Course content

This is a PhD-level course.

When implementing cyber- and information security theories and solutions to practical cases, possibly one main challenge is the knowledge shortage of and uncertainty associated with human factors. The practical needs to identify, measure, and possibly engineer them in a security research and development task become increasingly noticeable. This course selects and discusses some basic concepts and methods for understanding and engineering human factors through team-based learning, lectures, knowledge-sharing-oriented group discussion, and a term paper investigating the usefulness of human factor methods in the student's research work.

Learning outcome

Knowledge:

The students are expected to know some selected topics of

• Science, research methods, and qualitative approaches
• Human factor methods and ergonomics
• Security practice
• Technological laws and ethics

Skills:

The students are expected to know how to

• Identify human factors and their potential impact on a research plan
• Measure and manage human factors by established methods
• Apply the human factor methods in research work

General Competence:

The students are expected to be

• Ability to argue and discuss human factor methods with peer researchers
• Ability to critique human factor methods in a specific research work
• Ability to suggest and recommend human factor methods to a specific research work

Learning methods and activities

• Team-Based Learning (TBL) with lecture 2 sessions (2 x 90 minutes) (obligatory participation)
• 3 Guest lectures (obligatory participation)
  • Technological ethics
  • Security practice
  • socio-technical system methods
• 4 post-lecture short reports (2-4 pages each) relating to one's PhD work
• Course project which either identifies and maps human factor methods to your PhD research tasks, and arguing why they can be suitable, with evidence to prove / disprove their effectiveness; or innovates human factor method(s) to suit your PhD research task(s) with evaluation method and preferably evaluation result.
  • Course project plan presentation to define learning outcome, learning methods, and assessment methods
  • Course project mid-term assessment presentation
  • Course project final presentation and report for a summative assessment (10 - 20 pages, 10-50 references)

Compulsory assignments

• Mandatory assignment

Specific conditions

Required previous knowledge

This is a PhD-level course and the students need to be already enrolled in a NTNU PhD program.

Course materials

List under continuous updating:

• Hugh Coolican. Research Methods and Statistics in Psychology (7th Edition). Routledge, 2019.
• Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins. (2nd Edition) Human Factors Methods: A Practical Guide for Engineering and Design. July 26, 2013 by CRC Press, ISBN 9781409457541

Credit reductions