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Fashion Trends in a Middle School

Fashion Trends in a Middle School. Supercomputing Challenge Summer Institute Final Report July 27, 2006 Capshaw Middle School - Team #01 Theresa Anaya Burney Peter Colehour Susan Gibbs Thansewi J. Martinez Makoena Monese. Introduction.

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Fashion Trends in a Middle School

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  1. Fashion Trends in a Middle School Supercomputing Challenge Summer InstituteFinal ReportJuly 27, 2006Capshaw Middle School - Team #01 Theresa Anaya Burney Peter Colehour Susan Gibbs Thansewi J. Martinez Makoena Monese

  2. Introduction • Middle school students arrive at school wanting both to conform to fashion norms and to be recognized as individuals. Each student also has a relative degree of shyness or sociability. These factors affect each student’s susceptibility to a fashion trend. The research supports the relative shyness and resistance levels of students, and tipping points in the spread of a trend.

  3. Executive Summary Our computational model: • Allows multiple trials of how the initial percentage of resistant students affects speed of a trend’s spread • Imitates the real-world school environment: • Shows relative shyness and susceptibility of students • Recognizes that the relative percentage of resistant students determines the speed of the trend’s spread. • Can be used to study relevant middle school topics: • bullying • spread of disease • the susceptibility of individuals to drug, alcohol, tobacco use, and sexual activities.

  4. The Project Hypotheses • The StarLogo model will graph the spread of a trend, comparable to an infection model. • The lower the initial percentage of followers, the slower the trend will spread. • A tipping point may exist in the initial percentage of followers, above which the trend spreads much more quickly.

  5. Mathematica Model • Our infection model set two contact rates (30% of agents have fewer contacts) and used an infection variable for the percentage of the population that was susceptible (infection after 2 exposures) or immune (after 4 exposures). dPI /dt= rcPI (1-PI) Expected number of susceptible individuals who will become infected in the time Δt, assuming rc = 1.

  6. Starlogo Model • Our STARLOGO model allows students to manipulate the original percent of students characterized as “followers” (susceptible) and “freethinkers” (relatively immune).

  7. Results • All 3 Hypotheses proved • The StarLogo model is comparable to an an infection model. • The lower the initial percentage of followers, the slower the trend will spread. • Two tipping points exist in the initial percentage of followers, above which the trend spreads much more quickly

  8. Recommendations Students: • Expand model to apply to new issues • Expand and refine model to show affect of advertising, new conflicting trends, and • Conduct real-world experiments on the spread of trends Teachers: Create a StarLogo TNG model Use model to entice students into Challenge

  9. Acknowledgements • We appreciate: • STI Team - for all their support and patience. • Dylan Allegreti - for supporting the process and working with us.

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