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Comprehensive Plan <br />Public School Facilities Element <br />Table 12.12: Public School Student Enrollment Projections by School Type <br />N. SchoolType <br />201,5 16', <br />X2020 21 am <br />`; 2Q25 26 ,: <br />,.; 2030-311... <br />Elementary Schools <br />9,978 <br />10,971 <br />12,062 <br />13,263 <br />Middle Schools <br />5,196 <br />5,713 <br />6,282 <br />6,907 <br />High Schools <br />5,612 <br />6,171 <br />6,784 <br />7,459 <br />Total <br />20,786 <br />22,855 <br />25,128 <br />27,629 <br />Student Population from 2007 through 2013 <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. These are Sebastian <br />Charter Junior High, North County Charter, St. Peter's Academy, Indian River Academy, <br />and Indian River Charter High School. As a result of the addition of these schools, the <br />FDOE enrollment data for the School District showed an estimated average of 555 fewer <br />students per year. When these students were accounted for in the School District's <br />enrollment projections, the number of students in the appropriate grades and years were <br />adjusted through the use of the enrollment ratios developed for this forecast for public <br />schools. <br />This process specified a regression model for each grade level as follows: <br />Stu(,lentsgradex,yeart = Const. + 161* Studentsgradex—l,yeart 1 +)32* population growth <br />This regression model specifies 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 />20 <br />