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How Simulations Generate Knowledge

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About This MicroSim

This interactive MicroSim helps students assess the strengths and limitations of simulation-based knowledge by tracing the cycle from assumptions to outputs and validation.. It supports the learning objectives in Chapter: Knowledge, Technology, and Power.

How to Use

Use the interactive controls below the drawing area to explore the visualization. Hover over elements for additional information and click to see detailed descriptions.

Iframe Embed Code

You can add this MicroSim to any web page by adding this to your HTML:

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<iframe src="https://dmccreary.github.io/theory-of-knowledge/sims/simulation-knowledge-cycle/main.html"
        height="450px"
        width="100%"
        scrolling="no"></iframe>

Lesson Plan

Grade Level

9-12 (High School / IB TOK)

Duration

15-20 minutes

Prerequisites

  • Basic understanding of how computer models and simulations are used in science
  • Awareness that climate science relies heavily on computational models
  • Familiarity with the TOK concept that knowledge production methods have both strengths and limitations

Learning Objectives

  • Evaluate the strengths and limitations of simulation-based knowledge by tracing how assumptions, models, and validation interact in the knowledge cycle

Activities

  1. Exploration (5 min): Step through each stage of the simulation knowledge cycle using the climate modeling example. At each stage — assumptions, model building, running the simulation, interpreting results, and validation against real-world data — read the descriptions and note how each stage depends on the ones before it. Pay special attention to the evaluation panel that highlights where uncertainty enters.
  2. Guided Practice (10 min): After completing the cycle, open the evaluation panel and examine the strengths and limitations listed for each stage. In small groups, discuss: At which stage is the most uncertainty introduced? Can a simulation ever "prove" something, or can it only provide evidence? Consider how a climate skeptic and a climate scientist might evaluate the same simulation differently. Write down your group's consensus on the single greatest limitation of simulation-based knowledge.
  3. Assessment (5 min): A government bases a major policy decision on a simulation that predicts sea levels will rise by 1 meter in 50 years. Write a brief TOK-style evaluation: What are two reasons to trust this simulation-based knowledge? What are two reasons to treat it with caution? Conclude with your own reasoned judgment about how much weight simulation evidence should carry in policy decisions.

Assessment

  • Accurately traces how knowledge flows through the simulation cycle from assumptions to validation
  • Identifies at least two specific strengths and two specific limitations of simulation-based knowledge
  • Provides a balanced, reasoned evaluation of simulation evidence rather than an all-or-nothing judgment

Quiz

Test your understanding with this review question.

1. A climate simulation accurately predicts average global temperatures for the past 50 years when fed historical data. What can we most reasonably conclude?

  1. The simulation proves that its predictions about future climate are certainly correct.
  2. The simulation's assumptions and model structure are consistent with past data, which gives some confidence in — but does not guarantee — its future predictions.
  3. The simulation is unreliable because it was only tested against data that already happened.
  4. Past accuracy is irrelevant to evaluating a simulation's knowledge claims about the future.
Show Answer

The correct answer is B. Successful validation against historical data (sometimes called "hindcasting") demonstrates that the model's assumptions and structure can reproduce known outcomes, which increases confidence in the model. However, it does not guarantee future accuracy because future conditions may differ from past conditions in ways the model does not capture. Option A overstates the conclusion; options C and D understate the value of validation.

Concept Tested: Validation and limitations of simulation-based knowledge

References

  1. International Baccalaureate Organization. Theory of Knowledge Guide. Cardiff: IBO, 2022.
  2. Woolman, M. Ways of Knowing: An Introduction to Theory of Knowledge. IBID Press, 2006.