Journal of Behavioral Education

, Volume 17, Issue 2, pp 160–171 | Cite as

Using a High Probability Command Sequence to Increase Classroom Compliance: The Role of Behavioral Momentum

  • Phillip J. Belfiore
  • Sarah Pulley Basile
  • David L. Lee
Original Paper


One of the most problematic behaviors in children with developmental disabilities is noncompliance. Although behavioral research has provided strategies to impact noncompliance, oftentimes the methodologies are consequent techniques, which may not be conducive to implementation by the classroom teacher. In this teacher-designed and implemented study, a sequence of high-probability instructional commands preceded the targeted low-probability command, in an attempt to increase compliance to the low-probability command. Results, discussed within the body of behavioral momentum research, showed an increase in compliance to low-probability classroom commands for a seven year-old student with moderate mental retardation and Down Syndrome. Results are discussed as (a) an effective, antecedent approach to classroom compliance and (b) re-connecting the gap between applied behavioral research and experimentally controlled classroom practice.


Command compliance Behavioral momentum Down syndrome developmental disabilities High-probability command sequence 


  1. Ardoin, S. P., Martens, B. K., & Wolfe L. A. (1999). Using high-probability instruction sequences with fading to increase student compliance during transitions. Journal of Applied Behavior Analysis, 32, 339–351.CrossRefGoogle Scholar
  2. Austin, J. L., & Agar, G. (2005). Helping young children follow their teachers’ directions: The utility of high probability command sequences in pre-k and kindergarten classrooms. Education and Treatment of Children, 28, 222–236.Google Scholar
  3. Barlow, D. H., & Hersen, M. (1984). Single case experimental designs: Strategies for studying behavioral change. Boston: Allyn and Bacon.Google Scholar
  4. Belfiore, P. J., Lee, D. L., Scheeler, M. C., & Klien, D. (2002). Implications of behavioral momentum and academic achievement for students with behavioral disorders: Linking theory with practice. Psychology in the Schools, 39, 171–180.CrossRefGoogle Scholar
  5. Brandon, P. K., & Houlihan, D. (1997). Applying behavioral theory to practice: An examination of the behavioral momentum metaphor. Behavioral Interventions, 12, 113–131.CrossRefGoogle Scholar
  6. Davis, C. A., & Reichle, J. (1996). Variant and invariant high-probability requests: Increasing appropriate behaviors in children with emotional-behavioral disorders. Journal of Applied Behavior Analysis, 29, 471–482.PubMedCrossRefGoogle Scholar
  7. Ducharme, J. M., & DiAdamo, C. (2005). An errorless approach to management of child noncompliance in a special education setting. School Psychology Review, 34, 107–115.Google Scholar
  8. Hutchinson, J. M., & Belfiore, P. J. (1998). Adding a sequence of high-preference mathematic problems to increase low-preference mathematics problems performance. Proven Practices, 1, 12–16.Google Scholar
  9. Laraway, S., Snycerski, S., Michael, J., & Poling, A. (2003). Motivating operations and terms to describe them: Some further refinements. Journal of Applied Behavior Analysis, 36, 407–414.PubMedCrossRefGoogle Scholar
  10. Lee, D. L., (2006). Facilitating academic transitions: An application of behavioral momentum. Remedial and Special Education, 27, 312–317.CrossRefGoogle Scholar
  11. Lee, D. L., Belfiore, P. J., Ferko, D., Hua, Y., Carranza, M., & Hildebrand, K. (2006). Using pre and post low-p latency to assess behavioral momentum: A preliminary investigation. Journal of Behavioral Education, 15, 203–214.CrossRefGoogle Scholar
  12. Lee, D. L., Belfiore, P. J., & Gormley, S. (in press). I don’t wanna: Creating a momentum of school success. Teaching Exceptional Children.Google Scholar
  13. Lee, D. L., Belfiore, P. J., Scheeler, M. C., Hua, Y., & Smith, R. (2004). Behavioral momentum in academics: Using embedded high-p sequence to increase academic productivity. Psychology in the Schools, 41, 789–801.CrossRefGoogle Scholar
  14. Mace, F. C. (1994). Basic research needed for stimulating the development of behavioral technologies. Journal of the Experimental Analysis of Behavior, 61, 529–550.PubMedCrossRefGoogle Scholar
  15. Mace, F. C., & Belfiore, P. J. (1990). Behavioral momentum in the treatment of escape-motivated stereotypy. Journal of Applied Behavioral Analysis, 23, 507–514.CrossRefGoogle Scholar
  16. Mace, F. C., Hock, M. L., Lalli, J. S., West, B. J., Belfiore, P., Pinter, E., & Brown, D. K. (1988). Behavioral momentum in the treatment of noncompliance. Journal of Applied Behavior Analysis, 21, 123–141.PubMedCrossRefGoogle Scholar
  17. Michael, J. L., (1980). Flight from behavior analysis. The Behavior Analyst, 3, 1–24.Google Scholar
  18. Nevin, J. A., (1996). The momentum of compliance. Journal of Applied Behavior Analysis, 29, 535–547.PubMedCrossRefGoogle Scholar
  19. Nevin, J. A., Mandell, C., & Atak, J. (1983). The analysis of behavioral momentum. Journal of the Experimental Analysis of Behavior, 39, 49–59.PubMedCrossRefGoogle Scholar
  20. Olmi, D. J., Sevier, R. C., & Nastasi, D. F. (1997). Time-in/time-out as a response to noncompliance and inappropriate behavior with children with developmental disabilities: Two case studies. Psychology in the Schools, 34, 31–39.CrossRefGoogle Scholar
  21. Wilder, D. A., & Carr, J. E. (1998). Recent advances in the modification of establishing operations to reduce aberrant behavior. Behavioral Interventions, 13, 43–59.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Phillip J. Belfiore
    • 1
  • Sarah Pulley Basile
    • 2
  • David L. Lee
    • 3
  1. 1.Department of EducationMercyhurst CollegeErieUSA
  2. 2.Millcreek Township School DistrictErieUSA
  3. 3.The Pennsylvania State UniversityUniversity ParkUSA

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