Course details
Course positioning statement
COMP 3270 develops AI fluency for the AI era by equipping learners with the knowledge, skills, judgment, and ethical awareness needed to use generative AI effectively, responsibly, and adaptively in learning, professional practice, and everyday life.
Use generative AI with purpose, evidence, and human responsibility
COMP 3270 develops the practical judgment needed to use generative AI effectively and responsibly across learning, research, communication, professional practice, workplaces, and everyday life. Through structured prompts, verification, ethical analysis, human-governed workflows, and discipline-specific applications, students examine both the opportunities and corresponding risks of AI while preserving human agency, capability, relationships, and accountability.
Course overview
This interdisciplinary course progresses from the foundations of generative AI to prompt design, ethical and responsible use, learning and research, professional and everyday applications, governance, emerging systems, and a discipline-specific capstone strategy.
- Seven thematic modules organize 20 instructional units.
- Six assignments develop prompting, ethical analysis, verification, workflow design, reflection, and integration skills.
- No final examination is required.
- No programming experience is assumed or required.
Course learning outcomes
By the end of COMP 327, you should be able to:
- Explain how generative AI produces outputs and distinguish fluency from understanding, accuracy, and suitability.
- Design purposeful prompts and staged workflows with explicit context, criteria, evidence, and verification requirements.
- Allocate appropriate roles to people and AI systems while preserving meaningful human authority and accountability.
- Evaluate fairness, accessibility, privacy, security, copyright, authorship, attribution, and academic-integrity implications.
- Identify hallucinations, omissions, reasoning defects, false precision, and uncertainty in AI-generated material.
- Verify claims, sources, citations, and evidence using authoritative and sufficiently independent information.
- Use AI to support learning, research, communication, professional practice, and everyday tasks without replacing essential human work.
- Design responsible AI workflows with information boundaries, review gates, escalation, incident response, fallback, and stop conditions.
- Assess discipline-specific and organizational AI uses through evidence, stakeholder impact, professional authority, and governance.
- Evaluate emerging systems and future scenarios using adaptive safeguards, revalidation, and human-centred judgment.
Course outline
COMP 3270 is organised into seven thematic modules across 13 weeks. The 20 chapters of the course textbook serve as readings within these modules.
See the module navigation for detailed unit breakdowns.
Assessments
Six assignments assess learning outcomes across the course. Assignment 1 begins in Module 1 and continues cumulatively through Module 6.
| Assessment | Weight | Primary module | Recommended submission |
|---|---|---|---|
| Assignment 1: AI Learning and Reflection Journal | 15% | Modules 1–6 | End of Module 6 (Week 11) |
| Assignment 2: Prompt Engineering Portfolio | 15% | Module 2 | End of Module 2 (Week 4) |
| Assignment 3: Responsible AI Case Analysis | 20% | Module 3 | End of Module 3 (Week 6) |
| Assignment 4: Applied AI Workflow Project | 20% | Module 5 | End of Module 5 (Week 10) |
| Assignment 5: Verification and Fact-Checking Assignment | 10% | Module 4 | End of Module 4 (Week 8) |
| Assignment 6: Capstone Project | 20% | Capstone Project | End of (Week 13) |
Always verify exact due dates and times in the learning management system.
Schedule and due dates
The course follows a 13‑week recommended schedule. Use the module navigation to access each module's study guide, which includes weekly session plans and specific activities.
- Weeks 1–2: Module 1 – Understanding Generative AI and the AI Paradox
- Weeks 3–4: Module 2 – Prompt Engineering and Human-AI Collaboration (Assignment 2 due end of Week 4)
- Weeks 5–6: Module 3 – Responsible and Ethical AI Use (Assignment 3 due end of Week 6)
- Weeks 7–8: Module 4 – AI for Learning, Research, and Knowledge Creation (Assignment 5 due end of Week 8)
- Weeks 9–10: Module 5 – AI for Professional Practice and Everyday Life (Assignment 4 due end of Week 10)
- Week 11: Module 6 – AI Governance, Society, and Future Directions (Assignment 1 due end of Week 11)
- Weeks 12–13: Capstone Project – (Assignment 6 due end of Week 13)
Student support
You are not alone in this course. Several support services are available to help you succeed.
Contact your instructor for academic and assignment-related questions.
Access research databases, citation help, and information literacy support.
Request accommodations for disabilities or temporary conditions.
Workshops, writing centres, and tutoring resources are available through the university.
Assistance with learning management system, AI tools, and other software.
Confidential counselling and wellness resources are available to all students.
For specific support, refer to the course syllabus or the university's student services portal.