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Dt Curriculum

MicrosoftOfficialPublished by Microsoft

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From the author

Design Thinking learning curriculum covering nine progressive modules across the full Problem, Solution, and Implementation Space methods plus a shared manufacturing reference scenario for teaching and practice
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The DT Curriculum is a structured educational framework designed to guide learners through the full Design Thinking lifecycle, spanning the Problem, Solution, and Implementation spaces. It provides nine distinct modules that cover essential methods from initial scoping and research to prototyping, testing, and final handoff. To ensure consistent application of these concepts, the curriculum integrates a shared manufacturing reference scenario, allowing learners to apply theoretical knowledge to a realistic, evolving context throughout their training.

What it does

  • Provides nine progressive modules covering the complete Design Thinking methodology.
  • Uses a shared manufacturing reference scenario to maintain context across all learning modules.
  • Teaches core techniques like stakeholder mapping, contextual inquiry, and frozen request unfreezing.
  • Includes comprehension checks and practice exercises for each design method.
  • Structures learning from the Problem Space through to the Implementation Space.
  • Offers specific guidance on moving from stakeholder assumptions to user-validated reality.

When to use it

  • When teaching or learning the end-to-end Design Thinking process.
  • When you need a structured curriculum to train teams on problem-space scoping and solution-space design.
  • When you want to use a consistent, realistic manufacturing scenario to practice design methods.
  • When you need to bridge the gap between stakeholder requests and actual user needs.
  • When you are preparing for design research, prototyping, or user testing phases.

Advantages

  • Progressive structure ensures learners build skills logically from problem to implementation.
  • Shared scenario provides a consistent baseline for comparing different design methods.
  • Focuses on practical techniques like unfreezing requests and conducting contextual inquiry.
  • Encourages discipline in staying within the problem space before jumping to solutions.
  • Includes built-in assessment tools like comprehension checks and exercises.

Usage examples

“I am starting Module 1 of the Design Thinking curriculum. Can you load the scoping module and the manufacturing scenario?”
The agent loads the scoping module and the manufacturing scenario, then presents the first comprehension check regarding frozen versus fluid requests.
“I need to practice unfreezing a request. Use the manufacturing scenario to give me an exercise.”
The agent provides a specific request from the manufacturing scenario and asks the user to write three progressive questions to uncover the underlying problem.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/microsoft/dt-curriculum/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip dt-curriculum.zip -d .agents/skills

Documentation by Microsoft

DT Curriculum — Skill Entry

This SKILL.md is the entrypoint for the Design Thinking learning curriculum.

The dt-learning-tutor agent loads this skill to teach Design Thinking concepts, run comprehension checks, and assign practice exercises. The curriculum spans nine progressive modules — one per Design Thinking method — and a shared manufacturing reference scenario that threads through every module so learners build on consistent context as they advance from the Problem Space to the Implementation Space.

Curriculum references

Load the module that matches the method the learner is studying. Load the manufacturing scenario alongside any module that uses scenario-based checks or exercises.

ReferenceWhen to load
curriculum-01-scoping.mdTeaching Method 1: Scope Conversations (Problem Space).
curriculum-02-research.mdTeaching Method 2: Design Research (Problem Space).
curriculum-03-synthesis.mdTeaching Method 3: Synthesis (Problem Space).
curriculum-04-brainstorming.mdTeaching Method 4: Brainstorming (Solution Space).
curriculum-05-concepts.mdTeaching Method 5: User Concepts (Solution Space).
curriculum-06-prototypes.mdTeaching Method 6: Low-Fidelity Prototypes (Solution Space).
curriculum-07-testing.mdTeaching Method 7: High-Fidelity Prototypes (Implementation Space).
curriculum-08-iteration.mdTeaching Method 8: User Testing (Implementation Space).
curriculum-09-handoff.mdTeaching Method 9: Iteration at Scale (Implementation Space).
curriculum-scenario-manufacturing.mdAlongside any module using scenario-based comprehension checks or practice exercises.

Skill layout

  • SKILL.md — this file (skill entrypoint).

  • references/ — the DT curriculum knowledge documents.

    • curriculum-01-scoping.md through curriculum-09-handoff.md — one module per Design Thinking method.

    • curriculum-scenario-manufacturing.md — shared factory-floor reference scenario used across all nine modules.

Files

references/curriculum-scenario-manufacturing.md


title: Manufacturing Reference Learning Scenario description: DT curriculum manufacturing reference scenario with stakeholders, interview excerpts, observation data, and test results for module exercises.

Scenario Overview

Meridian Components is a mid-size manufacturer producing precision metal parts across three shifts. The plant uses mixed automation and manual processes with 120 operators, 12 shift supervisors, 4 quality engineers, and a plant manager.

Problem signal: First-pass yield on the night shift runs 12% below day shift. Defect rates triggered two customer escalations in the past quarter. The plant manager's initial request is "build a quality dashboard."

Stakeholders: Line operators (hands-on process), shift supervisors (floor oversight), quality engineers (defect analysis), maintenance engineers (equipment calibration), safety officer (PPE and procedure compliance), plant manager (production targets), union representative (labor agreements), temporary workers (seasonal staffing).

Complexity dimensions: Technical (equipment calibration drift, sensor data gaps), human (training inconsistency, fatigue patterns, informal workaround culture), organizational (shift handoff information loss, day-shift management bias), external (customer delivery expectations, regulatory compliance).

Scenario Progression

The scenario flows through all 9 methods. Each module builds on previous outputs.

Methods 1-3: Problem Space

Scoping reveals "build a quality dashboard" is a frozen request masking information asymmetry between shifts. Research through Gemba walks, operator shadows, and shift handoff observations uncovers that night-shift operators lack the informal knowledge transfer, rapid-response support, and management oversight day shifts enjoy. Workers spend 10-15 minutes finding correct manual sections while actual repairs take 5-10 minutes. Synthesis of interview and observation data produces a core theme: operators need immediate access to contextual repair knowledge without leaving their station.

Methods 4-6: Solution Space

Brainstorming against three constraints (85-90 dB noise, greasy hands, limited floor space) generates four solution themes: hands-free interaction, visual guidance, collaborative knowledge sharing, and proactive assistance. Concept development focuses on a voice-guided repair system with glove-friendly fallback controls. Lo-fi prototyping reveals touchscreen contamination, QR code lighting failures, and production-timing conflicts — constraints invisible from a desk.

Methods 7-9: Implementation Space

Hi-fi prototyping compares three microphone options (industrial-grade array, bone-conduction headset, directional lapel mic) in 85-90 dB environments and validates glove-friendly interfaces. Testing across four operator types shows 40% higher adoption with glove-friendly design. Shift-change periods generate 5x normal query volume. Emergency stop procedures are used 300% above forecast, revealing safety as the highest-value use case. Handoff documentation packages the validated solution with telemetry showing new hires use the system 3x more frequently than experienced operators.

Interview Excerpts

Present these fictional excerpts during research and synthesis exercises.

Night-shift operator A: "When something goes wrong at 2 AM, I radio the supervisor, but they're covering three lines. By the time they get to me, I've already tried two things from memory. Sometimes I fix it, sometimes I make it worse."

Night-shift operator B: "The manual is in the break room. I'm not walking 200 feet to look something up while my line is down. Carlos on day shift just asks Mike — Mike's been here 22 years and knows everything."

Night-shift operator C: "New people follow the book step by step, which is fine for normal stuff. But when the machine does something weird, the book doesn't cover it. We used to have Gloria on nights who knew every trick. She retired in March."

Day-shift operator: "When I get stuck, I tap the person next to me or call over to the senior operator. Usually sorted in two minutes. I heard night shift doesn't have that — their experienced people retired last year."

Shift supervisor: "I can see my quality numbers tanking after midnight, but I'm stretched across three production lines. The operators aren't doing anything wrong — they just don't have backup when something unusual happens."

Quality engineer: "Calibration drift accounts for maybe 30% of the defect variance. The rest is procedural — the same repair done three different ways depending on who's working. Day shift has more consistent execution because they can ask each other."

Maintenance engineer: "Equipment alerts fire constantly — most are false positives from old sensor thresholds. Operators learn to ignore them. The real problems get caught by operators noticing vibration changes or unusual sounds, not by sensor data."

Safety officer: "Emergency procedures are documented, but under pressure operators revert to whatever they practiced most recently. If the documented procedure isn't the one they rehearse, they'll improvise. That's where incidents happen."

Observation Data Points

Use these for Module 3 affinity clustering exercises.

  1. Night-shift operators take 10-15 minutes to locate correct manual sections

  2. Day-shift operators resolve issues by asking experienced colleagues

  3. Senior operator retirements removed institutional knowledge from night shift

  4. Supervisors cover three lines simultaneously during off-hours

  5. Repair procedures vary by operator — same fix done three different ways

  6. Equipment alerts produce frequent false positives from outdated thresholds

  7. Operators detect problems through vibration and sound before sensors trigger

  8. Break room manual location creates 200-foot round trip from production line

  9. Calibration drift accounts for approximately 30% of defect variance

  10. Remaining 70% of variance is procedural and knowledge-based

  11. Day-shift knowledge transfer happens informally through proximity

  12. Night-shift radio communication is delayed by supervisor coverage gaps

  13. Experienced operators develop personal repair shortcuts not documented in SOPs

  14. New hires follow SOPs strictly but lack context for unusual situations

  15. Shift handoff logs capture machine status but not in-progress troubleshooting

  16. Greasy hands prevent touchscreen interaction on the production floor

  17. Noise at 85-90 dB prevents normal voice conversation

  18. Temporary workers are excluded from informal knowledge networks

  19. Emergency procedures are accessed more than routine features during pilot testing

  20. Shift-change periods generate concentrated information-seeking spikes

Test Results

Use these fictional results for Module 7-9 exercises.

TestScenarioResultNotes
T1Voice command accuracy at 85 dB, industrial array micPass94% accuracy, exceeds 90% threshold
T2Voice command accuracy at 85 dB, bone-conduction headsetPass91% accuracy, operators found it uncomfortable with PPE
T3Voice command accuracy at 85 dB, directional lapel micFail78% accuracy, below 90% threshold
T4Glove-friendly gesture input for repair category selectionPassCompleted selection in under 8 seconds
T5Screen readability at arm's length under production lightingFail40% of operators reported difficulty; font size insufficient
T6System response time during peak production loadPassAverage 2.1 seconds, within 3-second threshold
T7Repair category terminology match with operator languageFail35% wrong-category selection rate; terminology mismatch
T8Emergency procedure lookup under simulated urgencyPass95% completion rate, 12-second average; highest satisfaction
  • All DT coaching artifacts are scoped to .copilot-tracking/dt/{project-slug}/. Never write DT artifacts directly under .copilot-tracking/dt/ without a project-slug directory.

Requirements and compatibility

Written for: GitHub Copilot, Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

Security

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Attribution and licence

Published by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/hve-core · .github/skills/design-thinking/dt-curriculum · commit f425e94
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download dt-curriculum.zip