- SCHOLASTIC ACHIEVEMENT[/size]
The purpose of the first "intelligence" test, devised by Binet and Simon in 1905, was to assess elementary school children and identify those most likely to fail in the regular instructional program. These children would learn better with more specialized and individualized instruction suited to their belowaverage level of cognitive development. Since Binet's invention, there have been countless studies of the validity of mental tests for predicting children's scholastic performance. The Psychological Abstracts contains some 11,000 citations of studies on the relation of educational achievement to "IQ." If there is any unquestioned fact in applied psychometrics, it is that IQ tests have a high degree of predictive validity for many educational criteria, such as scores on scholastic achievement tests, school and college grades, retention in grade, school dropout, number of years of schooling, probability of entering college, and, after entering, probability of receiving a bachelor's degree. With equality of educational opportunity for the whole population increasing in recent decades, IQ has become even more predictive of educational outcomes than it was before the second half of this century.
The evidence for the validity of IQ in predicting educational variables is so vast and has been reviewed so extensively elsewhere [11] that there is no need to review it in detail here. The median validity coefficient of IQ for educational variables is about +.50, but the spread of validity coefficients is considerable, ranging from close to zero up to about .85. Most of the variability in validity coefficients is due to differences in the range of ability in the particular groups being tested. The less the variability of IQ in a given group, of course, the lower is the correlation ceiling that the IQ is likely to have with any criterion variable. Hence we see an appreciable decrease in the average validity coefficient for each rung of the educational ladder from kindergarten to graduate or professional school. Several rungs on the educational ladder are the main junctures for either dropping out or continuing in school.
The correlation of IQ with grades and achievement test scores is highest (.60 to .70) in elementary school, which includes virtually the entire child population and hence the full range of mental ability. At each more advanced educational level, more and more pupils from the lower end of the IQ distribution drop out, thereby restricting the range of IQs. The average validity coefficients decrease accordingly: high school (.50 to .60), college (.40 to .50), graduate school (.30 to .40). All of these are quite high, as validity coefficients go, but they permit far less than accurate prediction of a specific individual. (The standard error of estimate is quite large for validity coefficients in this range.)
Achievement test scores are more highly correlated with IQ than are grades, probably because grades are more influenced by the teacher's idiosyncratic perceptions of the child's apparent effort, personality, docility, deportment, gender, and the like. For example, teachers tend, on average, to give higher course grades to girls than to boys, although the boys and the girls scarcely differ on objective achievement tests.
Even when pupils' school grades are averaged over a number of years, so that different teachers' idiosyncratic variability in grading is averaged out, the correlation between grades and IQ is still far from perfect. A strong test of the overall relationship between IQ and course grades was provided in a study [12] based on longitudinal data from the Berkeley Growth Study. A general factor (and individual factor scores) was obtained from pupils' teacher-assigned grades in arithmetic, English, and social studies in grades one through ten. Also, the general factor (and factor scores) was extracted from the matrix of intercorrelations of Stanford-Binet IQs obtained from the same pupils on six occasions at one- to two-year intervals between grades one and ten. Thus we have here highly stable measures of both school grades and IQs, with each individual's year-toyear fluctuations in IQ and teachers' grades averaged out in the general factor scores for IQ and for grades.
The correlation between the general factor for grades and the general factor for Stanford-Binet IQ was +.69. Corrected for attenuation, the correlation is +.75. This corrected correlation indicates that pupils' grades in academic subjects, although highly correlated with IQ, also reflect consistent sources of variance that are independent of IQ. The difficulty in studying or measuring the sources of variance in school grades that are not accounted for by IQ is that they seem to consist of a great many small (but relatively stable) sources of variance (personality traits, idiosyncratic traits, study habits, interests, drive, etc.) rather than just a few large, measurable traits. This is probably why attempts to improve the prediction of scholastic performance by including personality scales along with cognitive tests have shown little promise of raising predictive validity appreciably above that attributable to IQ alone. In the noncognitive realm, no general factor, or any combination of broad group factors, has been discovered that appreciably increases the predictive validity over and above the prediction from IQ alone.
Although IQ tests are highly g loaded, they also measure other factors in addition to g, such as verbal and numerical abilities. It is of interest, then, to ask how much the reported validity of IQ for predicting scholastic success can be attributed to g and how much to other factors independent of g.
The psychometrician Robert L. Thorndike [13] analyzed data specifically to answer this question. He concluded that 80 to 90 percent of the predictable variance in scholastic performance is accounted for by g, with 10 to 20 percent of the variance predicted by other factors measured by the IQ or other tests. This should not be surprising, since highly g-loaded tests that contain no verbal or numerical factors or information content that resembles anything taught in school (the Raven matrices is a good example) are only slightly less correlated with various measures of scholastic performance than are the standard IQ and scholastic aptitude tests, which typically include some scholastic content. Clearly the predictive validity of g does not depend on the test's containing material that children are taught in school or at home. Pupils' grades in different academic subjects share a substantial common factor that is largely g. 14
The reason that IQ tests predict academic achievement better than any other measurable variable is that school learning itself is g-demanding. Pupils must continually grasp "relations and correlates" as new material is introduced, and they must transfer previously learned knowledge and skills to the learning of new material. These cognitive activities, when specifically investigated, are found to be heavily g loaded. It has also been found that various school subjects differ in their g demands. Mathematics and written composition, for example, are more g-demanding than arithmetic computation and spelling. Reading comprehension is so g loaded and also so crucial in the educational process as to warrant a separate section (p. 280 ).
The number of years of formal education that a person acquires is a relatively crude measure of educational attainment. It is quite highly correlated with IQ, typically between +.60 and +70. 15 This correlation cannot be explained as entirely the result of more education causing higher IQ. A substantial correlation exists even if the IQ is measured at an age when all persons have had the same number of years of schooling. Validity coefficients in the range of .40 to .50 are found between IQ at age seven and amount of education completed by age 40. [16]
(Arthur Jensen.
The g Factor. pp277-279.)
In other words, not everyone who has the same amount of schooling, and even attains the same grades, has learned the same amount; and the amount that a person both
has learned, and
will learn in the future, is most highly correlated with
g. Since the academic records of students applying for college are largely based on the whims of their teachers,
g remains a better predictor of college-level educational-attainment than pre-college academic record.