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Augmented Academia Workbook 3

Need a refresher on GenAI concepts, prompt frameworks, or accessibility?
All required foundational concepts, prompt engineering strategies, and accessibility guidelines are covered in the guides below. Please review them as needed before or during this workshop: These guides contain all the required concepts, frameworks, and best practices for effective and responsible use of GenAI in education. Refer to them any time for step-by-step instructions, prompt templates, and policy guidance.

This workbook guides you through using Copilot/GenAI to author comprehensive assessment briefs, audit and adapt existing assessments for accessibility and real‑world relevance, and generate robust rubrics for reliable marking.

Work through the prompts, and adapt them to your course.

📝 Iterative Assessment Transformation & Enhancement

Transform existing assessments into more engaging, authentic learning experiences while maintaining their learning outcomes. Use GenAI to add real-world context, collaborative elements, and process documentation to your assessments.

Transforming Existing Assessments

Most assessments can be transformed into more engaging, authentic tasks without changing their fundamental learning outcomes or increasing workload.

Starting with a basic assessment brief, we'll demonstrate how to iteratively transform it through multiple GenAI prompts.

Example Assessment Brief: Cell Biology Essay (1,800 words)

Task: Write an 1,800-word essay discussing the structure and function of cellular organelles. Your essay should include descriptions of at least five major organelles and explain how they contribute to overall cell function.

Learning outcomes:
- Demonstrate knowledge of cellular structure
- Explain the relationship between organelle structure and function
- Apply concepts of cellular biology to explain cellular processes

Submission: Submit your essay as a Word document to the course Moodle page.

Marking criteria:
- Scientific accuracy (40%)
- Depth of explanation (30%)
- Use of scholarly sources (20%)
- Organization and clarity (10%)

Step 1: Basic Transformation for Engagement

First, let's apply our transformation prompt to add real-world context, collaboration, and process documentation:

Assessment Transformation Prompt:

You are an expert assessment designer specializing in [YOUR SUBJECT].


Transform this into a more engaging version that:
- Adds one authentic, real-world context element
- Includes one collaborative component
- Requires process documentation alongside final work
- Maintains the same learning outcomes and workload

Provide: Enhanced assessment brief (max 200 words) + implementation timeline
Current assessment brief:
[PASTE YOUR ORIGINAL ASSESSMENT BRIEF HERE]

Exercise: Paste your ORIGINAL assessment brief

Your task: Paste the original assessment brief you want to transform (this will be used with the transformation prompt above).

Step 2: Accessibility Enhancement

Now, let's further improve the assessment by specifically addressing accessibility concerns:

Second Transformation Prompt:

Review this assessment brief for accessibility barriers and inclusive design:

[PASTE THE FIRST ENHANCED ASSESSMENT]

Provide specific recommendations to improve:
1. Alternative formats and submission options
2. Flexibility in group work arrangements
3. Clear, plain language instructions
4. Inclusive examples and contexts
5. Reasonable adjustments that maintain academic standards

Return: Specific rewording suggestions and implementation guidance.

Exercise: Paste your GenAI-enhanced assessment brief

Your task: After using the transformation prompt above, paste your GenAI-enhanced assessment brief here for reference and further editing.

Designing Assessments Resistant to GenAI Misuse

Make assessments resilient to inappropriate use of GenAI by combining design, process, and verification strategies. Use a layered approach rather than relying on any single method.

  1. Authentic, situated tasks: Ask students to apply knowledge to specific local/case contexts, datasets, or recent events that require domain judgement and context awareness.
  2. Process-based evidence: Require process logs, annotated drafts, decision rationales, and versioned artefacts that show the student's thinking and iterations.
  3. Personalised prompts: Include small personalised inputs (e.g., a short reflection, a dataset excerpt, or a class-specific parameter) that change each student's required output.
  4. Staged submissions: Break assessment into milestones (proposal, draft, peer review, final) with feedback loops—harder for AI to fabricate consistently across stages.
  5. Oral or viva components: Short recorded explanations or viva voce questions tied to submitted work test understanding and deter outsourcing.
  6. Low-stakes formative practice: Train students to use AI appropriately in formative tasks and require declaration of AI use in summative tasks.
  7. Randomised question pools: Use parameterised questions or banks so individual answers differ and can't be copied wholesale.
  8. Assessment analytics: Monitor metadata (timestamps, submission patterns), similarity checks, and anomalous answer patterns to flag items for review.
  9. Explicit academic integrity: Require a short integrity statement and use spot-checking with source verification.
AI-Resilience Design Prompt (for instructors):

    You are an expert assessment designer. Given this assessment brief: [PASTE BRIEF], propose modifications and an evidence collection plan that make the assessment resistant to inappropriate GenAI use while preserving learning outcomes. Include:
    - 3 small personalised input variations to give every student a unique task
    - 2 process-based evidence requirements (e.g., reflective log, annotated draft)
    - A staged submission timeline with checks
    - Suggested oral/viva questions to verify understanding
    - A short academic integrity statement to require at submission

    Return: Modified brief + evidence checklist + timeline + sample viva questions

Exercise: Make your assessment AI-resilient

Your task: Use the AI-Resilience Design Prompt above to create a revised brief and paste it below.

Iterative Enhancement Principles

This example demonstrates how to progressively enhance an assessment through multiple iterations:

  1. First iteration: Add basic engagement elements (authentic context, collaboration, process)
  2. Second iteration: Address accessibility and inclusion needs
  3. Third iteration: Refine for specific disciplinary context and academic standards

Each iteration builds on the previous improvements while maintaining the core learning outcomes.

Transformation Principles

  1. Authentic context: Position students as professionals solving real problems - consultants, practitioners, researchers, etc.
  2. Meaningful collaboration: Design roles that require genuine interdependence (different expertise areas, perspectives, or tasks)
  3. Process visibility: Make thinking visible through documentation that shows decision-making, iteration, and integration
  4. Equivalent challenge: Ensure the core skills and knowledge remain the same, maintaining academic rigor

Quick Transformation Checklist

  • ✅ Is there a clear authentic/real-world context?
  • ✅ Is there a well-defined collaborative component?
  • ✅ Is process documentation incorporated?
  • ✅ Are the original learning outcomes still addressed?
  • ✅ Is the workload equivalent to the original?

Accessibility Considerations

When transforming assessments, build accessibility in from the start:

Assessment Accessibility Prompt:

Review this assessment brief for accessibility barriers and inclusive design:

[PASTE ASSESSMENT BRIEF]

Provide specific recommendations to improve:
1. Alternative formats and submission options
2. Flexibility in group work arrangements
3. Clear, plain language instructions
4. Inclusive examples and contexts
5. Reasonable adjustments that maintain academic standards

Return: Specific rewording suggestions and implementation guidance.
Assessment Transformation Resources
  • Real-world stakeholders: Alumni networks, community organizations, university departments, local government
  • Collaborative structures: Jigsaw method, research teams, peer review pairs, student-led seminars
  • Process documentation: Research logs, design journals, decision matrices, reflective blogs, annotated bibliographies
  • Inclusive practices: Multiple modes of participation, choice in topics/formats, staged submission points