Targeting Multiple Choice Examinations for Accurate Outcomes

MEASUREMENT RESEARCH ASSOCIATES

TEST INSIGHTS

October 2008

Greetings!

A multiple-choice certification exam may have acceptable reliability, but it's likely that it can be improved in the most important area - the precision of candidate ability estimates near the cut score. The article below describes how.

Ross Brown

Manager Computer Based Testing and Analysis

Targeting Multiple Choice Examinations for Accurate Outcomes

The purpose of certification examinations is to make accurate pass or fail decisions about candidates. The more information available about the candidates who are close to the cut score, the more accurate the pass/fail decisions are. The Rasch perspective suggests that including more items with difficulties close to the cut score yields the most information about those candidates close to the cut score. This is often called test targeting.

On most tests, the item difficulties range from very easy to very difficulty. For test targeting, the items that are too easy and too difficult are replaced with items that have difficulties close to the pass point. These items are those that are answered correctly by between 30% and 80% of candidates. The Wright Map in Figure 1 created by the Winsteps Program (Linacre, 1989), is ideal for tracking item difficulty distribution relative to the pass point. Both candidate measures and item difficulties are on the same scale, so the distribution of candidate measures can be compared to the distribution of item difficulties. In the Wright Map below, the items within the bracket on the right are the targeted items.

There are costs to targeting tests. Item writers often find it difficult to write items that perform at this level. As tests become more targeted, they appear more difficult to candidates. But common-item test equating allows more difficult test forms to be developed while maintaining the pass point as an absolute standard. The table shows two examples of tests that were made more targeted. The equating difficulty is the average item difficulty of the test expressed in scaled scores. When more items are in the target range of .30 to .80, the test becomes more difficult, but the difference in difficulty is accounted for in the analysis. The passing standard is maintained on the more difficult exam forms, but the percent correct necessary to pass decreases as the test becomes more difficult. Thus, the test is better psychometrically, and does not penalize the candidates.

Exam	Percent of exam items with difficulties from 0.30 to 0.80	Equating Difficulty	Passing Standard	Percent Correct Necessary to Pass
Exam 1, Year 1	26%	5.00	5.63	61%
Exam 1, Year 2	47%	5.74	5.63	48%
Exam 2, Year 1	49%	5.00	5.73	65%
Exam 2, Year 2	74%	5.76	5.73	49%

Figure 1 Wright Map of Candidates and Items

MEASURE | MEASURE

<more> -------------------- Candidate-+- ITEMS --------------------- <rare>

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Cut Score .### S| XXXXXXXXXXXXX |

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Less Able Candidates | XXXXXXXXXXXX

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<less> -------------------- Candidate-+- ITEMS ------------------<frequent>

Measurement Research Associates, Inc.

505 North Lake Shore Dr., Suite 1304

Chicago, IL 60611

Phone: (312) 822-9648 Fax: (312) 822-9650

Rasch-Related Resources: Rasch Measurement YouTube Channel
Rasch Measurement Transactions & Rasch Measurement research papers - free	An Introduction to the Rasch Model with Examples in R (eRm, etc.), Debelak, Strobl, Zeigenfuse	Rasch Measurement Theory Analysis in R, Wind, Hua	Applying the Rasch Model in Social Sciences Using R, Lamprianou	El modelo métrico de Rasch: Fundamentación, implementación e interpretación de la medida en ciencias sociales (Spanish Edition), Manuel González-Montesinos M.
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar	Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch	Rasch Models for Measurement, David Andrich	Constructing Measures, Mark Wilson	Best Test Design - free, Wright & Stone Rating Scale Analysis - free, Wright & Masters
Virtual Standard Setting: Setting Cut Scores, Charalambos Kollias	Diseño de Mejores Pruebas - free, Spanish Best Test Design	A Course in Rasch Measurement Theory, Andrich, Marais	Rasch Models in Health, Christensen, Kreiner, Mesba	Multivariate and Mixture Distribution Rasch Models, von Davier, Carstensen
Rasch Books and Publications: Winsteps and Facets
Applying the Rasch Model (Winsteps, Facets) 4th Ed., Bond, Yan, Heene	Advances in Rasch Analyses in the Human Sciences (Winsteps, Facets) 1st Ed., Boone, Staver	Advances in Applications of Rasch Measurement in Science Education, X. Liu & W. J. Boone	Rasch Analysis in the Human Sciences (Winsteps) Boone, Staver, Yale	Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes	Rasch Models for Solving Measurement Problems (Facets), George Engelhard, Jr. & Jue Wang	Statistical Analyses for Language Testers (Facets), Rita Green	Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments (Facets), George Engelhard, Jr. & Stefanie Wind	Aplicação do Modelo de Rasch (Português), de Bond, Trevor G., Fox, Christine M
Exploring Rating Scale Functioning for Survey Research (R, Facets), Stefanie Wind	Rasch Measurement: Applications, Khine	Winsteps Tutorials - free Facets Tutorials - free	Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre	Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan

Coming Rasch-related Events
Apr. 21 - 22, 2025, Mon.-Tue.	International Objective Measurement Workshop (IOMW) - Boulder, CO, www.iomw.net
Jan. 17 - Feb. 21, 2025, Fri.-Fri.	On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
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Oct. 3 - Nov. 7, 2025, Fri.-Fri.	On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com