The cognitive task analysis system
Abstract
The objective of this dissertation is to develop and validate a cognitive job and task analysis methodology that not only analyzes jobs and tasks, but also provides a mechanism for improving cognitive job and task performance. It provides a scientific methodology for matching what individuals wish to do in a job and the actual job content for job (re)design. Four phases were used to achieve this objective. The first phase developed a human-centered cognitive performance (HCCP) model based on human information processing. In order to quantitatively measure those aspects related to human performance in the HCCP model, a Cognitive Task Analysis Questionnaire (CTAQ) was developed by mapping from the HCCP model to provide an easy way to measure the dynamic job requirements on human cognitive abilities. In the second phase, data on cognitive-oriented job elements for 50 diversified cognitive jobs were collected using the CTAQ with 321 job incumbents (8 job incumbents per job, 79 job incumbents rated 2 jobs). Factor analysis based on these collected data resulted in the identification of 8 reasonably meaningful cognitive job dimensions, and cluster analysis resulted in 3 cognitive job families. A shorter form questionnaire (R-CTAQ) was developed based on the results from the factor analysis. The third phase was carried out to develop a match index, which quantitatively measures the degree of match between job requirements on cognitive attributes and humans' expectations from jobs of cognitive attributes. A match index for 4 cognitive jobs was derived for 32 (8 per job) job incumbents based on the CTAQ, and two other developed questionnaires, the Cognitive Task Preference Questionnaire (CTPQ) and the Modified Job Satisfaction Questionnaire (MJSQ). These four questionnaires (the CTAQ, the R-CTAQ, the CTPQ, and the MJSQ) demonstrated good construct validity, internal consistency and interrater reliability. In the fourth phase, a sensitivity analysis based on cognitive topography was conducted to provide suggestions for job diagnosis and (re)design.
Degree
Ph.D.
Advisors
Salvendy, Purdue University.
Subject Area
Industrial engineering|Business community
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