Library_writer 6 | - Freelance Writer
Aug 01, 2019 | #1
As a form of single-case designs, multiple baseline designs (MBDs) offer a range of advantages over group designs that are particularly conducive to special education. Affording researchers the valuable ability to investigate intervention implications at the level of individual students, MBDs counter the most negative outcome of group designs; that being, the loss of variation in individual effects during intervention (Ferron, Farmer & Owens, 2010). The following inquiry explores the three, basic types of MBDs, devoting particular attention to how these designs could be applied in a special education setting and, more saliently, how the efficacy of these designs could be measured.
In contrast to group designs which generally have only a single score for each participant that will be averaged during data analysis, MBDs have multiple data points. Large samples are not required, and, by extension, researchers can be more sensitive to the needs of participants. Ferron, Farmer, and Owens write "if patterns emerge such that the intervention is not effective, it can be modified. [T]hese designs reduce the gap between research and practice by allowing practitioners to implement research in their current settings" (p. 930). Because the contemporary field of special education and its employment of RTI frameworks demands that students be evaluated over time, MBDs are particularly and increasingly useful in the twenty-first century.
Researchers, educators, policymakers, and a range of other stakeholders are acknowledging that interventions are most effectively evaluated at the individual level (Ferron, Farmer & Owens, 2010). Allowing for the collection of multiple data sets within a single-case design, MBDs vary across behaviors, subjects, and settings. For example, an MBD across behaviors might examine students who speak without raising their hands, while an MBD across subjects might examine spelling accuracy for multiple students. Finally, an MBD across settings could explore a student's use of bad language during recess, the cafeteria, and in the classroom (Barger-Anderson et al).
MBDs across behaviors are used to demonstrate or explore the efficacy of an intervention employed to target various behaviors. Zirpoli (2008) cites that "comparisons are made between conditions employed during the behavior change program. A condition refers to the baseline phase and various intervention phases used to modify an individual's behavior; these are called baseline and intervention conditions" (p. 206). Baseline conditions, or condition A, are defined before an intervention is employed, while intervention conditions, or condition B, continues throughout the intervention condition (Zirpoli, 2008). In an across-behaviors design, a single intervention is applied to a student across different behaviors.
In expanding the aforementioned example, an MBD across behaviors might examine the efficacy of positive reinforcement on the related behaviors of not raising hands when speaking, interrupting the teacher, or having sidebar conversation in the classroom. For a student who has problems with these issues, a teacher might take a baseline assessment before intervention of all three behavior's frequency, then gradually introduce a positive reinforcement intervention for one behavior at a time, measuring the impact on one, two, and then all three behaviors. While obstacles to studying this intervention might include time consumption related to tracking intervention efficacy or an inability to explore other influences on behavior, the design would generally be successful in measuring the impact of the intervention on disruptive behavior.
MBDs across students explore the impact of an intervention on the same behavior across multiple participants. After the baseline is established for all participants, the intervention, which is the independent variable, is applied to one participant while the baseline is maintained for the other students. If improvement is assessed for one student, then the intervention will be introduced to another student. Barger-Anderson et.al. (2004) write "the reasoning behind this design is that if one participant shows improvement when treatment is started it is probable that improvement is due to the treatment. If gains were reflected in the other participants' behaviors even though they were in baseline, a conclusion could not be made that the independent variable was the most probable reason for the observed changes" (p. 217). The introduction of spelling flashcards might be measured in this way, with flashcards being used for one student after the baseline is set and then gradually introduced to other students if they prove effective. Obstacles include an inability to thoroughly assess outside forces that might affect the intervention.
Similarly, MBDs across settings study the effects of an intervention on the same student across different settings (Zirpoli, 2008). If a student consistently uses bad language, an MBD across settings might examine the impact of positive reinforcement on the students use of bad language during recess, in the cafeteria, and in the general education classroom, introducing the intervention in one setting at a time before moving on to the next. Obstacles to MBDs across settings include an inability to control the setting conditions. For example, a student may be influenced more by peers' behavior during recess than s/he is in the general education classroom, and this could have more impact on his/her behavior than the setting itself.
Conclusions
MBDs are preferable to group designs for a wide range of reasons, most of which are related to their ease of use. Because studying the impact of interventions is critical to the special education field, MBDs will likely increase in popularity as time goes on. By extension, an understanding of MBDs variations is critical for contemporary educators.
REFERENCES
Barger-Anderson, R., Domaracki, J. W., Kearney-Vakulick, N., & Kubina, R. M. (2004). Multiple Baseline Designs: The Use of a Single-Case Experimental Design in Literacy Research. Reading Improvement, 41(4), 217-230.
Ferron, J. M., Farmer, J. L., & Owens, C. M. (2010). Estimating Individual Treatment Effects from Multiple-baseline Data: a Monte Carlo Study of Multilevel-modeling Approaches. Behavior Research Methods, 42(4), 930-943.
Zirpoli, T. (2008). Behavior Management. New Jersey: Prentice Hall.
In contrast to group designs which generally have only a single score for each participant that will be averaged during data analysis, MBDs have multiple data points. Large samples are not required, and, by extension, researchers can be more sensitive to the needs of participants. Ferron, Farmer, and Owens write "if patterns emerge such that the intervention is not effective, it can be modified. [T]hese designs reduce the gap between research and practice by allowing practitioners to implement research in their current settings" (p. 930). Because the contemporary field of special education and its employment of RTI frameworks demands that students be evaluated over time, MBDs are particularly and increasingly useful in the twenty-first century.Types of MBDs
Researchers, educators, policymakers, and a range of other stakeholders are acknowledging that interventions are most effectively evaluated at the individual level (Ferron, Farmer & Owens, 2010). Allowing for the collection of multiple data sets within a single-case design, MBDs vary across behaviors, subjects, and settings. For example, an MBD across behaviors might examine students who speak without raising their hands, while an MBD across subjects might examine spelling accuracy for multiple students. Finally, an MBD across settings could explore a student's use of bad language during recess, the cafeteria, and in the classroom (Barger-Anderson et al).
MBDs across Behaviors
MBDs across behaviors are used to demonstrate or explore the efficacy of an intervention employed to target various behaviors. Zirpoli (2008) cites that "comparisons are made between conditions employed during the behavior change program. A condition refers to the baseline phase and various intervention phases used to modify an individual's behavior; these are called baseline and intervention conditions" (p. 206). Baseline conditions, or condition A, are defined before an intervention is employed, while intervention conditions, or condition B, continues throughout the intervention condition (Zirpoli, 2008). In an across-behaviors design, a single intervention is applied to a student across different behaviors.
In expanding the aforementioned example, an MBD across behaviors might examine the efficacy of positive reinforcement on the related behaviors of not raising hands when speaking, interrupting the teacher, or having sidebar conversation in the classroom. For a student who has problems with these issues, a teacher might take a baseline assessment before intervention of all three behavior's frequency, then gradually introduce a positive reinforcement intervention for one behavior at a time, measuring the impact on one, two, and then all three behaviors. While obstacles to studying this intervention might include time consumption related to tracking intervention efficacy or an inability to explore other influences on behavior, the design would generally be successful in measuring the impact of the intervention on disruptive behavior.
MBD Across Students
MBDs across students explore the impact of an intervention on the same behavior across multiple participants. After the baseline is established for all participants, the intervention, which is the independent variable, is applied to one participant while the baseline is maintained for the other students. If improvement is assessed for one student, then the intervention will be introduced to another student. Barger-Anderson et.al. (2004) write "the reasoning behind this design is that if one participant shows improvement when treatment is started it is probable that improvement is due to the treatment. If gains were reflected in the other participants' behaviors even though they were in baseline, a conclusion could not be made that the independent variable was the most probable reason for the observed changes" (p. 217). The introduction of spelling flashcards might be measured in this way, with flashcards being used for one student after the baseline is set and then gradually introduced to other students if they prove effective. Obstacles include an inability to thoroughly assess outside forces that might affect the intervention.
MBD Across Settings
Similarly, MBDs across settings study the effects of an intervention on the same student across different settings (Zirpoli, 2008). If a student consistently uses bad language, an MBD across settings might examine the impact of positive reinforcement on the students use of bad language during recess, in the cafeteria, and in the general education classroom, introducing the intervention in one setting at a time before moving on to the next. Obstacles to MBDs across settings include an inability to control the setting conditions. For example, a student may be influenced more by peers' behavior during recess than s/he is in the general education classroom, and this could have more impact on his/her behavior than the setting itself.
Conclusions
MBDs are preferable to group designs for a wide range of reasons, most of which are related to their ease of use. Because studying the impact of interventions is critical to the special education field, MBDs will likely increase in popularity as time goes on. By extension, an understanding of MBDs variations is critical for contemporary educators.
REFERENCES
Barger-Anderson, R., Domaracki, J. W., Kearney-Vakulick, N., & Kubina, R. M. (2004). Multiple Baseline Designs: The Use of a Single-Case Experimental Design in Literacy Research. Reading Improvement, 41(4), 217-230.
Ferron, J. M., Farmer, J. L., & Owens, C. M. (2010). Estimating Individual Treatment Effects from Multiple-baseline Data: a Monte Carlo Study of Multilevel-modeling Approaches. Behavior Research Methods, 42(4), 930-943.
Zirpoli, T. (2008). Behavior Management. New Jersey: Prentice Hall.