gms | German Medical Science

GMS Journal for Medical Education

Gesellschaft für Medizinische Ausbildung (GMA)

ISSN 2366-5017

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A comparison of scoring algorithms for multiple answer MC-exams

Kurzfassung Vortrag Humanmedizin

Suche in Medline nach

  • corresponding author presenting/speaker Martin Fischer - Medizinische Klinik Innenstadt der Universität München, Schwerpunkt Medizindidaktik, München, Deutschland
  • Daniel Bauer
  • Veronika Kopp

GMS Z Med Ausbild 2005;22(4):Doc187

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter: http://www.egms.de/de/journals/zma/2005-22/zma000187.shtml

Eingereicht: 15. Juli 2005
Veröffentlicht: 18. November 2005

© 2005 Fischer et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.

Gliederung

Workshop

Objectives: To compare different scoring algorithms usually employed in determining students scores in multiple correct answer multiple-choice (MC) exams regarding performance, reliability, selectivity, and item difficulty.

Methods: Data from 420 3rd year medical students' end of term exam in internal medicine in February 2005 at Munich University were analysed (30 MC questions; up to 15 possible answers, up to 6 correct answers per question, at least as many distractors as true answers).

Scoring Algorithms: Each question scored a maximum of one point. No negative scores were applied. We compared:

- "Dichotomous" (D): One point if all true and no wrong answers were chosen.

- "Partial 1" (P1): One point for 100% true answers; 0.5 points for 50% or more true answers; zero points for less than 50% true answers.

- "Partial 2" (P2): A fraction of one point depending on the total number of possible answers was given for each correct decision (picking a right or ignoring a wrong answer); for each wrong decision one such fraction was subtracted.

Results: The P1-algorithm showed best results concerning item selectivity, item difficulties, and internal consistency (Cronbach's alpha), respectively.

Conclusions: The P1-algorithm seems to be the preferable method for the scoring of multiple answer MC-exams.