Tutorial 1 of 5

Capstone Scope, Purpose, and Evidence of Need

COMP 327 Capstone Project — Assignment 6: Discipline-Specific Responsible AI Integration Strategy

Suggested completion time: 120–150 minutes

Required prior work: Unit 20 proposal draft; course readings through Unit 20

Capstone period: Weeks 12–13

Recommended length: 4,000–5,000 words (final project)

1. Purpose of This Tutorial

This tutorial helps you transform the preliminary proposal you developed in Unit 20 into a bounded, feasible, and evidence-grounded Capstone Project. You will define a discipline-specific problem, establish a legitimate purpose, identify evidence of need, compare AI-supported and non-AI alternatives, and confirm that your project can be completed within the required length and period.

By the end of this tutorial, you will have a clear project brief that will guide all subsequent work. This is the foundation upon which your stakeholder analysis, workflow design, framework selection, governance planning, and final synthesis will be built.

📌 Why this matters

A well-scoped project is the single most important factor in producing a high-quality capstone. Projects that are too broad, lack evidence, or depend on unavailable resources cannot be completed successfully. This tutorial establishes stop conditions that protect you from investing time in an unworkable proposal.

2. Connection to the Capstone Project

The COMP 327 Capstone Project is the culminating assessment for the course. It requires you to integrate knowledge from Units 1 through 20 and apply it to a discipline-specific responsible AI integration strategy. This tutorial is the first of five project-development studios; each tutorial builds on the previous one to help you produce a concrete, submission-ready deliverable.

Your final product is a Discipline-Specific Responsible AI Integration Strategy of approximately 4,000–5,000 words, submitted as Assignment 6. This tutorial establishes the scope, purpose, and evidence of need for that strategy. Without a solid foundation here, the later tutorials cannot yield a coherent, defensible final project.

🔗 Links to other tutorials

Tutorial 2 builds on your scope and purpose to map stakeholders and workflows.
Tutorial 3 uses your problem definition to select and apply relevant frameworks.
Tutorial 4 transforms your identified risks into governance and safeguards.
Tutorial 5 synthesises everything into a verified, accessible final submission.

3. Learning Outcomes

By completing this tutorial, you will be able to:

Select and confirm a capstone stream and a discipline-specific problem that is bounded, evidence-supported, and feasible for a 4,000–5,000-word strategy.
Distinguish a broad topic from a bounded problem and articulate what is inside and outside your project scope.
Establish a legitimate human, organisational, community, professional, or public purpose for your proposed AI integration.
Identify and evaluate evidence that the problem or need exists, using authoritative disciplinary sources.
Compare AI-supported and non-AI alternatives, articulating the trade-offs and assumptions underlying each.
Develop preliminary inquiry or recommendation questions that will guide your research and analysis.
Assess feasibility and identify when specialist review, ethical approval, or additional authority is required.
Recognise stop conditions that would make a project unsuitable for the capstone and take corrective action.

4. Key Concepts

The following concepts are central to this tutorial. You encountered many of them in Units 1–20; here they are applied specifically to the task of scoping your capstone.

4.1 Bounded Problem

A bounded problem is one that is sufficiently narrow to be addressed within the constraints of the capstone (4,000–5,000 words, two weeks) while still being substantial enough to demonstrate integration of course learning. A bounded problem has clear boundaries: you can state what is included and, equally important, what is excluded.

💡 Example

Broad topic: "AI in healthcare"
Bounded problem: "An AI-supported clinical documentation assistant for discharge summaries in a hospital internal medicine unit, with human physician final review and approval."

4.2 Legitimate Purpose

A legitimate purpose is one that serves a genuine human, organisational, community, professional, or public need. It is not merely commercial opportunity, curiosity, or convenience. A legitimate purpose is defensible on ethical, professional, and practical grounds and aligns with the responsible use of AI.

4.3 Evidence of Need

Evidence of need is the documented basis for asserting that the problem you have identified actually exists and matters to stakeholders. Evidence can come from scholarly research, professional standards, organisational data, policy documents, authoritative technical documentation, accessibility guidance, or community governance requirements.

4.4 AI-Supported vs. Non-AI Alternatives

A responsible AI integration strategy must consider both the proposed AI-supported workflow and the non-AI alternatives. This comparison is not a simple "AI is better" claim; it requires an honest assessment of what each approach can and cannot achieve, the resources required, the risks involved, and the human capabilities preserved or diminished.

4.5 Scope Exclusions

Scope exclusions are deliberate boundaries that you set to keep the project feasible. They are not afterthoughts; they are essential design decisions that protect the integrity of your analysis. A responsible strategy acknowledges what it does not address.

Bounded Problem – narrow, clear boundaries, feasible within capstone constraints

Legitimate Purpose – serves genuine human, organisational, or public need

Evidence of Need – documented basis from authoritative sources

Alternatives Comparison – honest assessment of AI and non‑AI approaches

Scope Exclusions – deliberate boundaries that keep the project feasible

Feasibility – can be completed within length, time, and resource constraints

4.6 Frameworks Referenced in This Tutorial

While you will select and apply frameworks in depth in Tutorial 3, two framing frameworks are particularly relevant to scope and purpose:

ORBIT – Opportunity, Risk, Benefit, Impact, Trade-offs. Helps frame the high-level assessment of whether an AI integration is worthwhile and responsible.
AI Paradox – The tension between AI's potential benefits and its potential harms, and the need for deliberate, evidence-based navigation.

You are not required to apply these frameworks in this tutorial, but you should keep them in mind as you define your problem and purpose.

5. Retrieval Practice

Before you begin the guided activities, take a few minutes to recall what you already know. Answer these questions in your own words. This retrieval practice strengthens your memory and prepares your mind for the work ahead.

1. What is the difference between a broad topic and a bounded problem? Give an example from your own discipline.

Think about what makes a problem "bounded" — what are the boundaries? What is included and what is excluded?

2. List three types of evidence you could use to establish that a problem exists in a professional or disciplinary context.

Consider scholarly sources, professional standards, policy documents, organisational data, community governance, or accessibility guidance.

3. Why is it important to compare AI-supported and non-AI alternatives, rather than simply assuming AI is the best solution?

Think about responsibility, risk, human capability, and the principle of proportionality.

4. What does "legitimate purpose" mean in the context of responsible AI integration?

Consider whose needs are served, what values are advanced, and what ethical or professional standards apply.

5. Name two stop conditions that would require you to revise or abandon your capstone proposal.

Review the stop conditions listed in the master prompt — consider scope, evidence, authority, and feasibility.

6. Worked Synthetic Example

This worked example shows how a student in the Education stream might complete the scoping activities for their capstone. The example is synthetic; it is not a real project but illustrates the process and decisions involved.

6.1 Initial Topic

"I want to explore how AI can be used in post-secondary education to support students with disabilities."

This is a broad topic, not a bounded problem. It encompasses many possible uses of AI (tutoring, transcription, content adaptation, assessment accommodation, etc.), many types of disabilities, and many institutional contexts.

6.2 Bounded Problem

After reviewing the course materials and consulting the Unit 20 feedback, the student refines the topic:

✓ Bounded Problem Statement

Problem: At a mid-sized Canadian university, students with visual impairments face inconsistent access to course materials, including lecture notes, slide decks, and assigned readings, due to variable quality of institutional accessibility services and limited availability of human transcription support.

Proposed AI role: An AI-supported system that generates structured, accessible text summaries of lecture recordings and slide content, with human review by accessibility specialists and instructors before distribution to students.

6.3 Legitimate Purpose

✓ Purpose Statement

The purpose is to improve timely and equitable access to course materials for students with visual impairments, reducing the delay between lecture delivery and accessible material availability. This serves the institutional commitment to accessibility and inclusion under relevant human rights and accessibility legislation, and it supports student learning outcomes.

6.4 Evidence of Need

The student identifies several sources of evidence:

Institutional data: The university's accessibility office reports average delays of 7–10 business days for transcription requests.
Student feedback: Survey results from the disability student group indicate that 78% of respondents experience material-access delays affecting their academic performance.
Scholarly research: Studies on accessibility in higher education document the impact of delayed access on learning outcomes and student well-being.
Professional standards: The university's accessibility policy commits to "timely and equitable access to all course materials."

6.5 AI-Supported vs. Non-AI Alternatives

Table 1: Comparison of AI-supported and non-AI alternatives for the worked example
Approach	Advantages	Disadvantages / Risks	Human effort required
AI-supported (proposed)	Faster turnaround; scalable; can handle multiple courses simultaneously	Risk of errors; need for human review; privacy of lecture content; training required	Moderate — review, correction, and distribution by specialists
Non-AI: Expanded human transcription	High quality; human judgment; no AI-specific risks	Costly; slow; capacity-limited; cannot scale quickly	High — more transcription staff required
Non-AI: Institutional reform	Systemic improvement; addresses root causes	Slow; requires policy change and funding; uncertain timeline	Variable — policy and administrative effort

6.6 Scope Exclusions

This project does not propose live, real-time transcription (only post-lecture summarisation).
It does not address all types of disabilities — only visual impairment and material access.
It does not replace human accessibility specialists or instructors.
It does not involve deployment on real student records — all analysis is synthetic and scenario-based.

6.7 Feasibility Check

The student confirms that:

The project fits within 4,000–5,000 words.
Sources are available through the university library and public accessibility guidance.
No live deployment or real consequential decisions are required.
Specialist review (accessibility office feedback) can be sought if the student has institutional permission (or a synthetic consultation can be constructed).
The two-week capstone period is sufficient for the analysis and strategy development.

✅ Stop conditions passed

The project is bounded, evidence-supported, purposeful, and feasible.

7. Guided Activity

In this activity, you will work step-by-step to define your own capstone scope and purpose. Use the prompts below to generate the raw material for your student production activity. You may use the worked example as a model, but your answers must reflect your own discipline and chosen problem.

7.1 Select Your Capstone Stream

Identify which of the 16 approved capstone streams your project belongs to. If you are using the Open Interdisciplinary Stream, describe your proposed disciplinary combination.

✏️ Your stream:

Write your stream here.

7.2 Define Your Broad Topic

Start with the topic you brought from Unit 20. This is your starting point, not your final bounded problem.

✏️ Broad topic:

Write your broad topic here.

7.3 Refine to a Bounded Problem

Use the following questions to narrow your topic. Write a concise bounded problem statement.

What specific setting or context are you focusing on?
Who are the primary people affected?
What specific AI role are you proposing?
What are the boundaries of that AI role (what will it not do)?
What is the human activity that remains outside the AI's role?

✏️ Bounded problem statement:

Write your bounded problem statement here.

7.4 Establish Your Purpose

Write a statement that articulates the legitimate purpose of your proposed AI integration. Be specific about whose needs are served and what values or principles are advanced.

✏️ Purpose statement:

Write your purpose statement here.

7.5 Identify Evidence of Need

List at least three types of evidence you can draw on to establish that the problem exists. For each, note where you will obtain that evidence.

✏️ Evidence of need:

List your evidence sources here.

7.6 Compare AI and Non-AI Alternatives

Complete a comparison table like the one in the worked example. Identify at least two non-AI alternatives and articulate the advantages and disadvantages of each relative to your proposed AI-supported approach.

✏️ Alternatives comparison:

Describe your AI-supported approach and compare it to at least two non-AI alternatives.

7.7 Define Your Scope Exclusions

List at least four things that are deliberately outside the scope of your project. Be specific about what you are not addressing.

✏️ Scope exclusions:

List your scope exclusions here.

7.8 Preliminary Questions

Develop three to five preliminary research or recommendation questions that your capstone will address. These questions will guide your analysis and framework selection in later tutorials.

✏️ Preliminary questions:

Write your preliminary questions here.

7.9 Feasibility Check

Review your bounded problem against the feasibility criteria. If any are not met, revise your problem statement.

Can be addressed in 4,000–5,000 words
Can be completed within the two-week capstone period
Sources are accessible (library, public, or synthetic)
No live deployment or real consequential decisions required
No need for professional authority you do not possess
No confidential, personal, proprietary, or security-sensitive information is required
Specialist review (if needed) can be obtained or simulated

8. Student Production Activity

Now you will produce the capstone project brief that will serve as the foundation for all subsequent tutorials. This brief is a working document; you will refine it as you progress, but it must be complete enough to guide your work.

📄 Required Student Products

Create a single document (or set of documents) that includes all of the following:

Finalized capstone project brief – a concise summary of your project (1–2 paragraphs) that includes the problem, purpose, and proposed AI role.
Scope statement – a clear, bounded definition of what your project covers, including the context, setting, and boundaries.
Purpose and evidence-of-need statement – a narrative that explains why the problem matters, supported by evidence sources.
AI-versus-non-AI alternatives comparison – a table or structured comparison of at least three approaches (one AI-supported, two or more non-AI).
Preliminary authoritative-source plan – a list of at least five sources (scholarly, professional, policy, or technical) that you will use.
Preliminary research or recommendation questions – three to five questions that will guide your analysis.
Scope exclusions – a clear list of what is deliberately excluded.
Feasibility check – a brief assessment confirming that your project meets the feasibility criteria.

Format: You may use a word processor, a plain text file, or any other tool that allows you to organise your thoughts. The goal is to produce usable evidence that you can carry forward into Tutorial 2.

Collaboration: You may discuss your ideas with peers or your instructor, but your final brief must be your own work and reflect your own discipline-specific context.

⚠️ Stop conditions

If you encounter any of the following stop conditions, stop and revise your proposal before continuing:

The project is too broad to be addressed in 4,000–5,000 words.
The problem is not supported by evidence from authoritative sources.
The purpose is unclear or unsuitable (e.g., purely commercial, speculative, or trivial).
Necessary information cannot be used lawfully or ethically (e.g., it is confidential, personal, proprietary, or restricted).
You lack access to suitable sources (e.g., the only evidence is behind a paywall or requires institutional access you do not have).
The project requires professional authority you do not possess (e.g., legal advice, medical diagnosis, engineering certification).
The proposal depends on live deployment or real consequential decisions that cannot be simulated or scenario-tested.
The project cannot be completed within the required length and period.

9. Evidence-Retention Box

As you work through the tutorials, you will generate a growing body of evidence that supports your final capstone. The evidence-retention box is a place to record and preserve that evidence so you can easily retrieve it when writing your final report.

📂 Evidence-Retention Box — Tutorial 1

Save these items in a folder or document:

Your completed project brief
Your scope statement
Your purpose and evidence-of-need statement
Your alternatives comparison table
Your preliminary source plan (with full citations)
Your preliminary research questions
Your scope exclusions list
Your feasibility check
Any feedback or notes from discussions with peers or instructor

Why this matters: In Tutorial 5, you will conduct a self-audit of your entire capstone. Having a clear record of your evidence will make that audit faster, more accurate, and more thorough.

10. Common Problems and Corrective Actions

The following are frequent challenges students encounter when scoping their capstone projects, along with suggested corrective actions.

Table 2: Common scoping problems and corrective actions
Problem	Description	Corrective Action
Topic is too broad	Project covers multiple contexts, populations, AI roles, or disciplines.	Narrow to one specific setting, one defined group, and one bounded AI role. Use the "who, what, where, when" constraints.
Purpose is vague	Purpose is stated as "improve efficiency" or "explore possibilities" without specific human or organisational benefit.	Articulate a specific human, organisational, or community need. Ask: "Who benefits, and how?" "What problem does this solve?"
Evidence is weak	Assertions about the problem are based on personal opinion or anecdote without supporting sources.	Identify authoritative sources: scholarly research, professional standards, policy documents, institutional data, or community governance.
No non-AI comparison	Proposal assumes AI is the best or only solution without considering alternatives.	Identify at least two non-AI approaches and compare their strengths, weaknesses, risks, and human effort requirements.
Scope is undefined	The project boundaries are unclear; it is not clear what is included and what is excluded.	Write a clear scope statement and a separate list of exclusions. Be explicit about what you are not addressing.
Feasibility not checked	Project requires data, authority, or resources that are unavailable.	Run through the feasibility checklist. If any criterion is not met, revise the scope or choose a different problem.

🚩 Red flags to watch for

Confidential data: You cannot use real patient, client, student, or employee records without explicit, documented authority.
Live deployment: You cannot actually deploy an AI system in a real setting as part of the capstone.
Professional authority: You cannot provide legal advice, medical diagnosis, engineering certification, or similar professional services unless you hold the appropriate credentials and have institutional authority.
Speculative AI: Your proposal should be grounded in current or emerging AI capabilities that are documented and understood, not futuristic speculative systems.

11. Responsible-Use Boundaries

The following boundaries apply to all capstone work. They are designed to protect you, your stakeholders, and the integrity of the course.

⛔ Do Not

Do not upload confidential, personal, proprietary, privileged, security-sensitive, unpublished, Indigenous, or culturally governed information without explicit, documented authority.
Do not require access to actual workplace or client records.
Do not conduct live deployment of any AI system.
Do not test attacks, vulnerabilities, prompt injection, tool misuse, surveillance, or data extraction against real systems.
Do not enable real transactions, email sending, publication, record modification, deletion, device control, or external actions.
Do not permit AI to make consequential decisions.
Do not present AI-generated citations, references, quotations, calculations, laws, policies, standards, or technical claims as verified.
Do not infer sensitive characteristics, credibility, intent, eligibility, diagnosis, or risk about real people.
Do not use AI to write personal reflection or replace your final synthesis and judgment.
Do not claim professional, legal, regulatory, medical, financial, engineering, psychological, Indigenous, community, or institutional authority that you do not possess.

✅ Do

Use synthetic, supplied, public, licensed, or explicitly authorised materials.
Build scenarios and models that illustrate how a responsible AI integration could work, without actual deployment.
Base your analysis on authoritative sources that you can cite and verify.
Seek qualified guidance when your project approaches boundaries you are not authorised to cross.
Document all assumptions, uncertainties, and limitations.

12. Three Equivalent Participation Pathways

You may complete this tutorial using any of the three pathways below. All pathways assess the same learning outcomes and use the same standards. Choose the pathway that best fits your circumstances and learning preferences.

Option A: Approved AI Tools

You may use approved AI tools for bounded, low-risk tasks such as:

Generating candidate search terms for your literature review
Generating questions for further investigation
Comparing possible report structures
Critiquing a synthetic workflow (not your own)
Testing low-risk prompts that do not involve sensitive information
Identifying potential omissions in your scope
Checking plain-language clarity of your purpose statement

📋 Important

You must independently verify all important claims and remain fully responsible for your final work. AI tools are assistants, not authors.

Option B: Supplied Capstone Records

You may use supplied materials such as:

Synthetic case descriptions relevant to your stream
Sample proposals and scope statements
Curated source sets
Example workflows and responsibility matrices
Prompts and outputs from sample projects
Information inventories and risk registers

Your instructor may provide these materials through the Moodle course site or in the course materials. If you are unsure whether a material is available, check the course site or ask your instructor.

Option C: Non-AI Project Development

You may complete the entire tutorial using conventional, non-AI methods:

Course readings from Units 1 through 20
Library databases and scholarly search engines
Conventional web search (using authoritative sources)
Word processing and spreadsheet tools
Diagramming or mind-mapping tools
Checklists and supplied examples
Instructor or peer feedback

✅ All pathways are equivalent

The same standards apply regardless of which pathway you choose. Your final project will be assessed on the quality of your analysis, evidence, reasoning, and responsible AI integration — not on whether you used AI tools.

13. Accessibility Guidance

This tutorial is designed to be accessible to all students. The following guidance helps you produce an accessible capstone project and ensures that you can participate fully regardless of your learning environment or needs.

13.1 For Your Capstone Project

Use semantic heading structure (heading levels in logical order).
Provide descriptive link text (not "click here").
Ensure sufficient colour contrast (aim for WCAG 2.1 AA standard).
Do not rely on colour alone to convey meaning.
Use plain language and define technical terms.
Provide text alternatives for all diagrams, tables, and figures.
Use accessible tables with properly marked headers.
Provide a structured text representation of any visual workflow or stakeholder map.
Save your final project in an accessible file format (PDF with tags, Word with styles, or HTML).

13.2 For Your Participation

If you require alternative formats or additional support, contact your instructor or the accessibility office.
You may submit a structured text description in place of a visual diagram for any activity that asks for a diagram.
All self-check questions are accessible via keyboard and screen reader.

♿ Accessibility resources

Refer to the course materials for additional accessibility guidance, including the institutional accessibility policy and the Web Content Accessibility Guidelines (WCAG) summary.

14. Self-Check Questions

Answer these questions to check your understanding of the concepts covered in this tutorial. Each question includes feedback to help you identify areas for further review.

1. Which of the following is the best example of a bounded problem suitable for the COMP 327 Capstone Project?

A) "The impact of AI on society"
B) "An AI-supported meeting summarisation tool for project teams in a small software development company, with human review and approval before distribution"
C) "AI in education"
D) "The future of AI in healthcare"

Feedback: Option B is correct. It specifies a context (small software development company), a bounded AI role (meeting summarisation), a human activity (review and approval), and a clear purpose. Options A, C, and D are broad topics, not bounded problems.

2. What is the primary purpose of comparing AI-supported and non-AI alternatives in a responsible AI strategy?

A) To prove that AI is always better than human effort
B) To demonstrate that AI is cheaper than non-AI approaches
C) To make an honest, evidence-based assessment of trade-offs and risks
D) To comply with institutional policy requirements

Feedback: Option C is correct. The comparison is about understanding trade-offs, risks, human effort, and consequences. It is not about proving AI is superior or simply checking a box.

3. Which of the following is not an appropriate source of evidence for establishing a problem's existence in your capstone?

A) A peer-reviewed journal article on accessibility in higher education
B) A professional standard or code of conduct
C) A personal opinion from a friend in the same discipline
D) An institutional policy document

Feedback: Option C is correct. Personal opinion, even from a friend in the discipline, is not authoritative evidence. You need sources that can be cited and verified. Options A, B, and D are all appropriate sources.

4. A well-defined scope exclusion does which of the following?

A) Identifies what is deliberately left out of the project
B) Shows that the project is incomplete or poorly planned
C) Lists all the sources that will not be used
D) Describes the limitations of the AI system

Feedback: Option A is correct. Scope exclusions are deliberate boundaries that keep the project feasible and focused. They are a sign of good project design, not incompleteness.

5. Which of the following is a stop condition that requires you to revise or abandon your capstone proposal?

A) The project is 4,500 words long
B) The project depends on live deployment in a real setting
C) The project uses public, open-source data
D) The project seeks feedback from a peer

Feedback: Option B is correct. Live deployment is a stop condition because the capstone is an analysis and strategy document, not a deployment project. Options A, C, and D are not stop conditions.

6. What is the relationship between a "broad topic" and a "bounded problem" in the capstone?

A) They are the same thing; the terms are interchangeable
B) A broad topic is the final project; a bounded problem is the proposal
C) A broad topic is the starting point; a bounded problem is the refined, focused project scope
D) A bounded problem is broader than a broad topic

Feedback: Option C is correct. You start with a broad topic and refine it into a bounded problem through careful scoping. The bounded problem is narrower, more specific, and feasible for the capstone.

7. Which of the following is not a characteristic of a legitimate purpose for an AI integration strategy?

A) It serves a genuine human or organisational need
B) It is defensible on ethical and professional grounds
C) It is primarily about generating profit or market advantage
D) It aligns with professional standards and values

Feedback: Option C is correct. While commercial viability may be a consideration, a legitimate purpose is fundamentally about serving genuine human, organisational, community, professional, or public needs — not merely profit.

8. When should you stop and seek guidance from your instructor or a qualified professional?

A) When you are unsure about a citation format
B) When your project touches on legal, regulatory, medical, or professional territory you are not authorised to address
C) When you cannot find a source in the university library
D) When you need to choose a capstone stream

Feedback: Option B is correct. Seek qualified guidance when your project approaches boundaries you are not authorised to cross. Citation formats, library searches, and stream selection are all within the normal scope of the course and do not require specialist professional guidance.

15. Completion Checklist

Use this checklist to confirm that you have completed all required elements of Tutorial 1. Check each item off as you complete it.

I have reviewed the purpose and connection to the Capstone Project.
I have reviewed the learning outcomes and key concepts.
I have completed the retrieval practice questions.
I have reviewed the worked synthetic example and understand how the student refined their broad topic into a bounded problem.
I have completed the guided activity, including selecting my stream, defining my broad topic, refining to a bounded problem, establishing purpose, identifying evidence, comparing alternatives, defining scope exclusions, developing preliminary questions, and conducting a feasibility check.
I have produced all required student products:
- Finalized capstone project brief
- Scope statement
- Purpose and evidence-of-need statement
- AI-versus-non-AI alternatives comparison
- Preliminary authoritative-source plan
- Preliminary research or recommendation questions
- Scope exclusions
- Feasibility check
I have saved all evidence in my evidence-retention box.
I have reviewed the common problems and corrective actions and checked my work against them.
I have reviewed the responsible-use boundaries and confirmed my project is compliant.
I have chosen a participation pathway and completed the tutorial using that pathway.
I have reviewed the accessibility guidance and ensured my project products are accessible.
I have completed the self-check questions and reviewed the feedback.
I have confirmed that no stop conditions apply to my project.

✅ Tutorial 1 Complete

When you have checked all items above, you are ready to proceed to Tutorial 2: Stakeholders, Workflow, and Responsibility Design. Remember to keep all your evidence and products accessible — you will need them for the subsequent tutorials and your final submission.

16. Section Summaries

Purpose of This Tutorial

This tutorial helps you transform your Unit 20 proposal into a bounded, feasible, evidence-grounded Capstone Project. It establishes the foundation for all subsequent work.

Connection to the Capstone Project

The Capstone Project is the culminating assessment for COMP 327. Tutorial 1 is the first of five development studios that build toward your final submission.

Learning Outcomes

You should now be able to select a capstone stream, define a bounded problem, establish a legitimate purpose, identify evidence of need, compare alternatives, develop preliminary questions, and assess feasibility.

Key Concepts

The central concepts are: bounded problem, legitimate purpose, evidence of need, AI vs. non-AI alternatives, scope exclusions, and feasibility. These concepts are the building blocks of a responsible AI integration strategy.

Retrieval Practice

Retrieval practice strengthens your ability to recall and apply concepts. The questions you answered are designed to activate your prior knowledge and prepare you for the guided activities.

Worked Synthetic Example

The Education-stream example illustrates how to refine a broad topic into a bounded problem, establish purpose and evidence, compare alternatives, define scope exclusions, and check feasibility. Use it as a model for your own work.

Guided Activity

You worked through a structured process to define your capstone scope and purpose. The prompts helped you generate the raw material for your student production activity.

Student Production Activity

You produced a complete capstone project brief with eight required components. This brief is the foundation for all future tutorials.

Evidence-Retention Box

You saved all your capstone products in a designated location. This evidence will be essential for the self-audit in Tutorial 5.

Common Problems and Corrective Actions

You reviewed common scoping problems and how to correct them. Being aware of these pitfalls helps you produce a stronger, more focused project.

Responsible-Use Boundaries

You reviewed the boundaries that apply to all capstone work. Your project must respect these boundaries to be acceptable for submission.

Participation Pathways

You chose one of three equivalent pathways to complete the tutorial. All pathways assess the same learning outcomes.

Accessibility Guidance

You reviewed guidance for producing an accessible capstone and ensuring your participation is supported. Accessibility is an integral part of responsible AI practice.

Self-Check Questions

You answered eight self-check questions and reviewed the feedback. This helped you confirm your understanding of the key concepts and identify areas for further review.

Completion Checklist

You verified that you have completed all required elements of Tutorial 1 and that no stop conditions apply to your project.

📌 Looking ahead

In Tutorial 2, you will map stakeholders, workflows, and responsibility. Your project brief from this tutorial will be your starting point. Keep it close at hand.