By Kim Glenchur
Having a child undergo assessment for learning disabilities is a complex and confusing process for most parents. Many parents want clear information about psychoeducational testing - what the tests involve and how to understand and interpret the resulting test scores. Because these tests will be used to determine the nature and severity of any underlying disorders, it's important to understand what the test results mean.
In her book, Learning Disabilities from a Parent's Perspective, author and parent Kim Glenchur does an excellent job of "demystifying" the process of psychoeducational testing. Following is an excerpt from her book which clearly explains how to understand and interpret the scores that result from psychoeducational testing.
Most psychological tests are formal statistical measures of behavioral responses to test items that, over time and professional experience, have been accepted as appropriate measures of abilities and achievements. The basic issue of psychological testing is whether the test truly fulfills its claims. In order to understand psychological testing, some underlying statistical concepts must be reviewed.
Representative norm group
Like a control group in any scientific experiment, a representative norm group establishes the range of normal performance on a test. The individuals must be chosen at random from a larger population, and be truly representative of individuals with certain characteristics of age, intelligence, and so on. For example, if the representative norm only consisted of male students, then the test results comparing a female student's performance against this norm may be inaccurate. The accuracy of the performance range is also dependent on the size of the representative sample: The larger the norm group, the more accurately defined is the normal range.
With respect to psychological tests, revised tests anticipate IQ gains of the general American population each generation. Thus, a child could score lower on a restandardized test than on the version just retired.
At the statistical scoring extremes of a population, a few points of change can greatly affect school placement decisions, whereas a few points of change around the population average can be dismissed as random error.
Test realiability is about scoring accuracy. A reliable test reproduces the same results upon a second test administration, assuming no prior learning or actions that would alter the trait being tested. A reliable test is also longer rather than shorter; a large number of test items can reduce test problems such as a child's confusion or attentional lapse with a particular question.
Standard error is another indicator of reliability. Test measurements of ability, achievement, and so on, are not single numerical scores but are really a range of possible outcomes as indicated by that test's standard error of measurement. For example, a test score of 100 with a standard error of 5 suggests that the real score lies in the range of 95-105. A less reliable test could have a standard error of 10, meaning that the real score lies between 90-110.
Test validity is about effectively measuring the trait. According to David Wodrich, Clinical Director of Child Psychology at The Phoenix Children's Hospital in Arizona, a test title is frequently a "poor guide" on what that test or subtest measures.1 Content validity indicates whether the test contains items that truly measure a certain trait. For example, an intelligence test limited only to math items would really be a test of quantitative ability. Special attention should be given to standardized national achievement tests, which rarely match local curricula exactly. Construct validity denotes how well a test captures characteristics of a trait, as predicted by a particular theory. Predictive validity is a measurement of a test's usefulness to predict outcomes. For example, IQ tests began as an effort to identify people who would do well in college. Concurrent validity means that a test correlates well with other similar measures of the same trait.
Test uniformity and objectivity
Test uniformity and objectivity is the main difference between a formal standardized test and an informal test, such as asking a child the color of his shirt that day. Uniformity refers to one test being administered to a great number of people, and the test results can be used for later statistical analysis. Objectivity refers to unbiased scoring of test answers, a quality desirable, for example, in a baseball umpire calling balls and strikes.
Quantifiable scores support interpretation of the test results. Most psychological tests provide numerical scores, which allow statistical comparisons. Examples of tests without numerical scores are the Rorschach inkblot, projective drawings, and incomplete sentence tests.
Age and grade equivalent scores indicate the level of performance of the child. Thus, "10-3" represents the typical performance of a child of age 10 years and 3 months. Similarly, a fourth-grade, third-month performance level would be represented by "4-3." These are rough guides, however, because actual skills depend on the actual material presented in the classroom. A more reliable interpretation of a test result is the statistical difference of the individual's score from the norm population's average performance.
Reprinted with permission from Kim Glenchur. All rights reserved.
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