The enrollment projection model used by the edulog enrollment system is based on a modified cohort survival technique that separately identifies the various factors determining enrollment patterns within the district. Typically, the results are much more accurate than the traditional cohort survival techniques used by most school district planners.
The enrollment projection modeling software will enable the district to accomplish the following tasks:
- Project enrollment by grade for the entire district
- Project enrollment by grade and residing school
- Project enrollment by grade and enrolling school
- Project enrollment by grade and small planning zones
- Project enrollment by any aggregation of planning zones - if the planning zones are created (planning zones are totally operator-defined to represent census tracts, street or partial blocks, neighborhoods, or any other meaningful geographic area for planning considerations)
- Estimate future enrollment for existing and alternative attendance boundaries
- Project enrollment by racial/ethnic categories if sufficient data is available
- Project enrollment for new attendance boundaries or temporary study areas
- Project enrollment by any other operator-defined student attributes.
Initially, the model will project enrollments for five years out. Ten year projections can be made at the outset provided that proper historical and future data is available. As the district's databases are enhanced over time, the model will be able to project out ten to fifteen years.
If proper historical and future data is available, the model will evaluate, per user-defined area, the effect of:
- in-migration and out-migration trends
- cohort progression patterns
- retention rates
- skipped grade rates
- new housing
- turnover in existing housing stock
- changes in transfer policy
- transience rates
- district birth rates
- interest rates
The programs are capable of displaying graphic overlays of a user-specified number of years of historical and/or projected enrollments for a given user-defined area. The system allows for the comparison of alternative enrollment projection forecasts versus individual school capacities to identify over- and under-populated school conditions.
If the district creates a housing database, the model will allow the district to monitor housing development over time, and planning staff will be able to graphically analyze the development rates in any sub-area.
One of the strengths of the enrollment model proposed is the model's ability to perform "what-if" analysis. All projection models are only as accurate as the assumptions upon which they are based. The edulog enrollment projection model allows the district to efficiently consider alternative assumptions. For example, the enrollment effects of over- or under-estimating projected housing construction can be quickly simulated.
By quantifying the effects of alternative growth scenarios-rather than concentrating on the accuracy of the model's projections-the district can formulate alternative strategies for dealing with potential errors. This capability can be used to produce low and high projections, to determine effects of specific development projects, and to provide relevant information for budget and staffing considerations.
The software's linkage with edulog's boundary planning and boundary optimization software enables the district to analyze the facility and attendance boundary implications of alternative growth forecasts. The district will be able to determine the need for, and timing of, any needed facilities and to calculate the cost for building the facilities. A mitigation strategy for funding the facilities can be established. The district's current attendance boundaries can be loaded with the projected students to determine if any modifications will be required and to analyze alternative boundaries in light of the anticipated enrollment.
edulog's enrollment projection model goes beyond other mathematically based statistical packages because it tests various assumptions for future growth with a complete geographic orientation. Because it is intimately tied to the geocode, the model can actually predict student distributions in specific geographic areas while using a variety of growth assumptions.
"In 2001 the school board voted to renovate and reopen Garfield Elementary School for the 2003-2004 school year. To accommodate budgetary constraints, the administration was interested in recommendations for the closure of one elementary school. The district had a voluntary desegregation plan implemented in 1977. The new attendance boundary for the Garfield School was not required to conform to the 1977 plan and was to be built to accommodate the local neighborhood population. The primary objective of the project was minimal but adequate boundary realignment to satisfy the following goals: no building should exceed the maximum capacity, the racial composition of each school should not deviate more than ten percent from the current ratio, and current bilingual student assignments should be retained. This project included the implementation of the edulog planning system at the district and instruction in the use of the software.
"Space available choice, special needs classrooms and class size reductions represented only a portion of the programmatic variables that complicated student assignments in our district. In addition to objective and expert service, edulog identified and quantified the complex array of variables and provided alternative solutions for our District's realignment challenges."