LESSON PLAN FOR CHAOS AND THE COMPUTER

PURPOSE
The student will explore a model of the travels of Victim Alpha of the AIDS disease. Each student will deal with probability and random numbers to develop this study. Methods of protection and ignorance of the disease will also be discussed. Safe behavior by our students may very well be the ultimate goal of the exercise.

BACKGROUND
During the earliest indication of the AIDS epidemic a strange pattern was identified by the medical detectives. Young Gay men were being infected in many cities around the country, at seemingly almost the same time. A new disease normally will only show up in an isolated area. Why was it only showing up in cities thousands of miles away from each other? The answer was traced to a Male Flight Attendant , who was Gay and had tremendous stamina . In the age of ignorance, unprotected Sex and promiscuity the epidemic was well begun. Other factors have now taken over the spread of AIDS, we will also address them. Perhaps this topic is too strong for some classes, but in the world we live in it is better to be informed.

MATERIALS
Duplicated Sheets , Colored pencils, Ti-81+ Calculator. The use of the internent to contact theCDC in Atlanta CDC ATLANTA might be an extra added attraction. The Starlogo program from MIT is another added resource.StarLogo

PROCEDURE
On the Worksheet three cities are noted on the first row. (Guess the cities from the initials). At each lay over Alpha infected two people. (This went on for months) . Each other person had contact with two other persons . Set up a random number system (teachers lecture). Use that system to determine "by percentages" if that person became infected.(teachers lecture) Repeat this system for ten times . Count the number of men infected. The second line refers to the present and some factors that help control the disease today . First label the factors and place the possible percentages as per your in group discussions. Your teacher will explain your choices. Repeat each "Iteration" ten times . Count the number infected at each site.

RESULTS AND CONCLUSIONS

Joan Johnston and Alan Cushner