As spring approaches, IEP teams across the country face one of special education's most consequential decisions: Does this student qualify for Extended School Year (ESY) services? The answer should be grounded in data that demonstrates regression and recoupment patterns.
Understanding ESY Eligibility
Extended School Year services are required under IDEA when a student experiences significant regression during breaks that impairs their ability to benefit from their educational program.
Key Legal Standard
ESY services must be provided when necessary to provide FAPE. The question is not whether summer services would be beneficial, but whether the student will lose critical skills without them.
The Regression/Recoupment Standard
Regression refers to the loss of skills during breaks. Recoupment refers to the time needed to return to pre-break performance. Excessive recoupment time is often more significant than regression itself.
| Measure | Typical | Significant |
|---|---|---|
| Skill Level | 10-20% decrease | 30%+ decrease |
| Behavior Frequency | 1.5x increase | 2x+ increase |
| Recoupment Time | 2-4 weeks | 6+ weeks |
Data Collection Timeline
2 Weeks Before Each Break
Establish clear baseline data for target behaviors.
First Day Back
Resume data collection immediately. Document post-break performance.
Daily Until Recoupment
Track until student returns to baseline. Count the days.
The Bottom Line
ESY decisions should be based on data. Start collecting regression and recoupment data at winter break. When your data tells a compelling story, ESY decisions become clear and defensible.
References
McMahon, J. (1994). Extended school year: New directions and implications for school social workers. Children & Schools, 16(4), 231–239. https://doi.org/10.1093/cs/16.4.231
Barnard-Brak, L., & Stevens, T. (2021). Criteria for determining eligibility for extended school year services. Journal of Special Education, 55(1), 3–12.
Burke, M. M., & Decker, J. R. (2017). Extended school year: Legal and practical considerations for educators. Teaching Exceptional Children, 49(5), 339–346.
U.S. Department of Education. (2017). Sec. 300.106 extended school year services. https://sites.ed.gov/idea/regs/b/b/300.106
Briesch, A. M., Chafouleas, S. M., & Riley-Tillman, T. C. (2016). Direct behavior rating: Linking assessment, communication, and intervention. Guilford Press.
Chafouleas, S. M., Kilgus, S. P., Riley-Tillman, T. C., Jaffery, R., Christ, T. J., Briesch, A. M., Chanese, J. A. M., & Kalymon, K. M. (2013). An evaluation of the generalizability of direct behavior rating single-item scales to measure academic engagement across raters and observations. School Psychology Review, 42(4), 407–421.
Volpe, R. J., & Briesch, A. M. (2012). Generalizability and dependability of single-item and multiple-item direct behavior rating scales for engagement and disruptive behavior. School Psychology Review, 41(3), 246–261.
Smith, T. E., Thompson, A. M., & Maynard, B. R. (2022). Self-management interventions for reducing challenging behaviors among school-age students: A systematic review. Campbell Systematic Reviews, 18(1), e1223. https://doi.org/10.1002/cl2.1223
Ruble, L. A., McGrew, J. H., Wong, W. H., & Missall, K. N. (2018). Special education teachers' perceptions and intentions toward data collection. Journal of Early Intervention, 40(2), 177–191. https://doi.org/10.1177/1053815118771391
Take Action
Put what you've learned into practice with these resources.
Key Takeaways
- ESY eligibility is based on regression and recoupment data, not just severity of disability
- Begin collecting regression data after winter and spring breaks to establish patterns
- Document both behavioral and academic regression with specific, measurable data
- Recoupment time is equally important - track how long it takes to return to pre-break levels
- Strong ESY justifications connect behavior regression to educational impact
ESY Data Collection Template
Complete framework for tracking regression and recoupment to support ESY decisions
Tags:
Ready to Transform Your Classroom?
See how Classroom Pulse can help you streamline behavior data collection and support student outcomes.
Track Regression DataFree for up to 3 students • No credit card required
About the Author
The Classroom Pulse Team consists of former Special Education Teachers and BCBAs who are passionate about leveraging technology to reduce teacher burnout and improve student outcomes.
Related Articles
De-escalation Techniques: Preventing Behavioral Crises in the Classroom
Learn evidence-based de-escalation strategies to prevent behavioral crises before they occur. Discover early warning signs, verbal and non-verbal techniques, and how to create effective crisis prevention plans.
Autism-Specific Behavior Strategies: Evidence-Based Approaches for the ASD Classroom
Discover evidence-based behavior strategies designed specifically for autistic learners. Learn about sensory considerations, communication-based interventions, and how to adapt FBA practices for students on the autism spectrum.
Self-Monitoring: Teaching Students to Track Their Own Behavior
Learn how to implement student self-monitoring programs that build self-awareness, independence, and self-regulation skills. Discover age-appropriate strategies and technology tools for effective self-monitoring.