Assessing the Predictive Sensitivity of Early Childhood Screening Variables to Improve Pre-K Eligibility Decisions

1 online resource (124 pages) : PDF

2018

University of North Carolina at Charlotte

High-quality early childhood education, such as pre-kindergarten (pre-k) can help children develop the academic and social-emotional skills they need to succeed in school. Pre-k can be especially important for students at risk of starting elementary school behind their peers, helping them catch up to their peers by the time school begins and setting them on more positive educational and developmental trajectories. Many pre-k programs seek to identify children with the greatest need by collecting information about the child’s functioning, the child’s experiences in the home, and the child’s family. While there is ample research connecting early childhood risk factors to school readiness, there is no standard method for using multiple risk factors to determine which children have the greatest need for pre-k and, therefore, should be accepted into a pre-k program. The present study seeks to improve our ability to predict children’s school readiness, which is conceptualized here as language development (i.e., receptive vocabulary) and social-emotional functioning. Using hierarchical multiple regressions, the present study seeks to assess the extent to which early childhood variables collected during the Charlotte-Mecklenburg Schools (CMS) pre-k screening process predict child functioning at the beginning of pre-k. The results of these analyses 1) indicate the risk factors with the strongest relationships to receptive vocabulary and social-emotional functioning at the beginning of pre-k and 2) guide modifications to the CMS pre-k screening process and the formula used to determine eligibility.

masters theses

Early childhood education
Developmental psychology

M.A.

Child Risk
Early Childhood Education
Eligibility
School Readiness
Screening
Social-Emotional

Psychology

Kilmer, Ryan
Cook, James

Quinlan, Margaret

Thesis (M.A.)--University of North Carolina at Charlotte, 2018.

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Gadaire_uncc_0694N_11733

http://hdl.handle.net/20.500.13093/etd:420