received 2 or 3 column feedback, which highlight symptoms’ ability to discriminate between diagnoses, compared to the simple reminder of the correct diagnosis’ symptoms. Possible explanations include: insufficient training in use of tutorial feedback, limited exposure (few errors), test cases insensitive to lessons learned, or adequacy of the prototype feedback.