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Teaching Application: How a changing conditions design can be used in the classroom.

Mr, Woods was recently hired to teach physical education at an elementary school. When he arrived at work, Mr. Woods was approached by the special education teacher, Ms. Jones. She was concerned about Roberta, a student with physical disabilities who would be In Mr. Woods's gym class. Roberta, who used a wheelchair, had difficulty with eye-hand coordination. Ms. Jones hoped the student could learn to throw a basketball. Learning to play basketball would provide coordination training and a valuable leisure skill for Roberta. Mr. Woods agreed that the basketball skill seemed appropriate.
Mr. Woods decided to use a systematic approach to instruction. He asked Roberta to throw the basketball 20 times to see how often she could place the ball through a lowered hoop. This procedure was followed for five gym periods with no additional instruction until a baseline performance rate was determined. Mr. Woods then decided to use a modeling technique; he showed Roberta how to throw the ball and asked her to imitate him. Very little improvement was noted in five class periods. Mr. Woods met with the special education teacher to determine what could be done.

Ms. Jones carefully reviewed all the data and suggested changing the conditions. She explained that a change in intervention seemed necessary and that a modeling procedure could be used in combination with keeping score on a chart.

Mr. Woods agreed to try this. In 2 weeks, Roberta showed improvement but still missed more baskets than she hit. A final condition was implemented using modeling, scorekeeping, and a correction procedure. Mr. Woods now showed Roberta how to throw, recorded her score, and showed her exactly what she did wrong when she missed. This combination of procedures resulted in Roberta's being able to throw a basketball through a hoop 15 out of 20 times. A suggestion was made to Roberta's parents that a hoop be constructed at her home so that she could enjoy her new skill after school.

Advantages and Disadvantages

The changing conditions design with a single baseline allows the teacher to compare the effects of a number of interventions en student behavior. Although no functional relationship can be established, recording data in this format allows the teacher to monitor the effects of various procedures on student behavior. The teacher should be aware, however, that what she may be seeing is the cumulative effects of the interventions rather than the effects of any one intervention in isolation. Individual analysis of the effects of the interventions can be made using the repeated baselines format of the changing conditions design. The teacher who records data systematically in a changing conditions design will have a record of the student's progress and a good indication of what procedures are effective with that student.

The purpose for using behavior modification and applied behavior analysis techniques In the classroom is to achieve, and verify, meaningful changes in a student's behavior. The effectiveness of an intervention is commonly judged against both an experimental criterion and a therapeutic criterion. The experimental criterion verifies that an independent variable (an intervention) was responsible for the change in the dependent variable (a behavior). Single-subject designs demonstrating within-subject replications of effect satisfy this criterion (Baer, Wolf, & Risley, 1968; Barlow & Hersen, 1984 Kazdin, 1977).

The therapeutic criterion is a judgment as to whether the results of the teacher's intervention are "important or of clinical or applied significance" (Kazdin. 1982). For example, the teacher should ask herself whether it is truly meaningful to increase a student's grade from a D- to a D (Baer, Wolf, & Risley, 1968) or to decrease a child's self-destructive behavior from 100 to 60 instances per hour (Kazdin, 1977) or to reduce a student's off-task behavior in a resource room while it remains at high in the regular classroom. Kazdin (1977) suggests a third evaluation criterion: so do/ validation, the "social acceptability of an intervention program", Social validation was discussed at length in Chapter 2.
Intervention effects in applied behavior analysis are usually evaluated through visual/ inspection of the graph displaying the plotted data points of the various phases (conditions). Interpretation of data based on visual inspection sounds unrefined and may certainly be subjective. It may therefore be viewed by some as a weak form of evaluation. Evaluation resulting from visual inspection, however, reveals only strong intervention results, and that is what teachers are seeking.

The grossness and subjectivity of visual inspection are somewhat modified by common agreement that certain characteristics of the graphed data should be evaluated. These characteristics include the means of the data in the phases, the /eue/s of performance in the phases, the trends in performance, and the rapidity of behavior change (Kazdin, 1982).
Evaluation of changes in means focuses on the change in the average rate of student performance across the phases of a design. Within each phase, the mean (average) of the data points is determined and may be indicated on the graph by drawing a horizontal, dashed line corresponding to the value on the ordinate scale. Visual inspection of the relationship of these means will help determine if the intervention resulted in consistent and meaningful changes in the behavior in the desired direction of change.

Evaluation of the level of performance refers to the increase or decrease in student performance from the end of one phase to the beginning of the next phase. The teacher wants to evaluate the magnitude and direction of this change. When a large change in level occurs immediately after the introduction of a new condition, the level change is abrupt, which is indicative of a powerful or effective intervention" (Tawney & Gast, 1984). Tawney and Gast suggest the following steps to determine and evaluate a level change between two adjacent conditions; (1) identify the ordinate value of the last data point of the first condition and the first data point value of the second condition, (2) subtract the smallest value from the largest, and (3) note whether the change in level is in an improving or decaying direction.

Evaluation of a trend in performance focuses on systematic and consistent increases or decreases in performance. Data trends are most often evaluated using a procedure known as the quarter-intersect method (White & Liberty, 1976), Evaluation of trends is based on lines of progress developed from the median value of the data points in each phase. The use of a trend line increases the reliability of visual analysis among people looking at a graph (Bailey, 1984; Ottenbacher & Cusick, 1991). This is of particular importance as teams of teachers, students, parents, and other concerned individuals review student data to assess progress and make decisions about future instruction or intervention. Trend lines can provide (1) an indication of the direction of behavior change in the past and (2) a prediction of the direction of behavior change in the future. This information can help the teacher determine whether to change the Intervention.

Taking this process one step further will yield a split-middle line of progress (White & Haring, 1980). This line of progress is drawn so that an equal number of data points fall on and above the line as tall on and below the line.

A fourth characteristic that may be evaluated through visual inspection is the rapidity of the behavior change. This refers to the length of time between the onset or termination of one phase and changes in performance, The sooner the change occurs after the intervention has been applied (or with-drawn), the clearer the intervention effect. It should be noted that "rapidity of change is a difficult notation to specify because it is a joint function of changes in level and slope (trend).... A marked change in level and in slope usually reflects a rapid change" (Kazdin, 1982).

Although visual inspection is useful, convenient, and basically reliable for identifying or verifying strong intervention effects, much of the current published research using single-subject designs has accompanied visual inspection with statistical verification of effects (for example, t test, F test, R test, time series analysis). Kazdin (1976) offers three reasons to support the use of statistical techniques:

• To assist in distinguishing subtle effects from chance occurrence
• To analyze the effects of a treatment procedure when a stable baseline cannot be established
• To assess the treatment effects in environments that lack control

More information about advanced uses of visual inspection and especially about statistical evaluation in single-subject designs can be found in Barlow and Hersen (1984), Kazdin (1982), and Tawney and Gast (1984).