Freshman Class Analysis using AgentSheets

Abstract

The 2005 CMST Challenge Project is to survey the ninth grade class at East High School to see how many of their lives are affected by: pregnancy, drug use, crime arrests, family structure, student employment, and value of education. It was very hard to find the percentages of these factors for the United States. Therefore only certain questions will be used in the simulation. The results of the survey will be run through an agent sheet simulation to estimate the number of students that will successfully graduate using the data collected from the 2004/2005 freshman class. In order to successfully simulate the passing rate of the 2004/2005 freshman class we researched teen mothers, drug abusers, criminal offenders, students with broken homes, and student employees and found out the percentage rate in the United States is for dropping out of high school based on these risk factors. Once we have researched and found the percentage rate for all of these factors we can then go ahead with collecting and organize the data the East High School freshman class. The students that are working with us on the challenge project will enter the data in excel. They can then use excel to graph the results and tabulate quantities for the risk factors. Once percentages have been researched for each risk factor, an agent sheet will be set up setting each risk factor as a disease decreasing chance of survival or in this case graduating. The CMST challenge project that we have chosen is to predict how many of the 2004/2005 freshman class will end up graduating based on pregnancy, drug use, crime arrests, family structure, and student employment. Once we have found the percentages for all risk factors our students will use excel and agent sheets to predict the graduating rate of the 2004/2005 freshman class. We choose to use agent sheets because agents sheets gave us the best representation of students as characters. We could also enter each different combination of risk factors as a separate agent. This allowed each survey response to be represented accurately on the floor as an agent. We were also able to program in the percentages for drop out as a characteristic for each agent.