Foundation for Success
The baseline data you collect in the first week becomes the comparison point for everything that follows. Accurate baselines make intervention decisions clearer and progress more visible.
What Is Baseline Data?
Baseline data captures behavior patterns BEFORE you implement any intervention. It answers the question: "What is the current level of behavior without any systematic support?"
Critical Distinction
If you start intervening immediately, you have no baseline. Without baseline data, you cannot demonstrate that your intervention caused the change - the behavior might have changed on its own.
First Week Collection Strategy
Days 1-2: Observe and Identify
Watch for patterns. Which behaviors are most concerning? When do they occur? Do not start formal data collection yet - just observe.
Days 3-5: Formal Baseline Collection
Select 2-3 target behaviors. Define them clearly. Collect data consistently across settings and times.
End of Week 1: Analyze and Plan
Review your baseline data. Identify patterns. Begin planning intervention based on what the data shows.
What to Measure
Frequency
How many times does the behavior occur? Best for discrete behaviors with clear start and end.
Duration
How long does each episode last? Best for behaviors like tantrums, off-task, or work refusal.
Latency
How long between instruction and compliance? Best for following directions or transition behaviors.
Intensity
How severe is the behavior? Use a rating scale (1-5) for behaviors like aggression or property destruction.
First Week Environmental Factors
Document these factors that may affect your baseline:
- ☐ New classroom, new teacher, new peers (adjustment period)
- ☐ Schedule not yet established (transitions unpredictable)
- ☐ Academic demands may be lighter than typical
- ☐ Student may be on "honeymoon" best behavior
- ☐ Summer regression may inflate problem behaviors
Patience Pays Off
It is tempting to start intervening immediately when you see challenging behavior. Resist this urge for at least 3-5 days. The baseline data you collect will make your interventions more targeted and your progress more measurable.
References
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
Simonsen, B., Fairbanks, S., Briesch, A., Myers, D., & Sugai, G. (2008). Evidence-based practices in classroom management: Considerations for research to practice. Education and Treatment of Children, 31(3), 351–380. https://doi.org/10.1353/etc.0.0007
Stormont, M., Reinke, W. M., Newcomer, L., Marchese, D., & Lewis, C. (2015). Coaching teachers’ use of social behavior interventions to improve children’s outcomes: A review of the literature. Journal of Positive Behavior Interventions, 17(2), 69–82. https://doi.org/10.1177/1098300714550657
Carr, E. G., Dunlap, G., Horner, R. H., Koegel, R. L., Turnbull, A. P., Sailor, W., Anderson, J. L., Albin, R. W., Koegel, L. K., & Fox, L. (2002). Positive behavior support: Evolution of an applied science. Journal of Positive Behavior Interventions, 4(1), 4–16. https://doi.org/10.1177/109830070200400102
Sugai, G., & Horner, R. H. (2020). Sustaining and scaling positive behavioral interventions and supports: Implementation drivers, outcomes, and considerations. Exceptional Children, 86(2), 120–136. https://doi.org/10.1177/0014402919855331
Take Action
Put what you've learned into practice with these resources.
Key Takeaways
- Baseline data should be collected BEFORE any intervention begins
- Focus on 2-3 key behaviors rather than trying to track everything
- Collect data across multiple settings and times of day
- Document environmental factors that may affect early behavior
- Baseline period typically lasts 3-5 school days minimum
Ready to Transform Your Classroom?
See how Classroom Pulse can help you streamline behavior data collection and support student outcomes.
Download Baseline Collection TemplateFree for up to 3 students • No credit card required
About the Author
Dr. Sarah Mitchell consists of former Special Education Teachers and BCBAs who are passionate about leveraging technology to reduce teacher burnout and improve student outcomes.
Related Articles
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.
Trauma-Informed Behavior Approaches: Reframing Challenging Behaviors Through a Healing Lens
Understand how trauma impacts student behavior and learn evidence-based approaches for supporting trauma-exposed students. Discover how to adapt FBA/BIP practices and create healing-centered classroom environments.
MTSS Framework: Integrating FBA and BIP Across All Tiers for Maximum Student Success
Learn how to effectively integrate Functional Behavioral Assessment (FBA) and Behavior Intervention Plans (BIP) within a Multi-tiered System of Supports (MTSS) framework. Discover best practices for data-driven decision making at each tier.
