Assessment of multiple choice question exams quality using graphical methods

Authors

  • Mustafa S. Yousuf Hashemite University, Jordan
  • Katherine Miles Hashemite University, Jordan
  • Heather Harvey Limestone University, United States of America
  • Mohammad Al-Tamimi Hashemite University, Jordan
  • Darwish Badran University of Jordan, Jordan

Keywords:

control charts, exam analysis, medical exams, receiver operator characteristic curve

Abstract

Exams should be valid, reliable, and discriminative. Multiple informative methods are used for exam analysis. Displaying analysis results numerically, however, may not be easily comprehended. Using graphical analysis tools could be better for the perception of analysis results. Two such methods were employed: standardized x-bar control charts with standard error of measurement as control limits and receiver operator characteristic curves. Exams of two medical classes were analyzed. For each exam, the mean, standard deviation, reliability, and standard error of measurement were calculated. The means were standardized and plotted against the reference lines of the control chart. The means were chosen as cut-off points to calculate sensitivity and specificity. The receiver operator characteristic curve was plotted and area under the curve determined. Standardized control charts allowed clear, simultaneous comparison of multiple exams. Calculating the control limits from the standard error of measurement created acceptable limits of variability in which the standard deviation and reliability were incorporated. The receiver operator characteristic curve graphically showed the discriminative power of the exam. Observations made with the graphical and classical methods were consistent. Using graphical methods to analyse exams could make their interpretation more accessible and the identification of exams that required further investigation easier.

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Published

2022-02-01

Issue

Section

Articles

How to Cite

Assessment of multiple choice question exams quality using graphical methods. (2022). Journal of University Teaching and Learning Practice, 19(3). https://open-publishing.org/journals/index.php/jutlp/article/view/576