Measurement Research

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*Describe works/studies that are in favor of intelligence testing and those works/studies against intelligence testing.

In efforts to avoid complete reliance and subjectivity of teachers' evaluations, intelligence tests were developed. Among the most advanced studies in favor of intelligence tests are achievement and aptitude tests. Achievement tests are defined as an evaluation of accomplishment or the degree of learning. They are designed to measure what an individual has learned after being exposed to specific information (Cohen & Swerdlik, 2005, p. 20). Achievement tests may be standardized (a test based on a representative sample of test takers), nationally, regionally, and locally, or the tests may not be standardized. Examples of Achievement tests include batteries such as the California Achievement Test, and the Wechsler Individual Achievement Test.

An aptitude test is designed to measure both learning and an individual's potential for the purpose of making predictions about the test taker's future performance. Examples of the Aptitude test include the Scholastic Assessment Test (SAT), The Act Assessment (ACT), and the Graduate Record Examination (GRE). "The primary difference between achievement tests and aptitude tests is that aptitude tests tend to focus more on informal learning or life experiences, whereas achievement tests focus more that has occurred as a result of some structured input" (Cohen & Swerdlik, 2005, 311).

(1) Supporters of Intelligence Testing

Proponents of Intelligence Testing suggest that intelligence tests avoid too much dependency on subjects' ability. Numerous studies have been conducted by psychologists and educators in several domains including: (a) schools, (b) screening for mental retardation, (c) academic ability, (d) identify gifted students, and (e) evaluate educational programs.

In their study, Kodaganallur, Weitz, & Rosenthal (2005), examined two approaches based on theories of intelligence testing based on models of intelligence tutoring. They focused on two specific models-- the Model-tracing and Constraint-based intelligent tutoring models, and they make the claim that the models afford performance at high levels. Thus, while admitting that there ...