CPM model put to the test in the WJ3COG test

 

Taub, G. E., & McGrew, K. S. (2014). The Woodcock–Johnson Tests of Cognitive Abilities III’s Cognitive Performance Model Empirical Support for Intermediate Factors Within CHC Theory. Journal of Psychoeducational Assessment, 32(3), 187-201.‏ http://www.iapsych.com/articles/taub2013.pdf

 CPM – cognitive performance model  was developed by Richard Woodcock, one of the developers of the Woodcock Johnson test in 1997.  This cognitive model assumes that intelligence is composed of three systems:

The thinking system (or thinking ability), which accounts for performance in tasks that require problem solving, thinking and complex executive functions.     The quality of a person's learning depends on his thinking ability.  The thinking ability includes the ability to abstract ideas, to conceptualize and to solve new problems, to process visual and auditory stimuli and to learn and to retrieve information from long term memory (in CHC terms, fluid ability, visual processing, auditory processing and long term storage and retrieval).  Limitations in one of these components affect the whole system, limit new learning and may require a change in instructions.

The cognitive efficiency system,  which allows for optimal use of the mental resources.  This is the ability to perform a task quickly and with attentional focus, and the ability to reach automatic performance.  This system reflects the relation between quality of performance and effort.  The cognitive efficiency system includes the ability to hold a few pieces of information in awareness and to perform manipulations on them and the ability to process information quickly (in CHC terms, short term memory and visuospatial ability).  Limitations in one of the component of the cognitive efficiency system affect the whole system and require adaptations in instruction methods and in testing.

Funds of acquired knowledge, which  include a person's crystallized knowledge, oral language,  math skills, reading and writing skills.  The quality of learning and performance are dependent on the relevant knowledge a person has.  Once a piece of information is learned, it can become a basis for new learning.  If a piece of information was not learned, it can become an impede future learning.  The funds of acquired knowledge are mutable:  instruction strategies and opportunities for enrichment can affect a person's level of performance in this system.

A child's functioning in every task is a result of the combined action of the three systems and facilitating/inhibiting factors:

Facilitators/inhibitors  affect performance for better or for worse.  Sometimes they are internal (health, emotional state, motivation), sometimes they are external (the presence of visual or auditory distractions, instruction method, the features of a specific tests the child takes).  Significant health issues that may interfere with school attendance may cause loss of learning opportunities.  Low motivation for learning or low interest in the contents learned may affect the extent of effort a person makes.  Cognitive styles or temperament, like impulsivity, may negatively affect the quality of a person's work.  Other factors, like emotional stability, organizing ability and concentration ability, may affect learning for better or for worse.

The CPM model was developed theoretically, not on the basis of empirical findings.  Despite the potential of this model, there is still little empirical research testing it.  One of the ways to conceptualize the model is through considering the CPM systems as intermediate abilities between g and the broad CHC abilities.  Keith (2005)   tested this using 22 tests from the Woodcock–Johnson test battery (WJ III).   He included Cognitive Efficiency and Thinking Ability as intermediate factors within the CHC model. The Verbal Ability factor was not included in this model because the CPM’s Verbal Ability factor and the second-order broad CHC factor, Crystallized Intelligence, are indistinguishable.   Keith found the categorization of Cognitive Efficiency and Thinking Ability as intermediate factors within the CHC theoretical model resulted in an improvement in the model’s fit, when compared with the CHC model without intermediate CPM factors.  Keith further noted that within this model, the Thinking Ability factor and g were indistinguishable, so he removed the Thinking Ability factor. In his simpler model, processing speed and short-term memory loaded on the intermediate Cognitive Efficiency factor (both the Verbal Ability and Thinking Ability factors were excluded from the analysis). Keith found that this parsimonious one-factor CPM model provided the best fit to the data.

Taub and McGrew (details and link above) also tested the CPM model using the WJ3COG standardization sample in the age range of 9-19.  Like Keith, they measured every broad CHC ability with three tests.  Thus they included the oral language test from the WJ3ACH as a measure of comprehension knowledge.  Taub and McGrew tested six versions of the CPM (and of the structure of intelligence):

Model 1: the traditional CHC-based measurement model:

click on image to enlarge

Model 2  (pictured below) is the traditional CPM model, which includes two Cognitive Performance factors as intermediate factors lying between the second- and third-order factors within the traditional CHC-based measurement model.  The Verbal Ability factor was eliminated from Figure 2 because it is an intermediate latent variable with only one indicator, Crystallized Intelligence (Gc). Thus, the variance accounted for by Verbal Ability in Model 2 is isomorphic with second-order broad CHC factor, Gc.

Model 3 (pictured below). This model is a replication of Keith’s one-factor CPM wherein the Thinking Ability and Verbal Ability factors are subsumed by the third-order general ability factor.

Model 4  ( pictured below) is similar to Model 2 with two differences. First, Model 4 includes the CPM factor, Verbal Ability. To provide adequate construct representation of Verbal Ability in Model 4, a second indicator was added, Auditory Processing (Ga). In this model, the variance accounted for by the broad CHC factor Ga was moved from the CPM Thinking Ability factor to the CPM Verbal Ability factor.   An inspection of the correlations between the WJ III tests measuring Ga abilities with Verbal and Thinking abilities revealed stronger relations with the former.

Model 5 (not pictured)  is a hybrid model. In this model, Ga shares variance with Thinking and Verbal ability. Thus, Model 5 incorporates the traditional placement of Ga as a component of Thinking Ability (Figure 2) and a component of Verbal ability as presented in Figure 4.

Model 6  (pictured below) is similar to Model 4; however, in Model 6 the intermediate CPM factor Thinking Ability is considered isomorphic with the third-order g factor.

The model that provided the best fit to the data was model 6.

The replication and finding of empirical support for the existence of intermediate factors within the CHC model suggests that researchers may need to account for the existence of intermediate factors within the CHC framework.  It is worth noting, that all models provided an improved fit over Model 1, the traditional CHC based theoretical measurement model. This indicates that the inclusion of intermediate factors within a traditional CHC theoretical model provides an improvement in overall model fit.

Does it mean that the CHC model should be changed?  We must remember that these are two studies done on a single intelligence test battery.  More evidence is needed from other test batteries.