High Level Design Rationale and Sources of our Project Idea The aim of this project was to explore evolutionary algorithms on an FPGA using how well an organism plays the game of Tic-Tac-Toe as a fitness function. Tic-Tac-Toe is a good example of this kind of a problem because games tend to have strategies buried behind massive amounts of data, in this case, thousands of boards and hundreds of thousands of possible paths through them. You may NOT electronically post this product online including to teacher blogs, classroom websites or school networks unless they are private or password protected.Our project attempts to model the random process of an evolution using how well the organism plays the classic game of Tic-Tac-Toe as a fitness function with the end goal to create the perfect Tic-Tac-Toe machine.Įvolutionary algorthms can solve complex problems that may not be able to be solved in traditional analytical or numerical methods by using random chance to find a local maximum in a fitness function. This entire document, or any parts within, may not be reproduced or displayed for public viewing. Additional licenses can be purchased at a discount for others to use in your department. Copying for more than one teacher, classroom, department, school, or school district is prohibited. Terms of Use: This document is for personal use only and may only be used by the original purchaser.

You will need access to a Google Account to make the most of these resources, but the printable pdfs are also very utilizable. The download is a pdf, with embedded force-copy links to create your own copies of the Google Docs, Slides and Sheets versions of these resources. A link to an editable sample graph of data created in Google Sheets. Slides with full instructions and embedded videos about natural selection in actual rock mice populations in the American southwest from HHMI Biointeractive.ĥ. (This works really well with Google Classroom for scoring and providing feedback!)Ĥ. A simple rubric for evaluating student work. An editable Google Doc of the lab document.Ģ. Students then generate graphs of their data and analyze the data to discover how the environment can create different survivial rates for different phenotypes, thus changing a population over time.ġ. Students repeat this to record the phenotypes of mice born in 3 generations, and then reset the game, playing again after a simulated environmental change. Students draw an allele card to determine the fate of their mouse. Students determine the phenotype of each mouse generated from their draw. Students work in dyads or groups to draw mice allele cards from a ''gene pool' I hope you find my efforts rewarding in creating a meaningful learning experience for your students. I also want my students generating and analyzing data in labs in addition to engaging in argumentation from evidence based on their data when writing conclusions. I created this version because I liked the nature of the game and what students learn about how populations change over time, but I needed it connected to a cohesive, real world story of a changing population.

There are many different versions of this game available online.

Learn about population genetics and evolution in this fun and engaging lab simulation! Your students get to play a card game that generates data to show how changes in the environment can result in changes in the gene frequencies in a population of rock pocket mice in the american southwest.

Population genetics card game simulator