[The Erlangen examination. An alternative to multiple choice testing for German neurology students].
BACKGROUND
With the latest revision of the German Medical Licensing Regulation in 2002, educating faculties gained more freedom in the organisation and assessment of trainees. The Erlangen Neurological Exam Structured (ERNEST) is an alternative for assessing competency in clinical knowledge at the end of the neurological general education. The answers must be given in written, short essay format.


METHODS
The students (mostly 5th year of medical education) underwent the ERNEST including eight sections with ten to 15 questions each and the MC examination as had been applied earlier. The results were given in percentage scores. The examination was evaluated by a questionnaire using Likert scales.


RESULTS
A total of 128 students (81 women, 47 men) with a mean age of 25.3 years (range 22-33) completed their initial training by the exam. The mean score was 69.6% in the ERNEST and 73.4% in the MC part (P<0.001). Of the students 12.5% in ERNEST and 11.7% in the MC (nonsignificant) failed to reach the projected score of 60% to pass the exam. Correlation between the ERNEST and MC results was significant, with r=0.784 (Pearson's coefficient, P<0.001). The students evaluated the aspects innovation, length, format, clarity of the tasks, closeness to reality, and compatibility with general physician's practice as predominantly positive.


CONCLUSIONS
The ERNEST is a viable alternative form of assessment as compared to the conventional MC exam. The basic quantitative parameters of the assessment comply with the requirements of medical assessments. The students evaluated ERNEST as mainly positive.
Heckmann
J G
JG
Neurologische Klinik, Universitätsklinikum, Schwabachanlage 6, Erlangen, Germany. josef.heckmann@uk-erlangen.de
Rauch
C
C
Dütsch
M
M
Lang
C
C
Weih
M
M
Schwab
S
S
D000328:Adult; D004501:Education, Medical / Q000379:methods* / Q000706:statistics & numerical data*; D004521:Educational Measurement / Q000379:methods* / Q000706:statistics & numerical data*; D005260:Female; D005858:Germany; D006801:Humans; D008297:Male; D009462:Neurology / Q000193:education* / Q000706:statistics & numerical data; D013337:Students, Medical / Q000706:statistics & numerical data*