Turbulence in Testing

Let's start with learning, because it is the goal of learning that we test. At this point an analogy from Engineering that uses flow of a liquid will help us get our heads wrapped around the concept. We can blaze a trail from liquid flow through learning flow to testing with a minimum of turbulence.

The flow of liquid in a flume or stream can be a smooth, even motion with each teaspoon fully maintaining its position with all the others at a suitably slow pace. However, as the speed of the flow is increased the liquid will develop eddies along the edges and with increased pressure these will become severe turbulence, constituting a chaotic state of affairs that defies description. How about the stream of mental activity we know as learning?

To keep it simple, as well as with the realization that we are in the area of mythology, let's consider an elementary school student learning the basic rules of reading, writing, and arithmetic. We have to start with a student whose background experiences are unique. The student's active knowledge of people, places, events, and emotions is idiosyncratic. The perception of any stimulus situation by a student is alike, only in general, to that of other learners, but it controls the beginning of learning. Backed up by the apperceptive mass and the mental set of the student within the present situation, new learning is occurring.

In the course of living, a student is always learning. Perhaps what is being learned is something we wish the student was not learning, dislike for school or that math is too hard to try, for example. The learning flow we hope for is a smooth assimilation of learning goals. But with increased pressure of overwhelming complexity we can imagine this continuous progression becoming turbulent. We can imagine the stimulus situation in a school lesson requiring more than the previously learned content to provide the ingredients for reaching the learning goal at which the lesson of the day is aimed. Then the individualistic resources, unique for that student, are brought to the task and may not coincide with the assignment. It can be said that speed and or unfamiliar complexity cause turbulence in the flow of learning. How does that cue us into a test taking problem?

Leaving the realm of mythology, we have evidence that a testing situation with too much pressure and complexity, often ambiguity as well, decreases the validity of the test performance by a student. But we must again go to the philosophical question, why, and resort to explanation rather than to science for rationalization. Taking an achievement test is a learning activity. As a student perceives a question, learning about the task involved occurs simultaneously along with at least two, possibly dichotomous, continua. First, the question is seen as one that can be answered in a certain way or, although familiar to the student, is beyond the student's present ability to solve. Second, the student sees the question as consistent with past class room lessons or foreign to past school experiences. Students, aware of their own inability to understand what is asked of them by an item, can often sniff out questions that do not belong in a test of what they have been exposed to in school. Can these items cause eddies in the stream of testing? Perhaps.

As the pressure of item failures increases for a student taking a test, especially if the test seems unfair, it can be postulated that turbulence in the learning-testing activity will result from inappropriate items that are either too difficult for a student to attempt, or inconsistent with classroom experiences. If this is reasonable, how much turbulence is acceptable in achievement testing?

The engineering approach is to do what can be done, such as smooth the sides of the conduit and control the pressure of flow. We have that option in achievement testing, starting with the use of the Rasch model. As a result of the application of Rasch measurement,calibrated item banks in reading, language usage, and arithmetic are available to solve one of the pressure problems, namely test appropriateness. By constructing tests of known difficulty using calibrated items, it is practical to develop a district testing program that will make it possible to assign students tests that both match and measure a student's level of performance. It follows that, with the curriculum people alert to the content of the items and watching for mismatches with their curriculum, test developers can decrease undesirable turbulence in testing.

Turbulence in Testing, G Ingebo … Rasch Measurement Transactions, 1990, 4:1 p.92

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
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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
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Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan

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