MEASUREMENT RESEARCH ASSOCIATES
TEST INSIGHTS
July 2008
Greetings!
 

All the work of examination development funnels down to a single number, the cut score, a decision on who passes and who fails.  Each stage of exam construction contributes to the overall quality of this decision, but one of the most critical is establishing the criterion referenced standard.
 
Tara McNaughton
Manager, Test Development and Analysis
 
Criterion Referenced Standard Setting for Multiple Choice Examinations
The purpose of a criterion-referenced standard is to determine "how much is enough" to be considered capable to practice in the field.  According to the Standards for Educational and Psychological Testing, verifying the appropriateness of the cut score is critical for validity.  The validity of the pass or fail inference depends on whether the standard for passing makes a valid distinction between acceptable and unacceptable performance (p. 157).  The level of performance required for passing should depend on the knowledge and skills necessary for acceptable performance and should not be adjusted to regulate the number of candidates passing the test (p. 162).  These standards suggest that an absolute expectation for passing should be established prior to the examination based on the examination content.  When a criterion referenced standard is established, theoretically all candidates can pass the examination or all candidates can fail, depending on their ability levels.
 
For multiple choice examinations, popular methods of establishing a criterion referenced standard are modified Angoff approaches which require expert judgment concerning the difficulty of each item based on an assessment of the content.  Theoretically, each item is a criterion.  The question usually is 'what is the probability that the minimally capable candidate would answer the item correctly?'  Participants consider the difficulty of the content of the item, relevance, and frequency, and make the assessment.  The Angoff method is relatively convenient, has a long history of use, can be learned quickly by the subject matter experts, and has been subject to extensive research.
 
The criterion referenced pass point depends, in part, on the subjective judgments of experts.  Even with training, the outcomes of a standard setting exercise may be different when different methods, experts, or items are used in the process.  Thus, there is error associated with the criterion referenced standard setting process.  Measurement error can increase the probability that able candidates will fail or less able candidates will pass.  Therefore, adjusting for the error of measurement surrounding the pass point when setting the criterion standard, is legitimate and provides confidence that only candidates who should pass, will pass.  Once the criterion referenced standard is established, test equating methods allow it to be carried forward to subsequent tests, so that candidates are required to meet the same standard to pass regardless of when they take the examination.
 
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 Journal of Applied Measurement
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

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