Table of Contents
- 1. Purpose of This Lesson
- 2. Connection to the Capstone Project
- 3. Learning Outcomes
- 4. Key Concepts
- 5. Retrieval Practice
- 6. Worked Synthetic Example
- 7. Guided Activity
- 8. Student Production Activity
- 9. Evidence-Retention Box
- 10. Common Problems & Corrective Actions
- 11. Responsible-Use Boundaries
- 12. Participation Pathways
- 13. Accessibility Guidance
- 14. Self-Check Questions
- 15. Completion Checklist
- 16. Section Summaries
1. Purpose of This Lesson
This lesson helps you select and apply relevant frameworks from the COMP 3270 course to your Capstone Project. Rather than mechanically applying every framework, you will learn to match frameworks to the specific questions your project raises, and to build an integrated analysis that synthesises insights across multiple frameworks.
The course offers a rich set of frameworks (AI Paradox, ORBIT, PCAFE-V, SCOPE, PARTNER, FAIRER, PROTECT, CREATE, TRACE, CLAIM, LEARN, RIGOUR, VOICE, WORKS, LIFE, DOMAIN, GOVERN, FUTURES, HUMAN). You will choose a primary framework that addresses your central concern, and supporting frameworks that cover specific aspects (e.g., fairness, evidence, governance). You will also identify which frameworks are not necessary and justify why.
By the end of this lesson, you will have a framework-selection matrix, an integrated analysis outline, an evidence map, and a residual-uncertainty register. These products will form the analytical core of your final capstone report.
Frameworks are not checklists; they are analytical lenses. Using them thoughtfully ensures that your strategy is grounded in established principles and that you do not overlook critical issues. A well-selected set of frameworks makes your analysis defensible, comprehensive, and transparent.
2. Connection to the Capstone Project
Your final capstone report includes a dedicated Framework Selection and Rationale section (Section 11 of the recommended structure) and an Integrated Responsible AI Analysis (Section 12). This lesson provides the raw material for those sections.
The frameworks you select will shape how you analyse fairness, information governance, evidence quality, human impact, and future scenarios. They also connect to the governance and safeguard design you will develop in Lesson 4.
- Lesson 1 defined your problem and purpose; these guide framework selection.
- Lesson 2 provided workflow and responsibility maps; frameworks like PARTNER and SCOPE directly apply to these.
- Lesson 4 will use your integrated analysis to design governance and safeguards.
- Lesson 5 will audit your analysis and ensure you have addressed all frameworks appropriately.
3. Learning Outcomes
By completing this lesson, you will be able to:
- Review the complete set of course frameworks and understand their purpose and scope.
- Match frameworks to the specific questions, risks, and governance needs of your capstone project.
- Distinguish between primary and supporting frameworks and justify your selections.
- Explain why certain frameworks are not applicable to your project.
- Apply selected frameworks to your problem, stakeholder analysis, workflow, and evidence.
- Synthesise findings from multiple frameworks into a coherent, non-repetitive integrated analysis.
- Map claims to evidence sources and identify residual uncertainties.
- Develop a preliminary recommendation direction based on your integrated analysis.
4. Key Concepts
This lesson centres on framework selection, integrated analysis, and evidence mapping. Below are the key concepts you will apply.
4.1 Framework Selection Criteria
You should select frameworks based on:
- Problem and purpose – What is the central challenge? Which frameworks directly address it?
- Discipline and stakeholders – Which frameworks are most relevant to your professional context?
- Information and AI role – What data, permissions, and AI capabilities are involved?
- Workflow and responsibility – Where are the human-AI interactions and authority points?
- Level of consequence – High-stakes contexts require more governance-oriented frameworks (e.g., GOVERN).
- Evidence required – How will you verify claims? (TRACE, CLAIM, RIGOUR).
- Future uncertainties – Are you considering emerging capabilities? (FUTURES).
You are not required to apply every framework. Choose those that add value and avoid checklist-driven use.
4.2 Primary vs. Supporting Frameworks
A primary framework is the overarching lens that shapes your entire analysis. It often addresses the core tension or opportunity in your project (e.g., AI Paradox, ORBIT, or PARTNER if allocation is central). Supporting frameworks address specific dimensions (e.g., FAIRER for fairness, GOVERN for governance).
You will typically have one primary and two to four supporting frameworks. Too many frameworks fragment the analysis; too few leave gaps.
4.3 Integrated Analysis
An integrated analysis does not present framework findings in separate, disconnected sections. Instead, it weaves them together to tell a coherent story about your proposed AI integration. You might organise by workflow steps, by stakeholder group, or by key questions, and then show how each framework sheds light on that aspect.
4.4 Evidence Map
An evidence map links every important claim in your analysis to a specific, verifiable source. This ensures that your strategy is evidence-based and not reliant on unverified AI-generated assertions. You will trace claims back to course materials, scholarly sources, professional standards, or other authoritative documents.
4.5 Residual-Uncertainty Register
Even with rigorous analysis, some uncertainty will remain. A residual-uncertainty register documents what you do not know, what assumptions you made, and where new evidence might change your conclusions. This is a hallmark of responsible AI practice.
4.6 Framework Names and Purposes (Quick Reference)
The course frameworks are grouped by theme. Use these when selecting frameworks:
- Foundational: AI Paradox, ORBIT – for opportunity-risk framing.
- Prompting & Workflow: PCAFE-V, SCOPE, PARTNER – for prompt design, context/stages, and human-AI allocation.
- Responsibility, Rights, Information: FAIRER (fairness/accessibility), PROTECT (privacy/security), CREATE (copyright/authorship).
- Evidence & Learning: TRACE, CLAIM, LEARN, RIGOUR – for verifying claims, learning impact, and research integrity.
- Applied Practice: VOICE (writing/communication), WORKS (organisational), LIFE (personal/consumer).
- Discipline, Governance, Integration: DOMAIN, GOVERN, FUTURES, HUMAN – for translating to discipline, governance, future scenarios, and human-centric integration.
Refer to the course materials for exact expansions; do not invent them. If you are unsure about a framework's details, use it by name and purpose only.
Selection Criteria
Problem, discipline, information, workflow, consequence, evidence, future uncertainty.
Primary vs. Supporting
One primary lens; two to four supporting frameworks.
Integrated Analysis
Thematic structure, not framework-by-framework.
Evidence Map
Every claim linked to a verifiable source.
Residual Uncertainty
Documented assumptions, gaps, and limitations.
Quick Reference
Grouped framework names and purposes.
5. Retrieval Practice
Before you begin the guided activities, recall what you know about frameworks and integration.
1. What is the main risk of using too many frameworks in your analysis?
Show hint
Think about fragmentation, repetition, and loss of focus.
2. How do you decide which framework is your primary one?
Show hint
Consider what is most central: the core problem, the main tension, or the key governance need.
3. What is the purpose of an evidence map?
Show hint
To link every claim to a verifiable source, ensuring accountability and credibility.
4. Why should you document residual uncertainty?
Show hint
To be transparent about limitations and to guide future monitoring and adaptation.
5. Give an example of a project where PARTNER would be a primary framework.
Show hint
Think of a project where human-AI allocation and authority are the central design challenge.
6. Worked Synthetic Example
Continuing the Education stream example from Lessons 1 and 2, the student now selects frameworks and builds an integrated analysis.
6.1 Framework-Selection Matrix
| Framework | Relevance | Selected? | Role |
|---|---|---|---|
| AI Paradox | High-level opportunity vs. risk framing | Yes | Supporting |
| ORBIT | Opportunity, Risk, Benefit, Impact, Trade-offs | No (covered by AI Paradox + others) | – |
| PARTNER | Central: human-AI allocation and authority | Yes | Primary |
| SCOPE | Context, sources, stages, evaluation gates | Yes | Supporting |
| FAIRER | Accessibility and inclusion for students with disabilities | Yes | Supporting |
| PROTECT | Privacy of lecture recordings, student data | Yes | Supporting |
| TRACE / CLAIM | Verification of AI-generated summaries and claims | Yes | Supporting |
| GOVERN | Oversight, monitoring, incident response | Yes | Supporting |
| FUTURES | Adaptive safeguards for emerging capabilities | Yes | Supporting |
| HUMAN | Final integration of human purpose, agency, accountability | Yes | Supporting (final review) |
| VOICE, WORKS, LIFE | Not applicable (not writing/organisational/personal focus) | No | – |
| CREATE | Copyright, authorship – not central (lecture content is owned by institution) | No | – |
| LEARN | Learning impact – relevant but covered by FAIRER and HUMAN | No (covered) | – |
Primary: PARTNER (responsibility and authority are the core design challenge).
Supporting: AI Paradox, SCOPE, FAIRER, PROTECT, TRACE/CLAIM, GOVERN, FUTURES,
HUMAN.
Excluded: ORBIT (covered), VOICE, WORKS, LIFE, CREATE, LEARN (not central or covered).
6.2 Integrated Analysis Outline
The student organises the analysis around three key themes:
- Human-AI Allocation and Authority (PARTNER + SCOPE) – Map each workflow step to responsibility, review, decision, and stop authorities. Use SCOPE to define stages and evaluation gates (e.g., draft, review, approval, distribution).
- Fairness, Access, and Privacy (FAIRER + PROTECT) – Assess representation of students with disabilities, ensure accessibility, and protect lecture content and student privacy through consent and data minimisation.
- Evidence, Verification, and Governance (TRACE/CLAIM + GOVERN + FUTURES + HUMAN) – Plan for verifying AI outputs, establish monitoring, incident response, and adaptive safeguards for future changes. Conclude with HUMAN integration of purpose, agency, and accountability.
This structure avoids repeating framework findings; each theme draws on multiple frameworks in an integrated way.
6.3 Evidence Map (Excerpt)
| Claim | Source | Verification |
|---|---|---|
| Students with visual impairments face delays in accessing materials. | University accessibility office survey (synthetic data); scholarly article on accessibility in higher education (cite specific). | Check survey methodology; verify article peer-reviewed. |
| AI-generated summaries require human review to ensure accuracy. | Course materials, Chapter 17; professional standards for accessibility. | Confirm source authority; check currency. |
| Lecture recordings are subject to institutional privacy policies. | Institutional policy document; PROTECT framework guidance. | Verify policy version; check applicable laws. |
6.4 Residual-Uncertainty Register
- AI accuracy – We assume a 95% accuracy rate for summarisation; actual performance may vary.
- Student adoption – We assume students will use the summaries; actual usage may be lower.
- Instructor engagement – We assume instructors will review summaries; they may lack time.
- Technological change – Future AI capabilities may change the viability of this approach.
6.5 Preliminary Recommendation Direction
Based on the integrated analysis, the student recommends a conditional adoption of the AI-supported summarisation system, with a phased rollout starting with a pilot in one department, strict human review, and a clear fallback to manual transcription. The recommendation is qualified: the system should not be adopted without ongoing monitoring and a re-evaluation after six months.
The student has thoughtfully selected frameworks, built an integrated analysis, mapped evidence, documented uncertainty, and arrived at a qualified recommendation.
7. Guided Activity
Using your project brief (Lesson 1) and workflow/responsibility design (Lesson 2), complete the following steps to select frameworks and plan your integrated analysis.
7.1 Review the Framework Set
Refresh your memory of all course frameworks. You can refer to the list in Section 4.6. For each framework, ask: “Does this framework address a central question, risk, or governance need in my project?”
7.2 Create a Framework-Selection Matrix
For each framework, decide if it is Primary, Supporting, or Not Selected. Provide a brief justification. Use a table like the one in the worked example.
List frameworks, your selection, and a short reason.
7.3 Identify Primary Framework Rationale
Write a clear rationale for your primary framework. Why is it the most appropriate lens for your analysis? What does it help you see that other frameworks might miss?
Explain why your primary framework is central.
7.4 Identify Supporting Framework Rationale
For each supporting framework, explain how it complements the primary framework and addresses specific aspects (e.g., fairness, evidence, governance).
List each supporting framework and its specific contribution.
7.5 List Excluded Frameworks with Brief Justification
Explain why you did not select certain frameworks. This demonstrates thoughtful selection rather than random inclusion.
List frameworks you excluded and why.
7.6 Develop an Integrated Analysis Outline
Organise your analysis into three to five thematic sections that draw on multiple frameworks. Avoid a “framework-by-framework” structure. For example, themes might be: (1) Responsibility and Workflow, (2) Fairness and Access, (3) Evidence and Verification, (4) Governance and Adaptation, (5) Human Integration.
Describe your thematic structure and which frameworks inform each theme.
7.7 Build an Evidence Map
For each major claim in your analysis, identify a specific source (course material, scholarly article, policy, etc.) and note how you will verify it. Use the table format from the worked example.
Create a table linking claims to sources and verification methods.
7.8 Create a Residual-Uncertainty Register
List at least three to five uncertainties, assumptions, or areas where evidence is incomplete. For each, note how it might affect your recommendation.
Document your uncertainties and their potential impact.
7.9 Articulate Preliminary Findings and Recommendation Direction
Based on your analysis so far, what is your preliminary conclusion? Is the AI integration recommended, recommended with conditions, or not recommended? This is preliminary; you will refine it in Lessons 4 and 5.
State your preliminary recommendation and the key findings supporting it.
8. Student Production Activity
Now produce the complete set of deliverables for this lesson. These will form the analytical backbone of your final capstone.
- Framework-selection matrix – a table listing all frameworks, your selection (Primary / Supporting / Not selected), and a brief justification.
- Primary-framework rationale – a concise explanation of why your primary framework is the most appropriate.
- Supporting-framework rationales – for each supporting framework, explain its specific contribution.
- List of excluded frameworks – with a brief justification for each exclusion.
- Integrated analysis outline – a thematic structure with notes on which frameworks inform each theme.
- Evidence map – a table linking each key claim to a source and verification method.
- Residual-uncertainty register – a list of uncertainties, assumptions, and their potential impact.
- Preliminary findings and recommendation direction – a short statement of your current conclusion.
Format: You may use a word processor or spreadsheet. Ensure all products are clearly labelled and saved in your evidence-retention folder.
Do not simply apply every framework mechanically. Your selection should be defensible and tailored to your project. If you find yourself struggling to justify a framework's inclusion, consider excluding it.
9. Evidence-Retention Box
Add the following items to your evidence-retention folder:
- Framework-selection matrix
- Primary-framework rationale
- Supporting-framework rationales
- Excluded frameworks list
- Integrated analysis outline
- Evidence map
- Residual-uncertainty register
- Preliminary findings and recommendation direction
These products will be essential for Lesson 4 (governance) and Lesson 5 (synthesis and audit).
10. Common Problems and Corrective Actions
| Problem | Description | Corrective Action |
|---|---|---|
| Applying every framework | Results in a checklist-style analysis that lacks focus. | Select only those frameworks that are genuinely relevant. Exclude others with justification. |
| No primary framework | All frameworks are treated equally, leading to a flat analysis. | Identify the one framework that is most central to your project's core challenge. |
| Fragmented analysis | Each framework is discussed separately without integration. | Organise by themes that cut across frameworks. Show how frameworks complement each other. |
| Weak evidence map | Claims are made without clear sources, or sources are not verified. | For each claim, identify a specific, authoritative source. Verify citations and dates. |
| Ignoring uncertainty | No residual-uncertainty register; project appears overly confident. | Document assumptions, limitations, and areas where evidence is incomplete. |
| Recommendation not supported | Preliminary recommendation does not clearly follow from the analysis. | Ensure your recommendation is logically derived from the integrated analysis and evidence. |
11. Responsible-Use Boundaries
When selecting and applying frameworks, keep the following boundaries in mind:
- Do not invent or reconstruct framework expansions; use the exact author-approved expansions from course materials.
- Do not claim that a framework supports a conclusion it does not.
- Do not use frameworks as a substitute for critical thinking; they are tools, not answers.
- Do not present AI-generated analysis as your own reasoning; you must integrate and verify all claims.
- Refer to frameworks by name and purpose, and cite course materials when using them.
- Justify your selections with clear reasoning linked to your project's context.
- Use the evidence map to ground every claim in a verifiable source.
- Be transparent about what you do not know and what you assume.
12. Three Equivalent Participation Pathways
You may complete this lesson using any of the three pathways below.
Option A: Approved AI Tools
Use AI tools for bounded tasks such as:
- Generating a candidate list of frameworks relevant to your problem (verify against course list).
- Drafting an initial outline for your integrated analysis.
- Suggesting potential evidence sources based on your topic.
- Helping you articulate residual uncertainties.
You must critically evaluate all AI-generated content and ensure it aligns with course frameworks and your own reasoning. You remain the author of all final products.
Option B: Supplied Capstone Records
Use supplied materials such as:
- Example framework-selection matrices for different streams.
- Sample integrated analysis outlines.
- Template evidence maps.
- Lists of common uncertainties for your discipline.
Adapt these materials to your specific project, ensuring that your selections and analysis reflect your unique scope and purpose.
Option C: Non-AI Project Development
Complete all activities using conventional methods:
- Review course materials manually to identify relevant frameworks.
- Develop your matrix and outline using word processing or spreadsheet tools.
- Build your evidence map by searching library databases and professional sources.
- Document uncertainties through careful reflection on your assumptions.
All pathways assess the same learning outcomes. Choose the one that best fits your workflow.
13. Accessibility Guidance
Ensure your framework selection and analysis products are accessible:
- Use clear headings in your analysis outline.
- Make tables (matrix, evidence map) with proper headers and a caption.
- Provide a text description of any diagrams or visual representations of framework relationships.
- Write in plain language, defining technical terms.
- Ensure your residual-uncertainty register is structured (e.g., bulleted list with clear categories).
14. Self-Check Questions
1. What is the main disadvantage of using too many frameworks in your analysis?
Show feedback
Feedback: B is correct. Too many frameworks can make the analysis disjointed and repetitive. Quality over quantity is key.
2. Which framework would you use if your project's central issue is human-AI allocation and authority?
Show feedback
Feedback: B is correct. PARTNER is specifically designed for human-AI allocation and authority. The others address fairness, privacy, and evidence, respectively.
3. What is the purpose of an evidence map?
Show feedback
Feedback: B is correct. An evidence map is a tool for accountability and verification, not just a bibliography.
4. Why should you document residual uncertainty?
Show feedback
Feedback: B is correct. Documenting uncertainty is a sign of responsible analysis, not weakness.
5. Which of the following is not a good reason to exclude a framework?
Show feedback
Feedback: C is not a good reason. You should become familiar with all frameworks before deciding to exclude. If you are not familiar with one, you cannot make a justified exclusion.
6. In an integrated analysis, how should you structure your findings?
Show feedback
Feedback: B is correct. Thematic structure integrates frameworks and avoids repetition.
7. What should you do if you cannot find a verifiable source for an important claim?
Show feedback
Feedback: B is correct. If you cannot verify a claim, you should explicitly identify it as an assumption and document the uncertainty. Do not fabricate sources.
8. Which framework would be most appropriate for assessing the impact of an AI system on student learning and skill development?
Show feedback
Feedback: A is correct. LEARN is designed for learning, teaching, and capability development. The others address organisational, communication, and copyright issues.
15. Completion Checklist
- I have reviewed the purpose and connection to the Capstone Project.
- I have completed the retrieval practice questions.
- I have studied the worked synthetic example and understand the selection process and integrated analysis structure.
- I have completed the guided activity:
- Reviewed the framework set
- Created a framework-selection matrix
- Written primary and supporting framework rationales
- Listed excluded frameworks with justification
- Developed an integrated analysis outline
- Built an evidence map
- Created a residual-uncertainty register
- Articulated preliminary findings and recommendation direction
- I have produced all required student products.
- I have saved all evidence in my evidence-retention box.
- I have reviewed the common problems and corrected any issues.
- I have confirmed that I have not invented framework expansions and have used course materials.
- I have chosen a participation pathway and completed the lesson accordingly.
- I have ensured my products are accessible.
- I have completed the self-check questions and reviewed the feedback.
You are now ready for Lesson 4: Governance, Scenarios, and Adaptive Safeguards. Your integrated analysis will inform the risk classification and safeguard design in the next lesson.
16. Section Summaries
Purpose
Select and apply relevant frameworks, build an integrated analysis, and map evidence to claims.
Connection
Directly feeds into the Framework Selection and Integrated Analysis sections of your final report.
Learning Outcomes
You can now select frameworks, justify your choices, build a thematic analysis, and document uncertainty.
Key Concepts
Framework selection criteria, primary vs. supporting, integrated analysis, evidence map, residual-uncertainty register.
Retrieval Practice
Recalled key concepts to prepare for the activities.
Worked Example
Showed a complete selection matrix, integrated outline, evidence map, and uncertainty register for an Education project.
Guided Activity
Step-by-step prompts to build your own framework selection and integrated analysis.
Student Production
Produced eight concrete deliverables that form the analytical core of your capstone.
Evidence-Retention
Saved all products for later use in governance and synthesis lessons.
Common Problems
Addressed over-selection, fragmentation, weak evidence, and unsupported recommendations.
Responsible-Use Boundaries
Reinforced that frameworks are tools, not answers; do not invent expansions or fabricate sources.
Participation Pathways
Offered three equivalent ways to complete the lesson.
Accessibility
Guided you to ensure your matrix, outline, and maps are clear and structured.
Self-Check
Tested understanding of framework selection, evidence mapping, uncertainty, and integration.
Completion Checklist
Confirmed all required work is done and no stop conditions are triggered.
In Lesson 4, you will translate your integrated analysis into governance controls, risk classification, and adaptive safeguards.