Go Beyond Compliance: Use Individualized Education Programs to Answer Strategic Questions and Improve Programs

Adrienne D. Woods, SRI International
Marie C. Ireland, Charles Sturt University
Kimberly A. Murphy, Old Dominion University
Hope Sparks Lancaster, Boys Town National Research Hospital


Purpose: The most significant document to ensure effective and compliant design, implementation, monitoring, and enforcement of a program of special education services in the United States is the Individualized Education Program (IEP). Although IEPs have been used to document procedural compliance with the Individuals with Disabilities Education Act (IDEA) for individual students, IEPs also provide extensive data that can and should be used by a variety of stakeholders including speech-language pathologists (SLPs), school administrators, and state education agencies to design targeted professional development and collectively improve programs, processes, and outcomes in special education.

Method: We summarize existing literature on the use of IEP data and describe opportunities to use IEP data to analyze individual student service patterns and SLP practice patterns. Aggregated IEP data also provide a robust view of district-wide and state trends in eligibility rates and least restrictive environment settings. Information on current and potential IEP data uses, reflection questions for substantive compliance, and lessons learned from a large-scale analysis of IEP data are provided. These lessons include potential software adjustments to enhance usability as a data source for substantive compliance; program improvement; and monitoring individual, school-wide, and districtwide outcomes.

Conclusions: IEP data are a rich data source of information that may be used to (a) identify trends; (b) assist schools, districts, and states with ensuring substantive compliance with IDEA; (c) examine service equity and efficacy; (d) identify professional development needs; and (e) identify promising practices and provide opportunities to use real-time data to improve models and address public policy.