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Probability Concept Adaptation

Run the Probability Adaptation MicroSim Fullscreen Edit the Probability Adaptation MicroSim Using the p5.js Editor

Description

This interactive MicroSim demonstrates how a single educational concept (probability) can be adapted for vastly different audiences. Instructional designers must consider their audience's age, experience, mathematical background, and learning goals when creating educational materials.

The Seven Audience Levels

Each tab shows a different approach to teaching probability:

  1. Early Childhood (Ages 3-5) - "Lucky Duck Pond"
  2. Pure visual/tactile learning with animated ducks
  3. No numbers or text, just celebration animations

  4. Focus on the intuitive feeling of chance

  5. Elementary (Ages 6-10) - "Marble Jar Predictor"

  6. Introduction of counting and simple fractions
  7. Tally marks for tracking predictions

  8. Language like "3 out of 10"

  9. Middle School (Ages 11-13) - "Probability Explorer"

  10. Formal probability notation: P(event) = x/n
  11. Multiple scenario types (dice, coins, spinners)

  12. Comparing theoretical vs. experimental results

  13. High School (Ages 14-18) - "Insurance Risk Calculator"

  14. Real-world application context
  15. Multiple variables and compound probability

  16. Professional mathematical notation

  17. Undergraduate (Ages 18-22) - "Bayesian Reasoning Lab"

  18. Prior, likelihood, and posterior distributions
  19. Step-by-step Bayes' theorem visualization

  20. Medical diagnosis scenarios

  21. Graduate/PhD - "MCMC Sampler"

  22. Markov chain Monte Carlo visualization
  23. Parameter space exploration

  24. Convergence diagnostics

  25. Corporate/Professional - "Risk Decision Tool"

  26. Business decision context
  27. Risk-adjusted recommendations
  28. Confidence intervals and ROI focus

Interactive Features

  • Tab Navigation: Click any tab to view that audience level's approach
  • Comparison Mode: Toggle "Compare Mode" to view two approaches side-by-side
  • Animated Previews: Each tab shows an animated preview of how that MicroSim would work
  • Key Differences: Callouts highlight what changes between levels

Embedding This MicroSim

You can include this MicroSim on your website using the following iframe:

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<iframe src="https://dmccreary.github.io/automating-instructional-design/sims/probability-adaptation/main.html" height="502px" scrolling="no"></iframe>

Lesson Plan

Objective

Students will analyze audience-appropriate versions of probability concepts and design their own adaptations for different learner groups.

Activities

  1. Exploration (10 minutes): Have students explore each of the seven tabs, noting what changes between levels.

  2. Analysis Discussion (15 minutes): As a class, discuss:

  3. What mathematical concepts appear at which levels?
  4. Why do younger learners need concrete objects (ducks, marbles)?
  5. When does formal notation become appropriate?

  6. How does real-world context change across levels?

  7. Comparison Exercise (10 minutes): Using Compare Mode, have students identify:

  8. Three features that early childhood has that graduate level does not
  9. Three features that graduate level has that early childhood does not

  10. The "turning point" where abstract math appears

  11. Design Challenge (20 minutes): Give students a different concept (e.g., fractions, area, or variables) and have them sketch how they would adapt it for:

  12. A 5-year-old
  13. A middle schooler

  14. A business professional

  15. Presentation (10 minutes): Students share their adaptation designs and explain their choices.

Assessment

Students demonstrate understanding by correctly identifying audience-appropriate features and creating defensible adaptations for new concepts.

Design Principles Illustrated

This MicroSim demonstrates several key instructional design principles:

  • Concrete to Abstract: Young learners need physical/visual representations before symbolic notation
  • Scaffolding: Each level builds on previous understanding
  • Context Relevance: Adult learners benefit from real-world applications
  • Cognitive Load: Complexity increases with expertise level
  • Engagement Mechanisms: Different ages require different motivation strategies

References

  • Bruner, J. (1966). Toward a Theory of Instruction. Harvard University Press.
  • Piaget, J. (1952). The Origins of Intelligence in Children. International Universities Press.
  • Knowles, M. S. (1980). The Modern Practice of Adult Education. Cambridge Adult Education.
  • Fischbein, E. (1975). The Intuitive Sources of Probabilistic Thinking in Children. Springer.