ERIC Number: ED615007
Record Type: Non-Journal
Publication Date: 2021-Oct
Pages: 1
Abstractor: ERIC
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Predicting Early Fall Student Enrollment in the School District of Philadelphia. Study Snapshot. REL 2022-124
Regional Educational Laboratory Mid-Atlantic
Predicting incoming enrollment is an ongoing concern for the School District of Philadelphia (SDP) and similar districts with school choice systems, substantial student mobility, or both. Inaccurate predictions can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester. This Study Snapshot highlights key findings from a study that compared the accuracy of four statistical techniques for predicting fall enrollment at the school-by-grade level, using data from prior years, to assess which approach might be the most useful for planning school staffing in SDP. [For the full report, see ED615006. For the appendixes, see ED615008.]
Descriptors: Enrollment, Enrollment Projections, School Districts, Statistical Analysis, Data Analysis, Student Mobility, Class Size, Accuracy, Predictor Variables, Elementary Schools, Neighborhood Schools
Regional Educational Laboratory Mid-Atlantic. Available from: Institute of Education Sciences. 550 12th Street SW, Washington, DC 20202. Tel: 202-245-6940; Web site: https://ies.ed.gov/ncee/edlabs/regions/midatlantic/index.asp
Publication Type: Reports - Descriptive
Education Level: Elementary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: Regional Educational Laboratory Mid-Atlantic (ED/IES); Mathematica; National Center for Education Evaluation and Regional Assistance (NCEE) (ED/IES)
Identifiers - Location: Pennsylvania (Philadelphia)
IES Funded: Yes
Grant or Contract Numbers: EDIES17C0006
IES Publication: https://ies.ed.gov/ncee/edlabs/projects/project.asp?projectID=4648
Author Affiliations: N/A