Cyber Aptitude and the Science of Intellectual Assessment

Abstract 

The prediction of individual differences in skilled performance has been a source of substantial theoretical and empirical research since the turn of the 20th Century. In subsequent decades, significant refinements and advances in testing technology were made, including developments in the statistical evaluation of individual differences data, and, more recently, progress in understanding the structure and function of cognitive abilities. There is now a mission-critical need to build a high-caliber cyber talent pool. The use of the latest advancements in the behavioral and cognitive science of human capabilities assessment (i.e., individual differences research, cognitive task analysis, and neural markers) can dramatically accelerate and optimize the selection and development of such a workforce. The addition of cognitive aptitude batteries based on individual difference measures can improve prediction of training success in complex skills, such as language learning, mathematics, analytic thinking, and problem solving. We are using an aptitude-based approach to characterize cognitive strengths and weaknesses in order to improve the process of selecting and placing personnel in computer science and cybersecurity positions and/or programs of study. Scientists at the University of Maryland Center for Advanced Study of Language (CASL) have been developing a Cyber Aptitude Assessment, comprised of individual difference measures (e.g., cognitive skills and abilities, personality traits) that are proven to predict success in cyber-related jobs. This test should be able to predict: • How well and rapidly one can learn cybersecurity techniques. • How well one will perform in the face of an evolving cyber landscape. • How flexible one is when it comes to changing the focal area of one’s work. Good performance on complicated skills requires a person to have general and specific abilities, followed by effective training and opportunities for practice. We intend to assess applicants’ general fluid intelligence, specific cognitive skills and abilities, problem-solving styles, and stable personality dimensions. This approach mirrors CASL’s approach to assessing aptitude for basic language training, which includes measures of general mental ability, specific language aptitude, and personality traits. This talk will address what is new and innovative about our approach to the assessment of human capabilities and how we plan on validating our cyber assessment for predictive utility.