Our results demonstrate that the case-based, worked example approach is effective and efficient.

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The purpose of our study was the development and validation of a modified electronic key feature exam of clinical decision-making skills for undergraduate medical students. Therefore, the reliability of the test (15 items), the item difficulty level, the item-total correlations and correlations to other measures of knowledge (40 item MC-test and 580 items of German MC-National Licensing Exam, Part II) were calculated. Based on the guidelines provided by the Medical Council of Canada, a modified electronic key feature exam for internal medicine consisting of 15 key features (KFs) was developed for fifth year German medical students. Long menu (LM) and short menu (SM) question formats were used. Acceptance was assessed through a questionnaire. Thirty-seven students from four medical schools voluntarily participated in the study. The reliability of the key feature exam was 0.65 (Cronbach's alpha). The items' difficulty level scores were between 0.3 and 0.8 and the item-total correlations between 0.0 and 0.4. Correlations between the results of the KF exam and the other measures of knowledge were intermediate (r between 0.44 and 0.47) as well as the learners' level of acceptance. The modified electronic KF examination is a feasible and reliable evaluation tool that may be implemented for the assessment of clinical undergraduate training.

To compare different scoring algorithms for Pick-N multiple correct answer multiple-choice (MC) exams regarding test reliability, student performance, total item discrimination and item difficulty. Data from six 3rd year medical students' end of term exams in internal medicine from 2005 to 2008 at Munich University were analysed (1,255 students, 180 Pick-N items in total). Scoring Algorithms: Each question scored a maximum of one point. We compared: (a) Dichotomous scoring (DS): One point if all true and no wrong answers were chosen. (b) Partial credit algorithm 1 (PS(50)): One point for 100% true answers; 0.5 points for 50% or more true answers; zero points for less than 50% true answers. No point deduction for wrong choices. (c) Partial credit algorithm 2 (PS(1/m)): A fraction of one point depending on the total number of true answers was given for each correct answer identified. No point deduction for wrong choices. Application of partial crediting resulted in psychometric results superior to dichotomous scoring (DS). Algorithms examined resulted in similar psychometric data with PS(50) only slightly exceeding PS(1/m) in higher coefficients of reliability. The Pick-N MC format and its scoring using the PS(50) and PS(1/m) algorithms are suited for undergraduate medical examinations. Partial knowledge should be awarded in Pick-N MC exams.

By providing erroneous examples in combination with elaborated feedback in a computer-based learning environment, diagnostic knowledge was fostered. The approach of 'learning from worked examples' was successfully adapted to a complex domain and was found to support the acquisition of complex competencies.