Finding problems in a child’s mental skills, as well as information perception and processing skills, usually requires the work of a specialist, such as a clinical psychologist, with knowledge of cognitive learning skills. The price, availability, and logistics of these services are often barriers that limit the number of people who have access to this testing and this form of information. There are many different batteries of cognitive tests; some of them are designed to calculate IQ scores, others to determine the quality of specific levels of cognitive skills. In the latter category, Woodcock-Johnson III Cognitive Tests are considered to be particularly authoritative. This battery of tests, along with the complementary Woodcock-Johnson III Achievement Tests, are the varieties of IQ tests.
The test analyzes a person from a multitude of angles, which allows acquiring a comprehensive understanding of one’s psychological and cognitive capabilities. The test consists of numerical reasoning, concept formation, analysis synthesis, block rotation, spatial relations, and pattern recognition. It also tests visual matching, decision speed, cross out, incomplete words, academic knowledge, and memory span (Cucina and Howardson 1003).
Woodcock is considered to be the progenitor of the cross-battery approach, and he demonstrated with the help of confirmatory factor analysis the possibility of understanding subtest assessments of different psychometric methods within the framework of a single classification of cognitive abilities. Woodcock showed which factors in the Cattell-Horn Intelligence Theory different test batteries measure and which not. He suggested that it is necessary to use additional subtests of different psychometric methods in order to cover as widely as possible the measurement of all factors of intellectual abilities.
The cross-battery (CB) approach is based on the application of theories of fluid and crystallized intelligence, Cattell-Horn Carroll and factor analysis to the results of parallel testing of the same sample of subjects using different test batteries. The cross-battery approach is assessed as a significant breakthrough in the field of psychology of cognitive abilities and psychometry. This approach is based on strong theory, a rigorous psychometric assessment system, and a proven mathematical-statistical procedure for factor analysis of results. This makes the valid and scientifically sound use of its results.
There are three major factors of measurements, such as comprehension knowledge (Gc), processing speed (Gs), and fluid reasoning (Gf) (Strickland et al. 691). These elements allow testers to acquire a full picture of the mental capability of a person.
The development of neuropsychological diagnostics in general and children’s, in particular, is carried out mainly in two main directions. The applications are in the field of traditional clinical psychodiagnostics and the area of psychodiagnostics, built on psychometric principles. It is stated that both orthogonal broad abilities and g coefficient are needed to describe the variations in mental capabilities (Cucina and Howardson 1001). It means that the Woodcock-Johnson test can help to fully determine one’s psychological and neuropsychological capacities. Historically developed in some isolation from each other today, these two areas have become mutually penetrating and mutually reinforcing, and the practice of their joint use allows reaching a fundamentally new level of neuropsychological diagnosis.
Modern methodological problems of pediatric neuropsychology are reduced not only to the search for a productive integration of qualitative and psychometric approaches in psychodiagnostics. They are also associated with the necessity and difficulties of simultaneously taking into account the individual and age-related characteristics of neuropsychological connections, as well as with the challenge of correlating higher mental functions with different brain mechanisms.
Therefore, the solution of the problem of searching for statistically substantiated methods of evidence of individual psychological characteristics of a separately studied personality, in contrast to other individuals, and, especially, from representatives of the normative group, remains an urgent problem of psychodiagnostics. Thus, the implementation of the given test can be useful in predicting a child’s neurodevelopment.
Another important element of the test is its precision of measurement expressed in the results. It is stated that applying confirmatory factor analysis (CFA) to the test shows that Gs is the most critical in the process (Strickland et al. 689). It means that the given test is most suited to measure one’s speed of reasoning due to the time limitation factors. Other components, such as fluidity and Gc, are not fully elaborated due to the lack of uniqueness values, which would signify that the factors are demonstrating a subject’s mental framework.
The study of mental activity in psychophysiology is based on two relatively independent approaches. The first is based on the registration of physiological indicators in the course of mental action – it is aimed at identifying the dynamics of physiological indicators in the process of solving problems of various types. By varying the content of tasks and analyzing the accompanying changes in physiological indicators, researchers obtain physiological correlates of the activity performed.
The second approach proceeds from the fact that there are methods of cognitive activity inherent in a person, which are naturally reflected in physiological indicators. As a result, they acquire stable individual characteristics. According to this logic, the main thing is to find those indicators that are statistically reliably associated with the success of the cognitive activity, for example, with an intelligence coefficient, and physiological indicators, in this case, are obtained independently of psychometric ones.
A certain part of individual differences in the success of performing intelligence tests is explained by how quickly an individual can process information, regardless of acquired knowledge and skills. Thus, the concept of mental speed, or speed of mental actions, takes on the role of a factor explaining the origin of individual differences in cognitive activity and intelligence. It has been repeatedly shown that IQ is related to the reaction time taken in different evaluation options, negative correlation (Strickland et al. 694).
Along with this, in psychophysiology, there is a special direction in the chronometry of information processing processes, in which one of the main indicators is the latency of the components of the intellect, interpreted as markers of the execution time of individual cognitive operations. It is logical that there are a number of elements of the relationship between intelligence indicators.
In conclusion, it important to understand that the Woodcock-Johnson test allows people to measure their cognitive capabilities in three segments, such as fluid reasoning, comprehension, and speed. These factors play an essential role in assessing one’s mental capacity and intelligence. The disturbance of development can be used in neuropsychological diagnostics in order to take preliminary actions. The review of the literature reveals that the Woodcock-Johnson test is an outstanding tool for measuring a person’s Gs factor, which focuses on assessing the speed of reasoning. It is important to note that Gs and speed of thinking are not necessarily equal because reasoning involves a more complex and structured process of deliberate problem-solving.
References
Cucina, Jeffrey. M., and Garett. N. Howardson. “Woodcock-Johnson-III, Kaufman Adolescent and Adult Intelligence Test (KAIT), Kaufman Assessment Battery for Children (KABC), and Differential Ability Scales (DAS) support Carroll but not Cattell-Horn.” Psychological Assessment, vol. 29, no. 8, 2017, pp. 1001-1015.
Strickland, Tracy, et al. “Structure of the Woodcock–Johnson III cognitive tests in a referral sample of elementary school students.” Psychological Assessment, vol. 27, no. 2, 2015, pp. 689-697.