Learning Cyber: An Analysis of Strategies, Motivations, Personality, and Cognitive Characteristics

Abstract

This research examined the learning strategies, motivations, personality traits, and cognitive abilities of Army Soldiers who attended the U.S. Army Cyber School. The research aimed to identify psychological characteristics of well-performing students in cyber education. The Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991) was administered to assess each students learning strategies and motivations. These results were joined with other student assessment results collected during student in-processing, including the NEO Personality Inventory-3 (McCrae and Costa, 2010) and the 10-test Multidimensional Aptitude Battery (Jackson, 1998). The 19-week Cyber Phase I course test scores were obtained, averaged, and used as the performance criterion. Cyber students overall reported high motivation for cyber learning and a high regard for study habits and learning skills. Student personality results suggest a Cyber population high in Conscientiousness and Openness to Experience, while low in Neuroticism. The MAB-II cognitive test results suggest that cognitive ability is the strongest predictor of cyber education performance. Findings could be leveraged toward new mentoring and developmental counseling approaches. The quantification of the Cyber populations skills and behaviors could inform future work developing cyber fit algorithms used by recruiters and Army talent managers.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2019
Accession Number
AD1210091

Entities

People

  • Camilla Knott
  • David Lawburgh
  • Elizabeth R. Uhl
  • Matthew Deloia
  • Thomas R. Graves

Organizations

  • United States Army Research Institute of Environmental Medicine

Tags

Communities of Interest

  • Cyber
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computer Programming
  • Computer Science
  • Computers
  • Cybersecurity
  • Data Science
  • Data Sets
  • Education
  • Human Behavior
  • Information Processing
  • Information Science
  • Military Research
  • Motivation
  • Network Science
  • Performance Tests
  • Psychology
  • Reliability
  • Social Sciences
  • Students
  • Surveys
  • Training

Fields of Study

  • Education

Readers

  • Cybersecurity.
  • Instructional Design and Training Evaluation.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

  • Cyber