Interactive R0 Simulation template: Enhancing Learning Through Interactivity

 

Interactive R0 Simulation: Enhancing Learning Through Interactivity

Introduction

Understanding R0, the basic reproduction number, is crucial in the study of epidemiology. It represents the average number of people to whom a single infected person will transmit a disease. To make this concept more accessible and engaging for students, we can create an interactive simulation that allows for real-time manipulation and visualization. This blog post will guide you through the process of developing a simple yet effective R0 simulation. If successful, this tool can be incorporated into an existing lesson created in the Singapore Student Learning Space (SLS). Animation https://media.hhmi.org/biointeractive/click/modeling-disease-spread/advanced-spread.html

Purpose

The primary aim is to develop an interactive simulation to explain R0, making it a valuable addition to the new learning objectives (LO). An existing animation demonstrates disease spread, but a customizable version where students can adjust parameters and observe changes dynamically will enhance understanding and engagement. Additionally, integrating a graph to display the number of infected individuals over time will provide a comprehensive learning experience.

Creating the Interactive R0 Simulation

Use AI to generate the simulation

notice the code is difficult to add into WebEJS

to overcome this issue, conceptualise the position (x,y) of the spread of the infection, write in code the actual positions for level = 0,1,2 enough details for AI to understand the example.

ask AI to write the elegant code

ask AI to generalise for any number of cases

repeat for the lines joining the position

Conceptualizing the Spread

First, let's conceptualize the positions (x, y) of the spread of infection. We will use levels to denote different stages of infection. Each level will have a specific number of points arranged in a pattern.

Example Levels:

Level 0:

• Initial infection at the origin.
• Position: (0, 0)

Level 1:

• Three new infections around the initial point.
• Positions: (1, 1), (1, 0), (0, -1)

Level 2:

• Each infected point from Level 1 generates three more infections.
• Positions:
  • For (2, 4): (2, 3), (2, 2)
  • For (2, 1): (2, 0), (2, -1)
  • For (2, -2): (2, -3), (2, -4)

Link

Conclusion

Creating an interactive R0 simulation not only enhances the learning experience but also helps students better understand the dynamics of disease spread. By allowing real-time adjustments and providing visual feedback through a graph, students can experiment with different scenarios and observe the effects firsthand. Incorporating this tool into existing lessons in the SLS will make the learning process more engaging and effective.

Interactive simulations like this empower students to explore complex concepts in an intuitive and hands-on manner, fostering deeper comprehension and retention. By leveraging technology, we can transform education and make learning more accessible and enjoyable for all students.