Positive Supports for Behavior and Discipline Resource Database

This table details key areas such as methodology, data sources, and reporting considerations for each of the three equity requirements in IDEA.

The Significant Disproportionality Calculator is a spreadsheet application that the IDEA Data Center (IDC) created to help states analyze their data, make determinations of significant disproportionality, and support local education agencies (LEAs) in their analysis of data for significant disproportionality at the school-level. The accompanying user’s guide describes each worksheet within the calculator, formatting requirements, and instructions for using the calculator.

This tool provides a summary of the data states need to calculate significant disproportionality in the areas of identification, placement, and discipline.

This document assists states with the collection of data on children with disabilities served under IDEA who were subject to disciplinary removal.

This TA guide describes some of the more common methods for calculating disproportionality. The intended audience is state agency staff who must make decisions regarding their state’s disproportionality analyses and those who analyze disproportionality data or interpret the results of those analyses.

Our November 15–16, 2022 SPP/APR Summit brought together data quality influencers from across the country for a chance to connect and collaborate with their peers as they continue to improve the quality of their state’s SPP/APR data. For all sessions, see https://ideadata.org/spp-apr-summit. This session focused on several of the important decisions needed to generate data for Indicator 4A and 4B, including comparison group, calculation method, minimum cell size, minimum n-size, and threshold. It also contrasted Indicator 4 with significant disproportionality requirements.

The Excel spreadsheet application and user's guide are tools to aid states in their assessment of racial/ ethnic disproportionality. The spreadsheet application calculates several disproportionality measures, including risk, risk ratio, weighted risk ratio, alternate risk ratio, risk difference, composition, difference in composition, relative difference in composition, the E-formula, and variations of several of these measures for total disciplinary removals.

Did your state receive OSEP comments for Indicator 4 in the FFY2021 SPP/APR submission? An increased focus on significant discrepancies in discipline not only challenges states to examine Indicator 4 but also makes the importance of attending to basics apparent. Understanding concepts like comparison group, calculation method, minimum cell and n-sizes, and threshold is prerequisite before a state examines “reasonably designed methodology” for Indicator 4. Join us to discuss these topics and more! You will leave the webinar with an awareness of the important decision points necessary for consideration when it comes to Indicator 4.

This infographic document outlines how districts can examine discipline data, including exclusionary practices, among subgroups of students, to create "risk ratios."

This resource guide provides technical assistance to state educational agencies to better understand data and fiscal requirements related to CEIS, including identifying the need for mandatory comprehensive CEIS or voluntary CEIS. This guide connects States to relevant resources in areas related to State and local implementation.

TIPS is a research-validated framework to use during any team meeting focused on data-driven decision making. In the TIPS model, every team needs a minute taker , a facilitator, a data analyst, and at least one additional person available to be a backup to these roles if anyone is absent.

Universal behavior screening data can be used with other school data to provide educators with valuable information about the overall level of students’ performance at Tier 1 as well as an indicator of students who may need additional supports. This brief presents guiding questions to interpret screening data in a three-step process: examine student performance for the school as a whole, consider teacher-delivered, low-intensity supports, and make decisions for students who might require Tier 2 and Tier 3 supports.

This guide is intended to be used in conjunction with the practices guide: Supporting and Responding to Students’ Social, Emotional, and Behavioral Needs: Evidence-Based Practices for Educators (Center on PBIS, 2022). It provides updated guidance on how to (a) develop systems to support educators’ implementation of evidence-based classroom practices and (b) use data to guide the development of implementation supports.

This Practice Brief discusses four core types of data needed by high school PBIS Leadership Teams and that these data can be used to problem-solve at the (a) whole school, (b) at-risk group, or (c) individual student levels.

Data informed decision making is an important component of classroom behavior systems. This session will explore how coaches can use data to support accuracy and fluency with classroom practices, including considerations for using data to support teacher use of effective practices for remote and hybrid models for schooling.