Most organizations need information to assist them in selecting people for jobs. A job candidate’s thinking capability is often the key to success in the current fast paced, hi-tech environment in which academic qualifications and even work experience may not be a good predictor.

So how can organizations measure thinking ability of potential candidates? The following are some of the traditional and newer psychometric methodologies used to measure thinking ability:

• IQ tests (e.g. WAIS, GSAT, CRB, Watson-Glaser, Ravens…)
• Structured interviews (CPA, Iris, Potentia, CNT)
• Assessment centers (as designed for specific work environments)
• Simulation exercises (CPP, LOI)
• Questionnaires (part of personality assessments)

Traditional tests of cognitive capability—IQ tests in particular—measure thinking by exposing the subject to highly structured content which has to be manipulated via logical-analytical and memory processes in a linear causal manner. IQ tests have however been found to be culturally biased in that they mostly represent decontextualised and disembedded information.

IQ test results also primarily reflect the person’s current skills in particular content areas and is heavily influenced by previous learning and exposure. It provides little indication of future learning potential or natural stylistic preference. It thus requires of the person to solve well-structured problems by applying logical-analytical thinking in a linear manner. It also measures the person’s already developed ability to deal with specific item content. “Ability” here refers to already developed skills—as a function of previous exposure, or specific talent.

Other, more recent, methodologies for assessing thinking skills include computer based simulations such as the Cognitive Possesses Profiles or CPP. These newer simulation based assessments enable assessors to accurately identify thinking skill levels in unfamiliar, unstructured problem solving environments. They can also measure learning potential—or degree to which the person is likely to benefit from learning experiences and can accurately predict performance in the educational and work environments.

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