caitlin bryant jennifer davis zach wooten predicting the need for special education classes

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Caitlin Bryant Jennifer Davis Zach Wooten PREDICTING THE NEED FOR SPECIAL EDUCATION CLASSES

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Caitlin Bryant

Jennifer Davis

Zach Wooten

PREDICTING THE NEED FORSPECIAL EDUCATION CLASSES

OUTLINE

• Purpose

• Introduction

• Model Development

• Data Collection

• Data Analysis

• Conclusions

• Future Improvements

• Sources

PURPOSE OF OUR STUDY

• 13.7% of Children Receive Special Ed. Services

• Budget Cuts

• What Does This Mean For Students?

• Is the Number of Special Education Students Predictable?

INTRODUCTION

• Disabilities of Special Education Students

• Down Syndrome as Our Main Focus

• Definition of Down Syndrome

• Data Collection from 20 years

MODEL DEVELOPMENT

• Assumptions:

• Down Syndrome Model applied to other Disabilities

• 0.12% of Americans have Down Syndrome

• All Down Syndrome Children in School at Age 5

• All Down Syndrome Students Graduate/Transition

• Assume all 5-18 Year-Olds in 1990 in School

MODEL DEVELOPMENT• Equation Variables:

• xn: total # of students diagnosed with Down Syndrome in year n

• s: total # of 5 year-olds with Down Syndrome entering public school

• g: total # of graduating/transitioning Down Syndrome students

• r: # of Down Syndrome Students in Public School per Year

• Model Equation:

• Xn = (xn-1) + r(s – g)

DATA COLLECTION• Birth Rates for Years 1990-2010

• Finding Initial Population, x0

• Plotting the Differences between Years

DATA ANALYSIS• Histogram doesn’t appear to show Normality

• Probability Scale Plot:

DATA ANALYSIS• Normal and Uniform Distributions do not fit

• Plotting Randomness

• With Normal Distr.:

• With Uniform Distr.:

CONCLUSIONS

• Challenges of Educating Students of All Abilities

• Numbers are Virtually Impossible to Predict

• There is No Accurate Way for State Legislators to Predict # of Special Needs Students

• Special Education Budget Cuts Can Not be Justified

FUTURE IMPROVEMENTS

•Creating Models for Each Disability

•Collecting Information on # of Student Deaths and/or Dropouts

•Look at Costs of Special Needs Students vs. Average Students for the State

•Use Information to Create Ideal State Budget for Each State

SOURCES• SchoolSpeechPathology, . (2011, February 20). School speech pathology blog. Retrieved from

http://schoolspeechpathology.wordpress.com/2011/02/20/special-education-budget-cuts-of-2011/

• Pearson Education, . (2007). Crude birth and death rates for selected countries. Retrieved from http://www.infoplease.com/ipa/A0004395.html

• Pearson Education, . (2007). Live births and birth rates, by year. Retrieved from http://www.infoplease.com/ipa/A0005067.html

• Elizabeth, Mary. (2011). Special education statistics. Retrieved from http://www.educationbug.org/a/special-education-statistics.html

• Health Guide, Initials. (2001-2011). Learning disabilities in children. Retrieved from http://www.helpguide.org/mental/learningdisabilities

• Wikipedia, . (2011, March 10). Dsm-iv codes. Retrieved from - http://en.wikipedia.org/wiki/DSM-IVCodes

• Google, . (n.d.). Define: down syndrome. Retrieved from http://www.google.com/search

• National Down Syndrome Society, . (n.d.). Transition planning. Transition Planning, Retrieved from http://www.kcdsg.org/files/content/Transition%20Planning%20for%20Students%20with%20Down%20Syndrome.pdf

• U.S. Census Bureau, . (n.d.). American fact finder. Retrieved from http://factfinder.census.