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Education & learning publications June 22, 2019

Taking a critical look at your child find efforts

Margaret Gillis, Kathryn Morrison

Citation

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Gillis, M., Morrison, K., & Bernstein, H. (2019). Taking a critical look at your child find efforts. DaSy, The Center for IDEA Early Childhood Data Systems.

Abstract

In reviewing the data on the percentage of children birth to 3 years old that my state’s Part C program serves, I noticed that we serve a much lower percentage of children as compared with the national average. I want to understand why my state’s percentage is so much lower and identify some ways to improve our system. How can I examine our data and child find efforts? — Jane Coordinator

Background

Child find is a component of Part C of the Individuals with Disabilities Education Act (IDEA) that requires states to establish a comprehensive system to identify, evaluate, and enroll infants and toddlers who are eligible for early intervention. The comprehensiveness of the child find system affects the number of children Part C programs serve. In fall 2017, the percentage of infants and toddlers, birth to 3, served by Part C ranged across states from 0.8% to 9.5%, with a national average of 3.3%. The state percentages are expected to vary somewhat because of differences in each state’s eligibility criteria. However, big differences in the percentage of the population served between states with similar eligibility criteria would suggest that some states might not be serving all eligible children. This blog post provides guidance on where to begin to examine child find data and practices and describes several resources that are available.

Where to Start

Limited staff and resources pose challenges for many states, including how to improve the child find system. Program improvement can be a daunting process, and it can be difficult to know where to begin. However, taking a close look at your policies, procedures, practices, and data are first steps toward making your child find efforts more effective.

  • Start by reviewing the federal regulations that guide child find and consider how your state is meeting them.
  • Examine state and local program data related to child find to better understand your system. This includes reviewing public awareness efforts, referral procedures, and whether your state or local area uses a screening tool as a first step. Looking at difference across local programs in the percentage of the population served and the number and demographics of children (e.g., age, geographic location, gender) in each step of the child find process, from referral to enrollment, are also useful for identifying patterns.

Resources and Help Are Available

The Office of Special Education (OSEP) and the Technical Assistance centers are here to help! In addition to providing TA, they have developed tools that can assist you in evaluating and improving your child find system.

  • Child Find Self-Assessment : A four-part toolkit that can help states examine how they are meeting child find regulations, identify critical child find best practices, locate resources to help them implement best practices, and easily access OSEP’s policy letters and guidance on child find.
  • Part C Child Find Funnel Chart Tool : This Excel template displays data on each step of the Part C process, from referral through exit, for a set of infants and toddlers referred within a specified time span. Data can be entered for the entire state, a local program, or one or more subgroups. The tool enables Part C program administrators to easily visualize the differences in the number of children in each step of the process.
  • Meaningful Differences in Child Find Calculator : This Excel-based calculator allows states to make several comparisons related to the percentage of infants and toddlers served: state percentage compared with state target, local program percentage compared with state target, and year-to-year comparisons of the state percentages. It also computes confidence intervals to determine whether the difference between two numbers is large enough to be considered meaningful (statistically significant).

When Jane Coordinator looked at the state data, she noticed that not many referrals were coming from one region of the state. The Part C Child Find Funnel Chart Tool helped her determine that the point of difference from other regions was at referral. The Meaningful Differences Calculator determined that the difference was statistically significant. The Child Find Self-Assessment helped Jane identify several best practices the state could implement to address the low number of referrals from the region.

For more information on how to use any of the tools listed above or to receive other support related to child find, contact Margaret Gillis (margaret.gillis@sri.com) or Evelyn Shaw (evelyn.shaw@unc.edu).

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