Advertisement

Journal of Behavioral Education

, Volume 28, Issue 4, pp 435–455 | Cite as

Using Brief Experimental Analysis to Identify the Right Math Intervention at the Right Time

  • Joshua A. MellottEmail author
  • Scott P. Ardoin
Original Paper

Abstract

Brief experimental analysis (BEA) is a methodology of rapidly implementing interventions and observing the effect each has on student performance. Extensive research exists demonstrating the utility of BEA in identifying effective reading interventions for students, but comparatively little research exists regarding BEA and mathematics. The current study utilized BEA procedures to identify an intervention targeting skill- or performance-based deficits that would be effective for remediating 4 middle school students’ two-digit by two-digit multiplication skills. Each student had a clearly differentiated intervention identified by BEA as being most effective. Findings from the current study provide evidence for the utility of BEA in matching deficits with mathematics interventions and illustrate their sensitivity to changes in student performance.

Keywords

Brief experimental analysis Math interventions Skill-based deficits Performance-based deficits Cover copy compare 

Notes

References

  1. Ardoin, S. P., & Daly, E. J. (2007). Introduction to the special series: Close encounters of the instructional kind—How the instructional hierarchy is shaping instructional research 30 years later. Journal of Behavioral Education,16(1), 1–6.CrossRefGoogle Scholar
  2. Burns, M. K., Codding, R. S., Boice, C. H., & Lukito, G. (2010). Meta-analysis of acquisition and fluency math interventions with instructional and frustration level skills: Evidence for a skill-by-treatment interaction. School Psychology Review,39(1), 69.Google Scholar
  3. Burns, M. K., VanDerHeyden, A. M., & Jiban, C. L. (2006). Assessing the instructional level for mathematics: A comparison of methods. School Psychology Review,35, 401–418.Google Scholar
  4. Burns, M. K., & Wagner, D. (2008). Determining an effective intervention within a brief experimental analysis for reading: A meta-analytic review. School Psychology Review,37(1), 126–136.Google Scholar
  5. Carson, P. M., & Eckert, T. L. (2003). An experimental analysis of mathematics instructional components: Examining the effects of student-selected versus empirically-selected interventions. Journal of Behavioral Education,12(1), 35–54.CrossRefGoogle Scholar
  6. Codding, R. S., Baglici, S., Gottesman, D., Johnson, M., Kert, A. S., & Lebeouf, P. (2009). Selecting intervention strategies: Using brief experimental analysis for mathematics problems. Journal of Applied School Psychology,25(2), 146–168.CrossRefGoogle Scholar
  7. Codding, R. S., Eckert, T. L., Fanning, E., Shiyko, M., & Solomon, E. (2007). Comparing mathematics interventions: The effects of cover-copy-compare alone and combined with performance feedback on digits correct and incorrect. Journal of Behavioral Education,16(2), 125–141.CrossRefGoogle Scholar
  8. Common Core State Standards Initiative. (2017). Grade 4. http://www.commoncore.org. Accessed 2 Dec 2016.
  9. Daly, E. J., III, Lentz, F. E., Jr., & Boyer, J. (1996). The instructional hierarchy: A conceptual model for understanding the effective components of reading interventions. School Psychology Quarterly,11(4), 369–386.  https://doi.org/10.1037/h0088941.CrossRefGoogle Scholar
  10. Daly, E. J., Martens, B. K., Hamler, K. R., Dool, E. J., & Eckert, T. L. (1999). A brief experimental analysis for identifying instructional components needed to improve oral reading fluency. Journal of Applied Behavior Analysis,32(1), 83–94.CrossRefGoogle Scholar
  11. Daly, E. J., Murdoch, A., Lillenstein, L., Webber, L., & Lentz, F. E. (2002). An examination of methods for testing treatments: Conducting brief experimental analyses of the effects of instructional components on oral reading fluency. Education and Treatment of Children,25(3), 288–316.Google Scholar
  12. Daly, E. J., Witt, J. C., Martens, B. K., & Dool, E. J. (1997). A model for conducting a functional analysis of academic performance problems. School Psychology Review,26(4), 554.Google Scholar
  13. Deno, S. L., & Mirkin, P. K. (1977). Data-based program modification: A manual. Reston: Council for Exceptional Children.Google Scholar
  14. Duhon, G. J., Noell, G. H., Witt, J. C., Freeland, J. T., Dufrene, B. A., & Gilbertson, D. N. (2004). Identifying academic skill and performance deficits: The experimental analysis of brief assessments of academic skills. School Psychology Review,33(3), 429–443.Google Scholar
  15. Fuchs, L. S., & Fuchs, D. (1993). Formative evaluation of academic progress: How much growth can we expect? School Psychology Review,22, 27–49.Google Scholar
  16. Gilbertson, D., Witt, J. C., Duhon, G., & Dufrene, B. (2008). Using brief assessments to select math fluency and on-task behavior interventions: An investigation of treatment utility. Education and Treatment of Children,31(2), 167–181.CrossRefGoogle Scholar
  17. Harding, J., Wacker, D. P., Cooper, L. J., Millard, T., & Jensen-Kovalan, P. (1994). Brief hierarchical assessment of potential treatment components with children in an outpatient clinic. Journal of Applied Behavior Analysis,27(2), 291–300.  https://doi.org/10.1901/jaba.1994.27-291.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Haring, N. G. (1978). The fourth R: Research in the classroom (p. 1978). Columbus: C.E. Merrill.Google Scholar
  19. Hendrickson, J. M., Gable, R. A., Novak, C., & Peck, S. (1996). Functional assessment as strategy assessment for teaching academics. Education and Treatment of Children,19(3), 257–271.Google Scholar
  20. Joseph, L. M., Konrad, M., Cates, G., Vajcner, T., Eveleigh, E., & Fishley, K. M. (2012). A meta-analytic review of the cover-copy-compare and variations of this self-management procedure. Psychology in the Schools,49(2), 122–136.  https://doi.org/10.1002/pits.20622.CrossRefGoogle Scholar
  21. Koscinski, S. T., & Gast, D. L. (1993). Use of constant time delay in teaching multiplication facts to students with learning disabilities. Journal of Learning Disabilities,26(8), 533–544, 567.CrossRefGoogle Scholar
  22. Martens, B. K., & Gertz, L. E. (2009). Brief experimental analysis: A decision tool for bridging the gap between research and practice. Journal of Behavioral Education,18(1), 92–99.CrossRefGoogle Scholar
  23. McComas, J. J., & Burns, M. K. (2009). Brief experimental analyses of academic performance: Introduction to the special series. Journal of Behavioral Education,18(1), 1–4.CrossRefGoogle Scholar
  24. Mong, M. D., & Mong, K. W. (2012). The utility of brief experimental analysis and extended intervention analysis in selecting effective mathematics interventions. Journal of Behavioral Education,21(2), 99–118.CrossRefGoogle Scholar
  25. National Assessment of Educational Progress. (2015). National assessment of educational progress mathematics assessment. Washington, D.C.: U.S. Department of Education, Institute of Educational Sciences, National Center for Education Statistics.Google Scholar
  26. National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the national mathematics advisory panel. Washington, D.C.: US Department of Education.Google Scholar
  27. National Research Council. (2001). Adding it up. Washington, D.C.: National Academy Press.Google Scholar
  28. Poncy, B. C., Skinner, C. H., & Jaspers, K. E. (2007). Evaluating and comparing interventions designed to enhance math fact accuracy and fluency: Cover, copy, and compare versus taped problems. Journal of Behavioral Education,16, 27–37.CrossRefGoogle Scholar
  29. Reisener, C. D., Dufrene, B. A., Clark, C. R., Olmi, D. J., & Tingstrom, D. H. (2016). Selecting effective interventions to increase math computation fluency via brief experimental analyses. Psychology in the Schools,53(1), 39–57.CrossRefGoogle Scholar
  30. Shapiro, E. S. (2011). Academic skills problems: Direct assessment and intervention (4th ed.). New York: Guilford Press.Google Scholar
  31. Shinn, M. R. (1989). Curriculum-based measurement: Assessing special children. New York: Guilford Press.Google Scholar
  32. Skinner, C. H. (1998). Preventing academic skills deficits. In T. S. Watson, F. M. Gresham, T. S. Watson, & F. M. Gresham (Eds.), Handbook of child behavior therapy (pp. 61–82). New York: Plenum Press.CrossRefGoogle Scholar
  33. Skinner, C. H., Beatty, K. L., Turco, T. L., & Rasavage, C. (1989). Cover, copy, and compare: A method for increasing multiplication performance. School Psychology Review,18(3), 412–420.Google Scholar
  34. Tillema, E. S. (2009). Cultivating an area model. Mathematics in the Middle School,15(3), 142–147.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Educational Psychology, Center for Autism and Behavioral Education ResearchUniversity of GeorgiaAthensGeorgia

Personalised recommendations