Syllabus
Table of contents
Course Description
BIT/CS/PSCI 4164 Future of Security: Integrative Solutions to Complex Security Systems is the capstone course for the Integrated Security Pathways minor. It is a cross-disciplinary capstone course spanning multiple colleges and departments incorporating learning objectives from Pathways Learning Core Outcomes/Integrative Outcomes, Quantitative and Computational Thinking, Reasoning within the Social Sciences, and Intercultural and Global Awareness.
This course focuses on identifying and analyzing real-world security challenges that affect individuals, organizations, and nations. Students will develop skills in crisis communication, ethical decision-making, and structured problem-solving to scope issues, evaluate options, and plan responses before, during, and after conflicts, disasters, and attacks. The course emphasizes experiential learning, including participation in a team-based simulation that models cascading security and disaster events.
Having successfully completed this course, the student will be able to:
- Demonstrate and apply advanced problem-solving methodologies to address complex real-world security problems.
- Evaluate, compare and determine courses of action supported by data analysis to achieve equitable, effective, and efficient integrated security outcomes.
- Formulate and demonstrate execute communication strategies to facilitate effective decision-making across integrated security domains.
- Collaborate effectively in transdisciplinary teams to determine scope, assess options, and develop plans of action to address integrated security challenges in an ethical manner.
Prerequisites: BIT/CS/PSCI 2164 - Foundations of Contemporary Security Environments
Course Outline
- Integrated analysis of complex security scenarios 20%
- Advanced research topics in integrated security 20%
- Data analysis methodologies for decision making for complex security challenges 20%
- Transdisciplinary communication methods and strategies in an integrated security environment 20%
- Teams work in a simulated security scenario 20%
Grading
Grades are assigned on the following point basis:
| A 93.0% – | B 83.0-86.9% | C 73.0-76.9% | D 63.0-66.9% |
| A- 90.0-92.9% | B- 80.0-82.9% | C- 70.0-72.9% | D- 60.0-62.9% |
| B+ 87.0-89.9% | C+ 77.0-79.9% | D+ 67.0-69.9% | F below 60.0% |
If you have questions about a grade, you must discuss it with me within one week of when the grade was posted on Canvas. Note that grades are not rounded.
Reading & Annotation Assignments – 20%
Written analysis in this course is conducted through annotation using Hypothesis. Annotations are designed to support continuous, low-stakes analytical engagement with course materials and peer perspectives. Most weeks include one required reading for annotation.
Students are expected to contribute at least 5 substantive annotations per assigned reading AND at least 2 thoughtful replies to peer annotations. Substantive annotations should provide meaningful analysis or critique, explicitly connecting to human security dimensions, while replies should engage constructively with peers’ insights, advancing the discussion.
Late annotations will NOT be accepted and will receive NO credit; students must ensure all annotations are completed by the specified deadline.
In-Class Simulation – 30%
Students participate in an evolving crisis simulation that unfolds across multiple phases during the semester.
Team Capstone Project – 40%
Students work to design, facilitate, and evaluate an original security simulation involving cascading crisis events.
Participation – 10%
Participation is assessed throughout the course and is embedded across all components, including in-class discussions, case studies, simulation engagement, Hypothesis peer replies, and attendance.
Attendance is required at all scheduled class meetings. Active participation in discussions and activities is crucial for success in this course, especially given the emphasis on collaborative learning and the simulation component. Attendance will be occasionally taken to ensure consistent presence. Consistent attendance and engagement will significantly impact your understanding of complex topics and your ability to contribute effectively to group assignments.
If you must miss a class, please notify the instructors in advance when possible. It is your responsibility to obtain any missed notes or announcements from classmates.
Use of AI
Artificial Intelligence (AI) can be useful for revising and enhancing your work. However, relying on AI to write for you removes the opportunity to engage in critical thinking and express your ideas in your own way. Additionally, AI can sometimes produce inaccuracies, such as generating fake content or repeating ideas in different phrasing, which may compromise the quality of your work. AI-generated content can also sometimes appear to lack depth which may lead to written work that feels less original or insightful.
Below are some guidelines for using AI for this course.
- AI is permitted for enhancing clarity, coherence, grammar in writing, and for brainstorming, exploring new concepts.
- Generating entire sections or conducting primary research using AI is prohibited.
- Any use of AI in written work must be properly acknowledged.
For team projects, the use of AI is subject to the written agreement of all team members to ensure alignment and transparency. Each team member must review AI-refined work to confirm it aligns with their original contributions and understanding. Any discrepancies or AI-introduced changes must be discussed and approved by the entire team.
If you choose to use AI as part of your writing process, you must cite it in your Reference list (for example, the conversation history). If you submit a file, you must also include the following phrase with your signed Honor Code pledge on the last page of the submitted document:
We/I have used artificial intelligence tools as part of my writing process, but our/my submission only includes our/own ideas, opinions, and arguments.
The teaching staff will monitor for potential plagiarism and the use of AI in all submitted work. Plagiarism detection tools will be employed. Additionally, any excessive or inappropriate use of AI that deviates from the guidelines will be flagged. It is important to remember that while AI may assist in refining your work, it should not replace the intellectual effort and critical thinking required in producing assignments. Violations of these guidelines could lead to academic penalties.
Honor Code
The Undergraduate Honor Code pledge that each member of the university community agrees to abide by states:
As a Hokie, I will conduct myself with honor and integrity at all times. I will not lie, cheat, or steal, nor will I accept the actions of those who do.
Students enrolled in this course are responsible for abiding by the Honor Code. A student who has doubts about how the Honor Code applies to any assignment is responsible for obtaining specific guidance from the course instructor before submitting the assignment for evaluation. Ignorance of the rules does not exclude any member of the University community from the requirements and expectations of the Honor Code.
For additional information about the Honor Code, please visit https://honorsystem.vt.edu/.