Uncovering the root cause of ethnic difference in ability testing:differential test functioning, test familiarity and trait optimism as explanations of ethnic group differences

The present research represents a coherent approach to understanding the root causes of ethnic group differences in ability test performance. Two studies were conducted, each of which was designed to address a key knowledge gap in the ethnic bias literature. In Study 1, both the LR Method of Differential Item Functioning (DIF) detection and Mixture Latent Variable Modelling were used to investigate the degree to which Differential Test Functioning (DTF) could explain ethnic group test performance differences in a large, previously unpublished dataset. Though mean test score differences were observed between a number of ethnic groups, neither technique was able to identify ethnic DTF. This calls into question the practical application of DTF to understanding these group differences. Study 2 investigated whether a number of non-cognitive factors might explain ethnic group test performance differences on a variety of ability tests. Two factors – test familiarity and trait optimism – were able to explain a large proportion of ethnic group test score differences. Furthermore, test familiarity was found to mediate the relationship between socio-economic factors – particularly participant educational level and familial social status – and test performance, suggesting that test familiarity develops over time through the mechanism of exposure to ability testing in other contexts. These findings represent a substantial contribution to the field’s understanding of two key issues surrounding ethnic test performance differences. The author calls for a new line of research into these performance facilitating and debilitating factors, before recommendations are offered for practitioners to ensure fairer deployment of ability testing in high-stakes selection processes.

Differential impact of posterior lesions in the left and right hemisphere on visual category learning and generalization to contrast reversal

Hemispheric differences in the learning and generalization of pattern categories were explored in two experiments involving sixteen patients with unilateral posterior, cerebral lesions in the left (LH) or right (RH) hemisphere. In each experiment participants were first trained to criterion in a supervised learning paradigm to categorize a set of patterns that either consisted of simple geometric forms (Experiment 1) or unfamiliar grey-level images (Experiment 2). They were then tested for their ability to generalize acquired categorical knowledge to contrast-reversed versions of the learning patterns. The results showed that RH lesions impeded category learning of unfamiliar grey-level images more severely than LH lesions, whereas this relationship appeared reversed for categories defined by simple geometric forms. With regard to generalization to contrast reversal, categorization performance of LH and RH patients was unaffected in the case of simple geometric forms. However, generalization to of contrast-reversed grey-level images distinctly deteriorated for patients with LH lesions relative to those with RH lesions, with the latter (but not the former) being consistently unable to identify the pattern manipulation. These findings suggest a differential use of contrast information in the representation of pattern categories in the two hemispheres. Such specialization appears in line with previous distinctions between a predominantly lefthemispheric, abstract-analytical and a righthemispheric, specific-holistic representation of object categories, and their prediction of a mandatory representation of contrast polarity in the RH. Some implications for the well-established dissociation of visual disorders for the recognition of faces and letters are discussed.

Ability assessment and job structure measures in occupational mobility

Recent and potential changes in technology have resulted in the anticipation of increases in the frequency of job changes. This has led manpower policy makers to investigate the feasibility of incorporating the employment skills of job groups in the general prediction of future job learning and performance with a view to the establishment of "job families" within which transfer might be considered reciprocally high. A structured job analysis instrument (the Position Analysis Questionnaire) is evaluated in terms of two distinct sets of scores; job dimensions and synthetically established attribute/trait profiles. Studies demonstrate that estimates of a job's structure/dimensions and requisite human attributes can be reliably established. Three alternative techniques of statistically assembling profiles of the requisite human attributes for jobs are found to have differential levels of reliability and differential degrees of validity in their estimation of the "actual" ability requirements of jobs. The utility of these two sets of job descriptors to serve as representations of the cognitive structure similarity of job groups is investigated in a study which simulates a job transfer situation. The central role of the index of similarity used to assess the relationship between "target" and "present" job is demonstrated. The relative extents to which job structure similarity and job attribute similariity are associated with positive transfer are investigated. The studies demonstrate that the dimensions of jobs, and more fruitfully their requisite human attributes can serve as bases to predict job transfer learning and performance. The nature of the index of similarity used to optimally formulate predictions of transfer is such that networks of jobs might be establishable to which current job incumbents could be expected to transfer positively. The derivation of "job families" with anticipated reciprocal transfer consequences is considered to be less appropriate.