Learning Experiences & Instruction
Now that you have your goals and assessments, it's time to design the learning experiences that will help students succeed. This is UbD Stage 3!
Learning Outcomes
By the end of this module, you will be able to:
- ✓ Develop a course topic sequence that connects your outcomes and assessments to specific content
- ✓ Apply the WHERETO and BOPPPS frameworks to plan effective learning sequences
- ✓ Compare WHERETO (unit planning) vs. BOPPPS (lesson planning) and choose appropriately
- ✓ Use AI to generate diverse learning activities aligned with your outcomes
- ✓ Design a complete lesson plan or module using AI assistance
- ✓ Select appropriate instructional strategies for different learning goals
- ✓ Create classroom activities where students engage directly with AI as a learning tool
Dexi Says:
This is where your course really comes to life! We'll use AI to brainstorm tons of creative activity ideas, then you'll pick the ones that fit your students best.
Developing Your Course Topic Sequence
Before designing individual activities and lessons, you need a concrete topic sequence—a structured map of what you'll teach, organized by week or unit. Without this, activity planning is built on an unstable foundation.
Your topic sequence bridges the gap between the "what" (learning outcomes and assessments from Modules 2–3) and the "how" (activities and lessons you'll design in the sections that follow). It answers the question: "In what order will I teach the content students need?"
What a Good Topic Sequence Includes
Topics by Week/Unit
A clear list of what content is covered each week or unit, organized in a logical teaching order.
Outcome Connections
Each topic should connect to one or more of your learning outcomes. If a topic doesn't serve an outcome, reconsider whether it belongs.
Assessment Placement
Where your major assessments fall in the schedule, so activities build toward them at the right time.
Think Sequence, Not Coverage
A common course design mistake is trying to "cover" everything. Your topic sequence should focus on the content students need to achieve your learning outcomes and succeed on your assessments—not everything you could possibly teach.
Build Your Topic Sequence
Generate Your Course Topic Sequence
Return to DesignLab After Each AI Interaction
When you copy a prompt and paste it into your AI tool, remember to come back here afterward! Copy the AI's response, return to this page, and continue with the next step. AI chatbots can easily lead you down rabbit holes—DesignLab keeps your design process structured and focused.
Step 1: Reflect
Before using AI, draft a rough topic list on your own. You know your discipline best:
• What are the major topics or units in your course?
• What order makes sense pedagogically (e.g., foundational concepts first)?
• Where do your major assessments need to fall?
Even a rough outline gives you a strong baseline for evaluating the AI's suggestions.
Step 2: Rough Draft
Write down your ideas in rough form—even a few bullet points or a quick sketch. Having your own draft gives you a clear baseline for comparing and evaluating the AI’s output.
Now use this prompt to have AI help you build a structured topic sequence:
Help me develop a course topic sequence for my course. Course: [Course name] Course description: [Paste your course description] Duration: [e.g., 15 weeks, 10 modules] Learning outcomes: [Paste your learning outcomes from Module 2] Major assessments: [Paste your assessment descriptions from Module 3] Please generate a week-by-week (or unit-by-unit) topic sequence that: 1. Lists the main topic(s) for each week/unit 2. Notes which learning outcome(s) each topic supports 3. Indicates where major assessments fall in the schedule 4. Sequences topics so foundational concepts come before advanced ones 5. Includes built-in review or synthesis weeks where appropriate Format as a structured table or list I can use as a course map.
Step 4: Critically Evaluate
Compare the AI's topic sequence with your own draft. Ask yourself:
• Does the order make sense for how your discipline is actually taught?
• Are there prerequisite relationships the AI missed or got wrong?
• Is the pacing realistic for your students and course format?
• Does every topic serve at least one learning outcome?
Revise until the sequence feels right for your course. You'll use this topic list throughout the rest of this module and in Module 5.
Dexi Says:
Your topic sequence is like a roadmap for the rest of your course design. Keep it handy—you'll reference it when designing activities, building lesson plans, and generating your syllabus in Module 5!
Lesson Planning Frameworks
This section introduces two powerful frameworks for planning instruction. WHERETO ↗ from UbD helps design comprehensive learning experiences, while BOPPPS provides a structured approach for individual lessons.
The WHERETO Framework
UbD provides a helpful acronym for planning learning experiences: WHERETO. Each letter represents an important element of effective instruction.
Where & Why
Help students understand WHERE they're going (goals) and WHY it matters.
Hook & Hold
HOOK student interest early and HOLD their attention throughout.
Equip & Experience
EQUIP students with knowledge and provide EXPERIENCES to explore ideas.
Rethink & Revise
Give opportunities to RETHINK ideas and REVISE their work.
Evaluate
Allow students to EVALUATE their own learning and progress.
Tailor & Personalize
TAILOR learning to different needs, interests, and abilities.
Organize
ORGANIZE the sequence for maximum engagement and understanding.
Pro Tip: Start with the Hook
A great hook can make or break a lesson. Consider: provocative questions, surprising facts, real-world problems, personal relevance, or compelling stories.
AI Prompt: Generate WHERETO-Aligned Activities
Step 1: Reflect
Before using AI, choose a topic from your course topic sequence (Section 2) and sketch out your own ideas for at least 2–3 WHERETO elements. How would you hook students into this topic? What activities come to mind? Having your own starting ideas will help you evaluate AI suggestions.
Step 2: Rough Draft
Write down your ideas in rough form—even a few bullet points or a quick sketch. Having your own draft gives you a clear baseline for comparing and evaluating the AI’s output.
I need help designing learning activities using the WHERETO framework from Understanding by Design. Course: [Your course name] Topic/Module: [Choose a specific topic or unit from your course topic sequence (Section 2)] Learning Outcome: [The specific outcome students should achieve] Class Format: [In-person, online, hybrid] Time Available: [e.g., 75-minute class session] Please suggest activities for each element of WHERETO: W - WHERE/WHY: How can I help students understand where we're going and why it matters? H - HOOK: What engaging opener would capture student interest? E - EQUIP/EXPERIENCE: What activities will build knowledge and allow exploration? R - RETHINK/REVISE: How can students revisit and refine their understanding? E - EVALUATE: How can students self-assess their learning? T - TAILOR: How can I differentiate for different learners? Consider Universal Design for Learning: multiple means of engagement (why), representation (what), and action/expression (how). O - ORGANIZE: What's the best sequence for these activities? Please provide 2-3 options for each element so I can choose what fits my context.
Step 4: Critically Evaluate
Compare the AI's suggestions with your own ideas. Are the proposed activities realistic for your class size and format? Do they fit your students' abilities and interests? Would these activities genuinely promote understanding, or are they just "busy work"? Select and adapt the best ideas.
🔄 Alternative Framework: BOPPPS
While WHERETO is comprehensive for unit planning, BOPPPS is a focused framework specifically designed for individual lesson planning. Developed at the University of British Columbia, it provides a structured approach to creating engaging, effective lessons.
You can use either framework (or both!) depending on your needs—WHERETO for broader unit design, BOPPPS for detailed lesson structure.
Bridge-In
Capture attention and connect to prior knowledge. Hook learners with a question, story, or relevant scenario.
Objectives
Clearly state what learners will be able to do by the end. Make learning outcomes specific and measurable.
Pre-Assessment
Check what learners already know. Use quick polls, questions, or brief activities to gauge starting points.
Participatory Learning
Engage learners in active learning. Include discussions, practice, problem-solving, and hands-on activities.
Post-Assessment
Verify learning occurred. Check if learning outcomes were met through quizzes, demonstrations, or applications.
Summary
Wrap up and look ahead. Reinforce key points, answer questions, and preview what comes next.
How AI Can Assist with BOPPPS
AI can help you generate creative bridge-in hooks, write clear measurable learning outcomes, create pre/post assessment questions, suggest participatory activities for your specific content, and draft effective summaries.
BOPPPS Is a Fractal Framework
While BOPPPS is most commonly used for individual lessons, the same structure can be applied at any scale—a single activity, a multi-week unit, or an entire course. Think of it as a repeating pattern:
At the course level: Your first class session is the Bridge-In (engaging students with the subject); the syllabus review covers Objectives; a diagnostic assignment serves as Pre-Assessment; the bulk of the semester is Participatory Learning; final exams or projects are the Post-Assessment; and a wrap-up or reflection session is the Summary.
Recognizing this pattern can help you design coherent learning experiences at every level—from a 10-minute activity up to a full-semester course.
AI Prompt: Generate BOPPPS Lesson Plan
Step 1: Reflect
Before using AI, outline your lesson basics: What are your 2–3 learning outcomes for this lesson? What's one engaging way you could open the lesson? What's the most important activity students should do? Your outline gives AI better context and gives you a benchmark for evaluation.
Step 2: Rough Draft
Write down your ideas in rough form—even a few bullet points or a quick sketch. Having your own draft gives you a clear baseline for comparing and evaluating the AI’s output.
Help me design a lesson using the BOPPPS framework. Course: [Your course name] Topic: [Choose a specific lesson topic from your course topic sequence] Duration: [e.g., 50 minutes, 75 minutes] Learning Outcome: [What students should be able to do] Class Size: [Number of students] Format: [In-person / Online / Hybrid] Please create a detailed lesson plan following BOPPPS: B - Bridge-In (2-5 min): - Engaging hook to capture attention - Connection to prior knowledge or real-world relevance O - Objectives (1-2 min): - Clear, measurable learning outcomes for this lesson (2-3 max) - How you'll share these with students P - Pre-Assessment (3-5 min): - Quick activity to gauge prior knowledge - How you'll use this information P - Participatory Learning (majority of class time): - Active learning activities - Mix of individual, pair, and group work - Include timing for each activity - Offer multiple means of engagement, representation, and expression (UDL) so all learners can participate meaningfully P - Post-Assessment (5-10 min): - How you'll verify learning occurred - Connection back to learning outcomes S - Summary (3-5 min): - Key takeaways to reinforce - Preview of next lesson - Any assignments or follow-up Please include specific timing and transitions between sections.
Step 4: Critically Evaluate
Review the AI-generated lesson plan against your outline. Are the timings realistic? Do the activities match how your students actually learn? Does the bridge-in genuinely connect to student interests, or is it generic? Revise to fit your classroom reality.
📊 WHERETO vs. BOPPPS: Quick Comparison
Both frameworks help you design effective instruction, but they serve different purposes. Use this comparison to choose the right one for your needs.
| Aspect | WHERETO | BOPPPS |
|---|---|---|
| Best For | Unit/module planning, course-level design | Individual lesson planning, class sessions |
| Origin | Understanding by Design (McTighe & Wiggins) | Instructional Skills Workshop (UBC) |
| Focus | Comprehensive learning experience design | Structured lesson delivery |
| Time Scope | Multiple class sessions, entire units | Single class session (50-90 min typical) |
| Key Strength | Ensures alignment with big-picture goals | Provides clear lesson structure and pacing |
| Differentiation | Built-in (T = Tailor) | Can be added within Participatory Learning |
| Assessment | Embedded throughout + self-evaluation | Pre-assessment and post-assessment built in |
| AI Assistance | Generate activities for each WHERETO element, suggest differentiation strategies, create assessment ideas | Generate hooks, write learning outcomes, create pre/post assessments, suggest participatory activities |
Pro Tip: Use Both Together!
Many educators use WHERETO for overall unit design and then BOPPPS for individual lesson plans within that unit. This gives you both the big-picture alignment and the detailed lesson structure.
Designing Engaging Activities
Different learning outcomes require different types of activities. Use this guide to select activity types that match what you want students to learn.
Activity Types by Learning Goal
💡 Hover or tap each card to see examples and descriptions
💭 Think-Pair-Share Examples
- Pose a question, give 2 min to think individually
- Pair students to discuss for 3-5 min
- Share key insights with the whole class
Best for: Activating prior knowledge, checking understanding, generating diverse perspectives
🔬 Case Study Examples
- Real-world business dilemmas
- Historical decision points
- Patient scenarios in healthcare
- Engineering failure analyses
Best for: Contextual application, decision-making skills, connecting theory to practice
🎭 Role Play Examples
- Simulated client consultations
- Historical figure debates
- Stakeholder negotiations
- Patient-provider interactions
Best for: Empathy building, communication skills, experiencing multiple viewpoints
🧩 Jigsaw Process
- Divide content into expert sections
- Students become experts in one section
- Regroup to teach each other
- Complete synthesis activity together
Best for: Large content coverage, peer teaching, interdependence
🎯 Problem-Based Learning
- Present ill-structured, authentic problems
- Students identify what they need to learn
- Research and collaborate on solutions
- Present and defend approaches
Best for: Self-directed learning, research skills, complex problem solving
✍️ Reflective Writing Types
- Learning journals or blogs
- Minute papers (muddiest point)
- Before/after belief statements
- Application letters to future self
Best for: Metacognition, processing experiences, connecting to personal meaning
🗣️ Debate Formats
- Formal structured debates
- Fishbowl discussions
- Four corners (agree/disagree)
- Socratic seminars
Best for: Critical thinking, evidence evaluation, constructing arguments
🛠️ Hands-On Examples
- Lab experiments and simulations
- Coding exercises with feedback
- Studio/workshop practice
- Procedural skill stations
Best for: Motor skills, procedural fluency, immediate application and feedback
Generate Activity Ideas with AI
Step 1: Reflect
Choose one learning outcome from your Module 2 work and a topic from your course topic sequence. Before using AI, brainstorm 3–5 activities you already know work well for this type of learning. What has engaged students in the past? What formats suit your teaching context?
-
Choose a learning outcome
Select one learning outcome from your Module 2 work that you want to design activities for.
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Use the AI prompt below
Copy the prompt and customize it with your specific outcome and context.
-
Critically evaluate and select
Compare AI suggestions with your own ideas. Choose 3-5 activities that would work best for your students and teaching style.
Step 2: Rough Draft
Write down your ideas in rough form—even a few bullet points or a quick sketch. Having your own draft gives you a clear baseline for comparing and evaluating the AI’s output.
Generate 10 diverse learning activity ideas for my course. Learning Outcome: [Paste your learning outcome] Student Level: [Introductory/Intermediate/Advanced] Class Size: [Small (under 20) / Medium (20-50) / Large (50+)] Format: [In-person / Online synchronous / Online asynchronous / Hybrid] Time per activity: [5-15 min / 15-30 min / 30-60 min / Extended project] For each activity, please provide: 1. Activity name 2. Brief description (2-3 sentences) 3. What makes it engaging 4. How it connects to the learning outcome 5. Any materials or prep needed Include a mix of: - Individual and group activities - Low-tech and tech-enhanced options - Active and reflective tasks - Formative assessment opportunities - Activities accessible through multiple means of engagement, representation, and expression (UDL principles)
Step 4: Critically Evaluate
Compare the AI's activity ideas with your own. Which suggestions are genuinely creative and feasible? Which ones wouldn't work in your specific context? Combine the best AI ideas with your own experience to build a strong activity repertoire for this outcome.
Discipline-Specific Activities
Want activities tailored to your field? Check the Prompt Library for discipline-specific prompts for STEM, humanities, business, arts, and health fields.
Building a Complete Lesson Plan
Now let's put it all together. A well-designed lesson plan sequences activities purposefully, manages time effectively, and includes transitions and checks for understanding.
📋 Sample Lesson Structure (75 min)
AI Prompt: Generate a Complete Lesson Plan
Step 1: Reflect
Before using AI, draft a rough lesson outline: What are your learning outcomes for this lesson? What's the main activity? How will you know if students learned? Even a quick sketch helps you evaluate the AI's lesson plan against your teaching instincts.
Step 2: Rough Draft
Write down your ideas in rough form—even a few bullet points or a quick sketch. Having your own draft gives you a clear baseline for comparing and evaluating the AI’s output.
Create a detailed lesson plan for my course. Course: [Course name] Topic: [Choose a specific topic from your course topic sequence] Learning Outcome: [What students should be able to do after this lesson] Prior Knowledge: [What students already know] Class Duration: [e.g., 50 minutes, 75 minutes, 3 hours] Class Size: [Number of students] Format: [In-person / Online / Hybrid] Please create a lesson plan that includes: 1. **Learning outcomes** (2-3 specific, measurable outcomes for this lesson) 2. **Materials needed** (handouts, tech, supplies) 3. **Detailed timeline** with: - Activity name - Duration - Description of what happens - Instructor actions - Student actions - Transitions 4. **Assessment strategy** (how you'll check for understanding) 5. **Differentiation options** (applying UDL principles: multiple means of engagement, representation, and action/expression for diverse learners) 6. **Contingency plans** (if activities run short/long) Use the WHERETO framework to ensure engaging, effective instruction.
Step 4: Critically Evaluate
Compare the AI's lesson plan with your rough outline. Are the timings realistic for your class? Do the activities build logically? Would this plan actually work in your room with your students? Adjust timings, swap activities, and add your own transitions. Remember: AI-generated timings are estimates—always build in buffer time.
Student AI Activities in the Classroom
Beyond using AI to design your course, you can create powerful learning experiences where students engage directly with AI in the classroom. These activities help students develop AI literacy while deepening their understanding of course content.
Why Student-AI Activities?
Students need to learn how to work with AI effectively—it's a critical skill for their future careers. Classroom activities that incorporate AI teach students to prompt effectively, evaluate AI outputs critically, and understand both the capabilities and limitations of these tools.
Types of Student-AI Classroom Activities
AI as Tutor
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AI as Tutor
Students use AI to get explanations, work through problems, and receive personalized feedback on their understanding.
Best for: Concept clarification, practice problems, explaining errors
AI as Role-Play Partner
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AI as Role-Play Partner
AI takes on roles (patient, client, historical figure, stakeholder) for students to practice skills in realistic scenarios.
Best for: Communication skills, interviews, negotiations, difficult conversations
AI as Thought Partner
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AI as Thought Partner
Students brainstorm ideas, explore perspectives, and stress-test arguments through dialogue with AI.
Best for: Creative projects, argument development, exploring multiple viewpoints
AI as Subject for Analysis
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AI as Subject for Analysis
Students critically analyze AI outputs, identify errors, biases, and limitations as a learning exercise.
Best for: Critical thinking, media literacy, fact-checking, bias detection
AI as Writing Assistant
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AI as Writing Assistant
Students use AI to improve drafts, get feedback, or overcome writer's block while maintaining ownership of their work.
Best for: Writing workshops, revision practice, peer editing prep
AI as Quiz Generator
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AI as Quiz Generator
Students prompt AI to create practice questions about the material, then answer them—teaching through question creation.
Best for: Exam prep, self-assessment, metacognition about what's important
AI as Study Buddy
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AI as Study Buddy
Students use AI as a personalized study partner—asking it to explain concepts in different ways, quiz them on material, summarize readings, or help them create study guides and flashcards.
Best for: Exam preparation, concept review, self-directed learning, filling knowledge gaps
AI as Research Assistant
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AI as Research Assistant
Students use AI to brainstorm search terms, generate research questions, organize sources into themes, or summarize literature—then verify and refine using actual databases.
Best for: Literature reviews, research proposals, annotated bibliographies, identifying gaps in knowledge
AI as Peer Reviewer
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AI as Peer Reviewer
Students submit drafts to AI for preliminary feedback on structure, argument clarity, or evidence use before human peer review—building revision skills and reducing first-draft anxiety.
Best for: Writing workshops, revision practice, self-editing, preparing for peer review
AI as Data Analyst
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AI as Data Analyst
Students use AI to help interpret datasets, explain statistical output in plain language, suggest visualization approaches, or troubleshoot code—while maintaining responsibility for analytical decisions.
Best for: Data interpretation, statistical reasoning, research methods courses, coding-based analysis
Explore More Student-AI Activity Ideas
Looking for expanded examples and implementation guides? These external resources offer additional inspiration for integrating AI into student learning experiences:
- Harvard Business School Publishing — Student Use Cases for AI
- One Useful Thing (Ethan Mollick) — Practical AI in Education
Note: External links may change over time. If a link doesn't work, try searching for the resource by name.
Detailed Activity Examples
Guided Problem-Solving with AI
Description: Students work through practice problems by asking AI for hints (not answers) when stuck. They must explain their reasoning to the AI and ask follow-up questions until they understand.
Time: 20-30 minutes
Setup: Provide students with a set of problems. Instruct them to use AI as a tutor—asking for hints, explanations of concepts, or feedback on their approach, but NOT asking AI to solve the problem for them.
Learning Focus: Students learn to formulate good questions, identify where they're confused, and develop metacognitive awareness.
Practice Difficult Conversations
Description: Students practice challenging professional conversations by having AI play a specific role (difficult patient, unhappy customer, resistant stakeholder).
Time: 15-25 minutes per scenario
Setup: Give students a scenario and a prompt to set up the AI's role. Students conduct the conversation, then reflect on what strategies worked.
Learning Focus: Communication skills, empathy, handling difficult situations in a low-stakes environment.
AI Fact-Checking Challenge
Description: Give students AI-generated content about a topic they've studied. Their task is to identify errors, verify claims, and produce a corrected version with citations.
Time: 30-45 minutes
Setup: Pre-generate content using AI that intentionally (or naturally) contains some errors. Students must find and fix them using course materials and reliable sources.
Learning Focus: Critical evaluation, research skills, deep engagement with content to identify what's accurate vs. inaccurate.
Devil's Advocate Debate Prep
Description: Students prepare arguments for a position by having AI argue against them. AI plays devil's advocate, challenging students' reasoning and helping them anticipate counterarguments.
Time: 20-30 minutes
Setup: Students state their position to AI and ask it to challenge their reasoning, find weaknesses, and present opposing viewpoints.
Learning Focus: Argument development, anticipating counterarguments, strengthening critical thinking.
Design Your Own Student-AI Activity
Help me design a classroom activity where students engage directly with AI. Course: [Course name] Topic: [Specific topic or skill] Learning Outcome: [What students should learn or practice] Class Size: [Number of students] Time Available: [Duration] AI Role: [Tutor/Role-play partner/Thought partner/Subject for analysis/Writing assistant/Quiz generator] Please provide: 1. Activity Overview - What students will do - How AI is incorporated - Expected outcomes 2. Student Instructions - Step-by-step process - Sample prompts students can use or adapt - What to do if they get stuck 3. Facilitation Guide - How to introduce the activity - What to monitor during the activity - Common issues and solutions 4. Debrief Questions - Reflection prompts for after the activity - What to discuss as a class 5. Assessment Criteria (if applicable) - What demonstrates successful engagement - How to evaluate student work
Create a role-play scenario where AI acts as a character for student practice. Context: [e.g., Healthcare, Business, Education, Social Work] Skill Being Practiced: [e.g., Motivational interviewing, customer service, parent conference] Difficulty Level: [Easy/Moderate/Challenging] Please create: 1. Character Profile for AI - Name, background, situation - Personality traits and communication style - Hidden concerns or motivations - How cooperative/resistant they should be 2. Scenario Setup - Context students receive - Their role and goals - What information they have/don't have 3. Student Prompt to Give AI - Ready-to-copy prompt that sets up the AI's role - Instructions for AI behavior 4. Success Criteria - What good handling looks like - Red flags or mistakes to avoid 5. Debrief Questions - Reflection on what worked - What they'd do differently
Create an activity where students critically analyze AI-generated content. Topic: [Subject matter students have studied] Analysis Focus: [Accuracy/Bias/Completeness/Logic/Sources] Student Level: [Introductory/Intermediate/Advanced] Please provide: 1. AI-Generated Content - Create a passage about the topic - Include 3-5 subtle errors, oversimplifications, or biases - Make some content accurate so students must discriminate 2. Student Instructions - What to look for - How to verify claims - Required deliverable (annotated document, correction report, etc.) 3. Answer Key - List of intentional issues - Explanation of why each is problematic - Corrected versions 4. Discussion Guide - Why AI makes these kinds of errors - Implications for using AI in their field - Strategies for critical AI use
Implementation Tips
- Start with a brief demo showing students how to interact with AI effectively
- Provide sample prompts students can adapt—don't assume they know how to prompt well
- Build in time for whole-class debrief to share insights and address questions
- Have a backup plan for technical issues (partner work, pre-generated outputs)
- Consider equity—not all students may have equal access to AI tools outside class
Dexi Says:
The magic happens in the debrief! After any student-AI activity, make time for reflection. Ask: "What surprised you? What did AI do well or poorly? How might you use AI differently next time?" These metacognitive conversations are where deep learning happens.
👩🏫 Exemplar Spotlight: Stage 3 in Action
Here's how Dr. Sarah Chen and Prof. Marcus Rivera planned their learning activities and lesson structures. Notice how every activity connects back to their assessments and learning outcomes.
Dr. Sarah Chen — Learning Experiences & Lesson Planning
Topic Sequence Decision: Sarah organized her 13 weeks around increasingly complex patient scenarios rather than body systems (the traditional approach). She starts with straightforward single-diagnosis patients and builds toward multi-morbidity cases with psychosocial complications—mirroring the complexity of her final performance task.
Key Activity — Clinical Reasoning Rounds (Weeks 4–12): Each week, students work through a brief patient vignette in small groups using a structured BOPPPS format. The Bridge-In presents a realistic clinical scenario; the Pre-Assessment asks students to identify what they already know about the condition; the Participatory Learning involves collaborative assessment planning and care prioritization; the Post-Assessment is a written clinical reasoning snapshot. Sarah uses the WHERETO principle of "Rethink and Revise" by having students revisit earlier cases later in the semester with new knowledge.
Student AI Activity: In Week 8, students use AI as a "patient simulator"—prompting it to role-play a patient with specific symptoms while they practice history-taking questions. They then critique the AI's portrayal: Was it realistic? What did it miss about the patient experience?
What Sarah Changed: AI suggested a sequence of traditional lectures followed by lab practice. Sarah restructured to interleave theory and practice from Module 1, because her students learn clinical reasoning by doing it—not by memorizing first and applying later. She also rejected AI's suggestion for a weekly multiple-choice quiz, replacing it with the clinical reasoning journals that scaffold toward the performance task.
Prof. Marcus Rivera — Learning Experiences & Lesson Planning
Topic Sequence Decision: Marcus organized his course in three arcs: (1) Frameworks for Understanding Inequality (Weeks 1–4), (2) Domains of Inequality in Practice (Weeks 5–9), and (3) From Analysis to Action (Weeks 10–13). The third arc directly scaffolds toward the community policy brief performance task.
Key Activity — Theory Application Seminars (Weeks 5–9): Each week focuses on a specific domain (housing, education, health, labor, criminal justice). Students read a primary scholarly source and a community-level data report, then discuss in structured seminars. The BOPPPS Bridge-In uses a short documentary clip or local news story. Students practice applying theoretical frameworks in low-stakes weekly discussion posts, building the analytical skills they'll need for the policy brief.
Student AI Activity: In Week 7, Marcus assigns an "AI Fact-Checking Challenge." Students prompt AI to explain the causes of a specific form of inequality, then fact-check the response against course readings. They submit a 500-word critique identifying what AI got right, what it oversimplified, and what structural factors it missed entirely.
What Marcus Changed: AI proposed a lecture-heavy sequence with case studies as homework. Marcus shifted to seminar-based learning because his course goals emphasize discussion, perspective-taking, and argument construction—skills that develop through dialogue, not passive listening. He kept AI's suggestion for scaffolded annotated bibliography deadlines (Weeks 6, 9, 11) because the progressive structure genuinely helps students build toward the final brief.
Module 4 Reflection
You've now designed learning experiences aligned with your outcomes and assessments. Take a moment to reflect on your progress.
Your Reflection
📖 Further Reading for This Module
Want to go deeper into the frameworks and concepts introduced this module? These scholarly sources provide the foundation for the ideas in this module.
Wiggins, G. P., & McTighe, J. (2005). Understanding by design. Ascd.
🎉 Module 4 Complete!
Fantastic work! You've designed engaging learning experiences using the WHERETO and BOPPPS frameworks with AI assistance.
Coming up in Module 5: We'll bring everything together into a complete course package, generate your syllabus, and walk away with reusable tools you can return to anytime.