The Journey to Knowledge

There are three stages of development through which a new idea is brought into use. This is the pattern by which the Rasch model has been developed into a useful tool for the construction of tests.

Stage 1: Try It Out

The first stage was the application of the idea that Rasch encapsulated in his model. His neat and clean probabilistic model, which strongly represents the essence of what Item Response Theory is intended to do, was an essential measurement insight and a decisive departure from traditional testing. Application of the Model generally produced reasonable results. But there were some problematic ones. In Portland,we could not link tests a full grade level apart in difficulty in a way which satisfied us.

Stage 2: Learn from Experience

Flowchart of operational item bank
In the second stage we paid attention to the conditions under which the model functions successfully. We found that with our Portland data it took 300 cases and 40 items to stabilize item calibrations. We ran into trouble when we tried to link tests more than three tenths of a logit apart in difficulty. However, we still believed that fit statistics and individual standard errors were all we needed to know. This was a hangover from years of statistical training, understandable but inadequate for the task ahead. We experienced a period of maturing, and of finding out through trial and error that the Rasch model requires test developers to think clearly and comprehensively.

Stage 3: Transform your Mind

The third phase emerges as a discontinuity. It arises from the ashes of conventional statistical methodology like a Phoenix - a new way of incorporating old ideas into unforeseen contexts. This third phase requires thought processes compatible with the nature of the model as probably measuring a variable.

Probabilistic thinking must replace deterministic ideas in the intrinsic beauty of the relationship expressed by the theory. Deterministic thinking vilifies randomness as destructive, though inevitable. It follows that randomness must be minimized. Probabilistic thinking, however, perceives randomness to be constructive. Randomness is like wind, fire and water: too much or too little are bad. A healthy variable requires a harmonious amount. Deterministic thinking looks for yes/no directives based on significance tests. Probabilistic thinking looks for reasonable patterns and useful compromises.

The power and the sensitivity of the Rasch model is apparent when judging an item's compatibility with a variable and the relationship of each item to the others in the test instrument. When linking tests, selection of meaningful linking items and their calibrations requires good judgement, not just statistical know-how. This same judgmental procedure is necessary to build an item bank.

Rasch practitioners, I exhort you! Abandon the hopeless quest for deterministic perfection. Decide instead to construct meaning and utility. That construction is often found to have greater beauty and to yield more insight than perfection could have ever offered. "To travel hopefully is a better thing than to arrive" (Robert Louis Stevenson, Virginibus Puerisque: El Dorado.)

George Ingebo
3708 NE 136 Place
Portland OR 97230

The journey to knowledge. Ingebo G. … Rasch Measurement Transactions, 1996, 10:2 p. 508

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

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