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Comprehensive Plan Public School Facilities Element <br />Table 12.11: Public School Student Enrollment Projections by School Type <br />School T e <br />2018-19 <br />2028-29 <br />Elementary Schools <br />8,765 <br />11,814 <br />Middle Schools <br />3,675 <br />4,925 <br />High Schools <br />3,645 <br />6,788 <br />Other <br />150 <br />100 <br />Total <br />16,244 <br />23,627 <br />Student Population from 2009 through 2015 <br />The data used to forecast student population were obtained from the FDOE. Since the <br />1998/99 school year, five charter schools have been established in the county. These are <br />Sebastian Charter Junior High, North County Charter, St. Peter's Academy, Indian River <br />Academy, and Indian River Charter High School. As a result of the addition of these <br />schools, the FDOE enrollment data for the School District showed an estimated average <br />of 555 fewer students per year. When these students were accounted for in the School <br />District's enrollment projections, the number of students in the appropriate grades and <br />years were adjusted through the use of the enrollment ratios developed for this public <br />school forecast. <br />This process specified a regression model for each grade level as follows: <br />StudentSgddex,yeart = Const. + 8, * Studentsgrade x-1, year t-1 + N2 * population growth <br />This regression model projects student population in a given year as a function of <br />unobservable factors (captured by the constant term), cohort survival (the number and <br />percentage of students advancing in grade), and a percentage of population growth. <br />Changes in any of these trends from one year to the next can have a significant impact on <br />the number of students ultimately enrolled. For example, the high school driver's license <br />law change in 1997 resulted in fewer high school dropouts statewide in 1999 and 2000. <br />Similarly, increases in population growth and changing development patterns can result <br />in more students than the cohort survival method may predict. <br />This regression model was refined and adjusted on a grade -by -grade basis to build the <br />student forecast models with the highest degree of predictability. <br />Community Development Department Indian River County <br />16 <br />