What are the characteristics of children who are suspended and/or expelled from CCEE programs?

Answering this question can provide insights into what groups of children are more or less likely to experience exclusionary discipline in CCEE programs. To answer this question, identify children who have experienced suspension or expulsion from CCEE program sites and analyze data about their characteristics in the aggregate. Differences in exclusionary discipline patterns for children enrolled in CCEE programs with varying characteristics may also be of interest and may be identified by linking child and family level information to site level information.

Identify Children Who Experienced Suspensions or Expulsions from CCEE Programs

The data element Reason for removal from program is a Child Level data element that contains field names detailing the disciplinary actions experienced by children in CCEE settings, including “OSS (Out of School Suspension) less than 10 days”, “OSS (Out of School Suspension) greater than 10 days”, “ISS (In School Suspension) less than 10 days”, “ISS (In School Suspension) greater than 10 days”, and “Expulsion”. Children who were suspended and/or expelled can be identified by selecting children who have “Yes” values indicated in the option set for the “OSS less than 10 days”, “OSS greater than 10 days”, “ISS less than 10 days”, “ISS more than 10 days”, and “Expulsion” fields.

Identify Child and Family Level Characteristics of Interest

Characteristics from Child Level and Family Level data elements can be selected for analysis depending on the characteristics of interest. Child Gender, Child Race, and Primary Type of Disability are examples of Child Level data elements that may be of interest in answering this question. Family Income and Guardian’s Highest Level of Education are examples of Family Level data elements that may be of interest as well.  A full list of Child Level and Family Level data elements can be found in the data dictionary of this document.

Analyze Child Attendance Patterns by Child Characteristics of Interest

If family characteristics are of interest for analysis, Child Level and Family Level data elements can be linked together using Child ID and Family ID.  The characteristics of interest for children with values in any of these four fields can be used to answer this question.

Example 1. Is there a difference in proportion of children suspended by gender? To answer this question, group by the Child Gender data element and note the total count (Child ID) of each value type. Then, filter the data to only include children who have a “Yes” response to a Reason for Removal from Program field that corresponds to being suspended. Note the total count (Child ID) of children who were suspended by each Child Gender value type. For each gender category, divide the children suspended by the total children to obtain the proportion.

Example 2. Is there a difference in the proportion of expulsions experienced by children enrolled in different types of CCEE programs? To answer this question the Child Level data elements Early Childhood Program Type Enrollment and Reason for Removal from Program can be used. The field names for the Early Childhood Program Type Enrollment data element include program types such as Head Start, Public Preschool and Private Preschool, among others. The option set for each field name/program type is either “Yes” or “No”. An example of the coding that could be used is assigning a “1” to “Head Start”, a “2” to “Public Preschool”, and so on for each program where the option set for each field name (Program Type) is “Yes”. Once the type of CCEE program in which children are enrolled is organized or coded as desired, calculate the total number of children enrolled by counting the Child IDs for all children in the dataset. Then calculate the number of children who experienced expulsions from their CCEE program by counting the Child IDs for children that have a “Yes” value in the option set of the expulsion field for the Reason for Removal from Program data element. The child level data can then be filtered by each program type. Divide the number of children who experienced expulsions by the total number of children enrolled for each program type category and compare the values for all program type categories to determine if there are differences in expulsions between program types.