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Related Experiment Video

Updated: Jun 7, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Pick-N multiple choice-exams: a comparison of scoring algorithms.

Daniel Bauer¹, Matthias Holzer, Veronika Kopp

¹Faculty of Health, Institute for Teaching and Educational Research in Health Sciences, Witten/Herdecke University, Germany. daniel.bauer@uni-wh.de

Advances in Health Sciences Education : Theory and Practice

|November 2, 2010

Summary

Comparing scoring algorithms for multiple-choice exams, partial credit methods like PS(50) and PS(1/m) showed superior psychometric results compared to dichotomous scoring (DS) for medical students. Partial knowledge should be awarded in Pick-N exams.

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Area of Science:

Medical Education
Psychometrics
Assessment

Background:

Multiple-choice (MC) exams are widely used in medical education.
Traditional dichotomous scoring (DS) may not accurately reflect partial knowledge.
Pick-N format allows for multiple correct answers per item.

Purpose of the Study:

To compare the psychometric properties of different scoring algorithms for Pick-N MC exams.
To evaluate test reliability, student performance, item discrimination, and item difficulty.
To determine the suitability of scoring algorithms for undergraduate medical examinations.

Main Methods:

Analysis of data from six internal medicine end-of-term exams (2005-2008) at Munich University.
Involved 1,255 third-year medical students and 180 Pick-N items.
Compared Dichotomous Scoring (DS), Partial Credit algorithm 1 (PS(50)), and Partial Credit algorithm 2 (PS(1/m)).

Main Results:

Partial credit algorithms (PS(50), PS(1/m)) demonstrated superior psychometric results compared to DS.
PS(50) slightly outperformed PS(1/m) in reliability coefficients.
All algorithms showed similar psychometric data overall.

Conclusions:

Partial credit scoring algorithms are well-suited for Pick-N MC exams in undergraduate medical education.
Awarding partial knowledge in Pick-N exams enhances assessment accuracy.
PS(50) and PS(1/m) offer improved psychometric properties over DS.