**My website is under construction and has been updated with new links for the simulations. Use the menu to the left or scroll down to access all the simulations with the new links.**

**Welcome to my collection of computational models for biology and ecology. **

**Hypothesize, test, and revise your mental models.**

**Perturb, run, and reflect upon these thought experiments.**

**Cell Transport**

**Ecology**

**Enzymes**

**Evolution**

**Evolution of Populations: Genetic Drift, Natural Selection, and Mutations****Guppy Evolution: Natural Selection, Sexual Selection, and Genetic Drift**

**Genetics**

**Metabolism**

**Molecular Biology**

**Physiology**

**Physics**

**Timing and Coordination**

**Google Folder of Activity Sheets**

Computational models are thought experiments run on a computer. Computational modeling is a powerful tool for learning a system's dynamics. In a computational model, the parts are not simply linked by *variable x* affecting *variable y*. Rather, variables are linked operationally/mathematically. For example, y = 0.2x.

Using computational models allows users to interact with the quantities of a system, perturb the system, and use the model to understand the dynamics. Many behaviors of common biological and ecological systems are complex. Representing those systems with algebra is extremely daunting for high school students. However, quantitative modeling allows students to interact with complex mathematical relationships without needing to understand all the math. More importantly, students can manipulate the models and easily discover complex properties of many biological and ecological systems.

For example, computational models allow students to manipulate systems that have:

**Positive and negative feedback loops****Thresholds and tipping points****Robustness and sensitivity**

Additionally, computational models are ideal for representing biological concepts because they can be:

**Iterative****Change over time (dynamic)****Linear or non-linear****Deterministic or random****Predictable or chaotic**

Students can explore these ideas with computational models. They don't need to know the math to become a computational thinker. They do have to understand feedback loops, thresholds, and other important behaviors of systems. Our world is complex, and students need methods to experiment with these complex behaviors. Computational models help students understand those concepts because students can manipulate quantities and watch how that new quantity affects the system.

To better assist you here are a few things to keep in mind:

1. The simulations may take 10 seconds to load depending on the speed of your connection.

2. Some simulations take longer depending on the mathematical relationships. Be patient. Real experiments take much longer.

3. For help navigating through the simulations and graphs see THIS HELP GUIDE.

The goal of my computational models is to make you better critical thinkers. I want you to manipulate variables, examine data, and draw your own conclusions.

I use these computational models to teach scientific practices throughout my curricula. I have found that simulations are a powerful method of teaching the *Scientific Practices *identified by AP science courses, and the Next Generation Science Standards (NGSS).

*Simulations created by Mr. Jon Darkow*