Simulation & assessmentApplied · learners and designersPublic review edition

Simulation scenarios and 3D for learning

Design meaningful decisions while making assumptions, limitations and learning evidence visible.

AI-generated illustration of HADR learning and exercise, not an actual event
AI-generated learning illustration, not a record of an actual event.
A learning synthesis based on the listed sources, not yet endorsed by an expert reviewer. Activities and rubrics are proposed by this project.

What will you be able to do?

From outcomes to observable evidence

simulation-design · v0.1.0

Intended outcomes

Knowledge

Distinguish teaching visualisations from validated models.

Skills

Design choices and outcome-changing conditions.

Ethics

Disclose fictional data and make activities accessible.

Character

Explore alternatives and explain revised reasoning.

Practise through an activity

Design a fictional three-route supply scenario, state at least three limitations and provide a text alternative to the 3D presentation. Run it twice, changing one information item.

Collect evidence for assessment

Knowledge

A scope statement and list of unsupported claims.

SIM-K
Skills

A branching diagram with assumptions.

SIM-S
Ethics

Data labels and an equivalent non-animated activity.

SIM-E
Character

A comparison of decisions across two runs.

SIM-C

Project learning synthesis showing proposed outcomes, activity and evidence. This is not a university-endorsed assessment framework.

Module references:[who-simex-2017][who-aar-2019][sendai-2015]

Suggested preparation: HADR foundations and people-centred assistance Design a CPX from intended outcomes

An exercise is not automatically a forecast

WHO uses simulation exercises to practise roles and identify preparedness gaps; an exercise does not require a mathematical model or three-dimensional graphics. In this knowledge base, a 3D flood scene is an illustration of a fictional learning situation, not a hazard map or real flood forecast. Our design proposal is to state what each visual teaches, which data are invented and which questions it cannot answer, preventing visual polish from implying unsupported accuracy.

Original sources: [who-simex-2017]

Choices need reasons and conditional consequences

Design proposal: begin with one decision, such as which information to obtain before choosing a supply route. Create plausible options and conditional consequences: a road may close after the last report. Ask learners to explain their reasoning before revealing the result, then show how changed assumptions affect the decision. A favourable outcome does not automatically prove competence because it may reflect a lucky guess. Assess verification and adaptation alongside the selected option.

Original sources: [who-simex-2017]

Expose assumptions for exploration

Exercise proposal: maintain an assumption register covering routes, capacity, waiting time, communications and additional assistance needs. Change one factor at a time and compare outcomes. For any number, state its unit and source or label it a teaching parameter. Do not present a precise arrival time without a defensible basis. Ask learners what real data they would need and whether their conclusion changes substantially when a parameter shifts slightly.

Original sources: [sendai-2015]

Enable access and learning after exploration

Learning proposal: provide essential information in text and a two-dimensional diagram so keyboard users and people who disable animation can make equivalent decisions. After each run, ask which evidence was used, which assumption was missed and what should be checked next. WHO review guidance informs the reflection, but a short web activity is not equivalent to a complete AAR. Use reflections for classroom discussion; quiz scores alone do not certify operational readiness.

Original sources: [who-aar-2019]

See the process at a glance

A synthesized learning diagram. Read it alongside the lesson and original sources.

  1. Frame a decision

    Choose a problem requiring reasoning, not just viewing.

  2. Define conditions

    State data, assumptions, choices and limitations.

  3. Explore

    Change a factor and compare reasoning across runs.

  4. Reflect

    Identify learning, remaining unknowns and real-context requirements.

Fictional learning scenario

Explore a decision

Fictional scenario: a 3D scene shows a green road, but route information predates the latest rainfall. What should the learner do?

From knowledge to evidence

Design a fictional three-route supply scenario, state at least three limitations and provide a text alternative to the 3D presentation. Run it twice, changing one information item.

CriterionProficientDeveloping
TransparencyEvery parameter has units and a source or fictional labelPresents teaching parameters as actual data
Decision qualityExplains evidence and effects of changed assumptionsChooses without explanation
AccessibilityText supports an equivalent substantive activityEssential information exists only in animation

A proposed rubric for educators to adapt, not a university accreditation standard.

Check your understanding

Answer all 5 questions, then review the explanations. This score is for self-study.

1Does a polished visual establish model validity?
2How should an invented capacity parameter be labelled?
3Why change one factor at a time in the introductory activity?
4What is a suitable alternative when animation is disabled?
5What should reflection examine beyond the correct answer?

References & further verification

Cite this module

PK-Research. (2026). Simulation scenarios and 3D for learning (simulation-design, v0.1.0). HADR–CPX Knowledge Commons. https://hadr-cpx.pk-research.work/en/modules/simulation-design/