School of Social and Behavioral Sciences Assignment Guide COURSE #           1 Areas shaded in gray connect to a CLA/GEL. Grading Criteria Points Points Possible Earned Content Conduct a Functional Behavior Assessment that includes the following: 0-40 a) Indirect Assessment (Interview and Intake Information; utilize forms found in Doc Sharing) b) Direct Observation • • • • Operationally define target behavior Conduct an A-B-C Assessment Chart the rate of the target behavior according to date Hypothesize the function of the target behavior based upon the results of the A-B-C Assessment data Design a Function-Based, Individualized, Behavior Intervention Plan (BIP) and Evaluate the Effectiveness of the BIP: 0-40 a) Based upon your knowledge of the threeterm contingency and operant behavior, design a BIP. b) Evaluate the effectiveness of your intervention after 1-week and after 2-weeks using baseline and intervention data. Summarize the Assessment, Intervention, and Evaluation Process: a) Provide a summary, in essay form, of the steps in the FBA, BIP, and Evaluation process. b) Include a discussion of the purpose and importance of each step. C) Attach the following forms to the end of your paper, after the reference page: 0-40 • • • Interview and Intake Forms A-B-C data sheet(s) Rate chart of target behaviors during baseline, Week 1 Treatment, and Week 2 Treatment Writing Structure: 0-15 Paper includes a title page, introduction with thesis statement, conclusion, and in-text citations and reference page using APA style. Paper is appropriate in length (body of the paper should be 3–4 pages, not including the title page or reference page). Paper includes reference to the text book and any other academic sources used. Mechanics: 0-15 Paper uses Standard American English including correct grammar, spelling, and punctuation, and complete sentences and paragraphs. Paper is free of typographical errors. Paper includes a highly developed viewpoint and purpose. Paper demonstrates superior organization; communication is highly ordered, logical, and unified. Total An explanation of the points earned, as well as where the Assignment could be strengthened will be included with your grade. 150 Single-Subject Design After reading this chapter, you should be able to do the following: • Explain the purpose of single-subject designs. • Define baseline data and intervention data. • Describe the level, trend, and variability of behavior data and their importance for the analysis of data from a single-subject design. • Analyze the level, trend, and variability of baseline and intervention data. • Describe the different types of single-subject designs and discuss the advantages and disadvantages of each. Purpose of Single-Subject Design Once implemented, intervention strategies need to be evaluated for their effectiveness in modifying the target behavior. The strategies included in behavior intervention plans, in particular, should be evaluated on a continuous basis (Etscheidt, 2006; Maag & Katsiyannis, 2006). A number of different methods may be used to evaluate the effectiveness of intervention strategies, but only a few enable an assessment of the functional relationship between the behavior and the intervention. If a functional relationship does not exist between the behavior and the intervention, the intervention will most likely be ineffective, or it may actually exacerbate the behavior through ineffective reinforcement. Single-subject designs allow teachers to measure the effectiveness of intervention strategies for the specific behavior of one student or a group of students treated as one entity. For example, each data point on a single-subject design graph represents the behavior of a single student or the behavior of a group of students. The teacher can measure the effectiveness of the intervention by comparing the data points of the behavior prior to intervention with the data points of the behavior during intervention. Single-subject designs require repeated measures of the target behavior (dependent variable) and repeated measures of the behavior during the intervention strategy (independent variable) designed to modify the behavior. Single-subject designs have been used successfully to demonstrate the effectiveness of intervention strategies for students with behavioral, social, emotional, and academic difficulties. For example, Katz and Girolametto (2013) used a single-subject design to demonstrate the effectiveness of an intervention designed to increase interactions between students with autism spectrum disorders and their peers. Another study using a single-subject design demonstrated a functional relationship between academic choice and academic performance among students with emotional and behavioral disorders (Skerbetz & Kostewicz, 2013). Yet another study used a single-subject design to demonstrate the effectiveness of listening to music as a reinforcer for the verbal and physical behaviors of a student with severe ADHD (Nolan & Filter, 2012). Single-subject designs have been used extensively in education to compare the effects of interventions on behavior (Shabani & Lam, 2013), but most studies involving such designs have been conducted in the field of special education. However, if teachers are to develop an effective universal design for classroom management, many strategies currently used primarily in special education need to be implemented in general education classrooms. One such strategy is the use of single-subject designs to determine the effectiveness of interventions developed for students without disabilities. Baseline Data and Intervention Data The first step in implementing a single-subject design is to collect and record baseline data. Baseline data, or data on Condition A, consist of information collected on the student’s target behavior, usually during the functional behavioral assessment. Baseline data establish a benchmark against which the student’s behavior can be compared when subsequent interventions are introduced, enabling evaluation of the interventions’ effectiveness (Byiers, Reichle, & Symons, 2012). For example, the data obtained during Jane’s functional behavioral assessment (see Chapter 8) are baseline data. Baseline data describe the student’s existing behavior prior to any intervention. The baseline data also let the teacher know whether the target behavior is appropriate for intervention (see Figure 11.1). For example, on a systematic visual representation, or graph, of Jane’s baseline data, if the line representing her behavior is descending, this would indicate that the frequency of the target behavior is decreasing. If the inappropriate behavior is decreasing, intervention for the behavior is not necessary. Conversely, if the line representing her behavior is ascending, this means that the frequency of the behavior is increasing. However, the ascending data path also indicates that the behavior is changing, and the teacher needs to determine why the behavior is changing. Is the behavior getting worse, or are the data inaccurate because of a poor operational definition of the target behavior? Additionally, if the target behavior is changing, this may make it difficult for the teacher to determine the effectiveness of any interventions implemented to change the behavior, given that it would not be clear whether the changes are related to the intervention or to other variables. However, if the target behavior is worsening, the teacher may need to implement an intervention strategy immediately, especially if the behavior is severely disruptive or dangerous. Such a case often calls for a reactive strategy that results in time-out or an office referral. It is important for teachers to remember that while proactive intervention strategies are desirable, reactive strategies are sometimes necessary to maintain a safe and secure learning environment. Finally, a variable baseline indicates highly unstable data. The data points do not fall within a narrow range of values, which means that observed incidents of the target behavior does not occur consistently. For example, Jane exhibits her target behavior seven times during one observation period, two times during another period, and five times during a third. When a variable baseline is found, the teacher should not introduce an intervention strategy. Generally, an unstable baseline indicates that environmental variables are affecting the student’s behavior, and those variables need to be identified before an intervention can be developed. Figure 11.1 Types of Baseline Data A stable baseline shows no descending or ascending trend, and the data points fall within a small range of values. A stable baseline provides the best context for determining if an intervention strategy is effective. Measurement of the target behavior should continue until a consistent pattern occurs. Usually, a minimum of five baseline data points are needed to establish stability of the target behavior (Horner, Swaminathan, Sugai, & Smolkowski, 2012). For example, Jane’s data path indicates minor descending and ascending data points, and the behavior is relatively stable between five and seven incidents per observation. A stable baseline indicates that the target behavior is neither decreasing nor increasing prior to intervention and provides confidence that any change in the target behavior during and after intervention is a result of the effects of the intervention strategy. Once a stable baseline has been established, the next step is to implement the prescribed intervention strategy, often as part of a behavior intervention plan. The teacher observes, measures, and records the target behavior under the intervention strategy. The data collected during this period are the intervention data, or Condition B data. These data are plotted on a graph in the same manner as the baseline data. A single-subject design compares the baseline data and the intervention data to reveal any changes in the target behavior. Visual analysis of the baseline and intervention data usually involves examination of the level, trend, and variability of observed behaviors. Level, Trend, and Variability Once the baseline and intervention data have been collected and charted on a graph, the teacher can examine changes in the target behavior along one or more of three parameters: level, trend, and variability (Byiers et al., 2012). Level is the average rate of the behavior during a condition. For example, in the top graph in Figure 11.2, Jane’s level during the baseline is higher than that found during the intervention. Trend is a consistent one-direction change (increasing or decreasing) in the rate of the behavior during a condition. The middle graph in Figure 11.2 shows a consistent decrease in Jane’s inappropriate behavior during the intervention. Variability is fluctuation in the rate of the behavior during a condition. In the bottom graph in Figure 11.2, an obvious degree of variability can be seen in the baseline condition. The variability of the baseline has a minimum of three observed incidents per observation to a maximum of eight observed incidents per observation. This is a difference, or range, of five observed incidents (8 – 3 = 5). The intervention has a minimum of two observed incidents per observation to a maximum of three incidents per observation. This is a range of one observed incident (3 – 2 = 1). The teacher also needs to examine three other factors of level, trend, and variability of behavior to determine if there is a functional relationship between the behavior and the intervention: (a) the immediacy of the change of behaviors following a condition, (b) any overlap of data points between conditions, and (c) the degree of changes in the behaviors (Horner, Carr, Halle, Odom, & Wolery, 2005). For example, the level (top) graph in Figure 11.2 shows that the change between the baseline and the intervention occurred immediately. Also, the difference between the baseline condition and the intervention condition is especially evident since the two conditions do not overlap; the lowest baseline data point (5) is higher than the highest intervention data point (2). However, the trend (middle) graph in Figure 11.2 shows overlapping data points, and the change in behaviors between the baseline and intervention was not immediate. Yet there is an obvious descending trend and a degree of change in the behaviors. In the variability (bottom) graph in Figure 11.2, there is obvious evidence of change. Despite overlapping data points, the baseline condition is unstable, while the intervention condition is stable. The level in this graph also indicates evidence of change. Teachers can choose among several types of single-subject designs to measure the effectiveness of interventions. The type a teacher should select depends on the number, sequence, and various baseline and intervention conditions. The various types of singlesubject designs are the AB design, the withdrawal design, the alternating treatment design, the changing criterion design, and the multiple-baseline design. Types of Single-Subject Designs The AB Design The basic single-subject design is known as the AB design because it uses one set of baseline data (Condition A) and one set of intervention data (Condition B). The first step is to collect baseline data on the existing target behavior. Once the teacher has established a stable baseline, the intervention strategy is implemented and data are collected on the behavior under the intervention. The baseline data and the intervention data are charted and compared for any changes in the behavior. For example, baseline data have been collected on Jane’s target behavior (talking without permission). As a consequence of her behavior, each time Jane talks without permission, she has to write five times “I will not talk without permission.” The teacher implements the intervention strategy and measures and records the data points of the behavior under the intervention on a graph as depicted in Figure 11.3. The baseline data and the intervention data are separated by the condition change line, which is the vertical dotted line drawn upward from the abscissa (horizontal axis). Additionally, condition labels are printed at the top of the graph to identify the baseline data and the intervention data. Figure 11.2 Level, Trend, and Variability of Behavior Changes Visual inspection of the graph reveals that the intervention strategy (writing five lines) did not affect Jane’s behavior. There was no change in level, trend, or variability. There was no immediate change of behavior under the condition, data points overlapped between baseline and intervention, and there was no degree of change in behavior. However, one should be cautious when making assumptions based on the AB design. While the AB design is the easiest kind of single-subject design for teachers to implement, it cannot accurately determine the effectiveness of an intervention because it does not provide for replication of the procedure. Because of this lack of replication, the teacher cannot be sure if any observed changes in the behavior are reliable. It is possible that any behavior changes were due to any number of external factors (Byiers et al., 2012), such as interaction with peers, the student’s relationship with the teacher, conditions at the student’s home, and other environmental factors. For example, if the AB design had indicated an improvement in Jane’s behavior under the intervention condition, the teacher could not be sure if the change of behavior was due to “writing lines” or because Jane’s peers were encouraging her to raise her hand before talking. Figure 11.3 AB Design: Jane Replication is the repeating of the intervention strategy, or independent variable, to determine the likelihood that the change in the behavior was not due to external variables. Additionally, if the replication of the intervention strategy produces results similar to the first implementation of the strategy, it may be reasonably assumed that the data are reliable. One method of replication is to repeat the baseline and intervention conditions. A simple singlesubject design that replicates the conditions is the withdrawal design. Case Study Kale Kale is a fifth grader at Franklin Pierce Middle School. She and her family are Kanaka Maoli (Native Hawaiians) who moved to Kentucky a year ago. Kale has been a quiet and respectful student, but weeks after the fall semester began, her teacher, Mrs. Daily, began noticing that Kale’s grades were not reflecting her ability. Kale’s records from her previous school showed that Kale made above-average to excellent grades in all classes there. However, now, instead of earning above-average grades, Kale was earning average to belowaverage grades, and sometimes failing grades. Mrs. Daily began monitoring Kale’s behavior in class. She noted that when Kale was given a seat assignment in class, she did not remain on task. Mrs. Daily had her classroom assistant conduct an anecdotal observation and used a duration recording method to measure the duration of Kale’s off-task behavior. The results of the behavioral observation were as follows: The classroom assistant also noted that when Kale worked in a cooperative group she was an active participant and seemed knowledgeable about the group’s assignment. Since Mrs. Daily understood that Hawaiian culture emphasizes the cooperation of individuals and the needs of the whole, she wondered if Kale’s behavior was influenced by her culture. As an intervention strategy, Mrs. Daily assigned a peer buddy to work on seat assignments with Kale. She evaluated the effect of the intervention on Kale’s behavior by using an AB singlesubject design. Based on the results, Mrs. Daily concluded that the intervention strategy was effective in modifying Kale’s behavior. Do you agree with Mrs. Daily’s conclusion? The Withdrawal Design The withdrawal design (or ABAB design) is simply an extension of the AB design. The withdrawal design adds a second baseline after the intervention strategy, and then reintroduces the intervention strategy after the second baseline. The teacher first measures and records the baseline data (Condition A1). Once a stable baseline has been established, the teacher implements the intervention strategy (Condition B1). After an equal number of sessions, the teacher withdraws the intervention strategy. The target behavior without intervention is measured and recorded for a second time (Condition A2). Finally, after a set number of observation sessions, the intervention strategy is reintroduced (Condition B2). This provides the teacher with an additional opportunity to evaluate whether the behavior is actually affected by the intervention. For example, the teacher implements the withdrawal design, or ABAB design, for Jane’s target behavior, as shown in Figure 11.4. Visual inspection of the graph once again indicates that the intervention strategy (writing five sentences) did not affect the target behavior. There was no change in level, trend, or variability. There was no immediate change of behavior under the condition, data points overlapped between baseline and intervention, and there was no degree of change in behaviors. Since the data points were consistent across multiple conditions, the data obtained are considered to be more reliable than data in an AB design. However, Jane’s behaviors across the conditions were basically at the same level. As a result, a functional relationship between the target behavior and the intervention strategy cannot be demonstrated. Figure 11.4 Withdrawal Design (ABAB): Jane The withdrawal design is fairly simple to implement, and it provides replication of the intervention strategy. However, the teacher should not assume that after the first intervention phase the behavior would return to the same level as that prior to the first intervention. Some residual effects may remain from the first AB experience that could affect the second baseline condition. Additionally, the teacher needs to consider the ethical issue of withdrawing an effective intervention to return to a baseline condition. For example, LeVar has been hitting other students. The first intervention that was implemented was effective in reducing LeVar’s behavior. The teacher may not want to withdraw this intervention in order to conduct a second baseline condition and a second intervention condition. The Alternating Treatment Design The alternating treatment design (ABAC) is similar to the withdrawal design, but instead of reintroducing the same intervention, the teacher adds a second, different intervention (Condition C). For example, in Jane’s case, the teacher first measures and records the baseline data (Condition A1) on Jane’s target behavior (talking without permission). The teacher then implements and records the data from the first intervention (writing sentences), which is Condition B. The teacher withdraws the intervention strategy and measures and records the target behavior without intervention for a second time (Condition A2). Then, instead of reintroducing the same intervention strategy (Condition B), as in a withdrawal design, the teacher implements a different intervention. In this case, each time Jane raises her hand before speaking, the teacher gives her a token worth 2 minutes of computer time at the end of day. This second intervention is known as Condition C. The resulting graph (Figure 11.5) seems to indicate that the first intervention (Condition B) did not affect Jane’s target behavior, but the second intervention (Condition C) had a significant effect on the behavior. The graph shows an obvious descending trend in Condition C, and the data points for Condition C do not overlap with any of the previous conditions, which would seem to indicate that Condition C affected the target behavior. However, it is not known if Condition C would be consistent across multiple conditions, which would increase the reliability of the data. Baselines and interventions can be repeated often in alternating treatment designs across multiple conditions, but each intervention should be implemented an equal number of times. For example, the teacher could implement an alternative design for Jane that uses the following sequence: ABACABAC. In this instance, both the first intervention (Condition B) and the second intervention (Condition C) would be repeated twice. Another variation of the alternating treatment design is a rotating design involving the following sequence: ABCBCBC. In this design, both Condition B and Condition C are repeated three times. Both variations of the alternating treatment design provide replication of the intervention strategies and increase reliability. Figure 11.5 Alternating Treatment Design: Jane The alternating treatment design allows the teacher to compare the results of two or more intervention strategies and determine which intervention has been most effective in modifying the student’s target behavior. However, the teacher needs to remember that the alternating treatment design does not establish the cause of the behavior, and it does not determine whether the results are due to the cumulative effects of both interventions. The Changing Criterion Design When using the changing criterion design, the teacher evaluates the effectiveness of an intervention strategy by progressively increasing or decreasing the behavior in stepwise changes by manipulating the conditions of the intervention. The changing criterion design starts with an initial baseline condition, which is followed by a series of intervention conditions based on distinctive, or stepwise, levels of the criterion for the behavior. This series of intervention conditions serves as a baseline for subsequent intervention conditions (McDougall, Hawkins, Brady, & Jenkins, 2006). For example, Jane’s teacher wants to decrease the frequency of Jane’s target behavior (talking without permission) while also decreasing Jane’s reliance on the intervention strategy (token for computer time). Using the changing criterion design, the teacher increases the criterion for receiving a token. In the initial intervention strategy, Jane receives a token every time she raises her hand to ask for permission to talk (alternative behavior). In the second, subsequent intervention strategy, the criterion is increased to two occurrences of raising her hand before she receives a token. The criterion is increased by one occurrence at a time until the frequency is four occurrences of the alternative behavior per token. From the data in the resulting graph (Figure 11.6), it appears that the teacher was successful in reducing Jane’s target behavior while simultaneously increasing the criterion across the intervention strategies. There are few overlapping data points between the different criterion conditions, and, generally, the criterion conditions resulted in decreases in Jane’s behavior. Figure 11.6 Changing Criterion Design: Jane The teacher should consider three factors when using the changing criterion design. The first is the length of the intervention stages. Each subsequent intervention stage should be long enough to establish stable intervention data so that the effectiveness of the intervention strategy can be determined. Usually, a minimum of five baseline data points are needed to establish stability of the behavior. The second factor is the size of the criterion change. The change should be reasonable in size, because a large increase in the criterion may negate the effectiveness of the intervention strategy. For example, if Jane’s teacher were to increase the criterion dramatically all at once, from one token for every incident of the alternative behavior to one token per four incidents of the alternative behavior, Jane may not respond favorably, but she may respond well to gradual increases in the criterion. Finally, the number of criterion changes can determine the effectiveness of the intervention strategy. The more changes, the more confidence the teacher can have in the effectiveness of the intervention strategy, but the number of criterion changes should be relevant to the length of the intervention stages and the size of the criterion for each intervention stage. The longer the intervention stage, the longer it takes to complete the observation of the target behavior. Shorter intervention stages allow the teacher to implement more criterion changes in a shorter amount of time. Unlike the withdrawal design, the changing criterion design does not require withdrawal of the intervention, and so does not delay the intervention or present any of the ethical issues related to withdrawing an effective intervention (Byiers et al., 2012). Given the time constraints many teachers face in today’s classrooms, the crucial factors they must consider when using the changing criterion design are the length of the intervention stages and the size and number of criterion changes. The Multiple-Baseline Design The multiple-baseline design is an extension of the AB design that allows teachers to examine intervention strategies across students, behaviors, and settings (dependent variables). The three different types of multiple-baseline design utilize multiple baselines across behaviors, across individuals, and across settings. Using the multiple-baseline acrossbehaviors design, a teacher can analyze the effectiveness of an intervention strategy on two or more behaviors of one student in a single observation period. For example, Jane’s teacher could analyze the effectiveness of an intervention strategy for Jane’s talking-withoutpermission and out-of-seat behaviors. Using the multiple-baseline across-individuals design, a teacher could analyze the effectiveness of an intervention strategy for two or more students with the same target behavior. For example, the teacher could analyze the effectiveness of an intervention strategy for both Jane’s and Timothy’s talking-without-permission behaviors (see Figure 11.7). Finally, using the multiple-baseline across-settings design allows the teacher to analyze the effectiveness of the intervention strategy for one student in two or more settings. The teacher could analyze the effectiveness of the intervention strategy for Jane’s target behavior in both her English class and her math class. Figure 11.7 Multiple-Baseline Design: Jane and Timothy The multiple-baseline design provides replication of the intervention strategy, and the data obtained are considered more reliable. Additionally, such a design may provide information on causality between the behavior and the intervention when there is a change in the target behavior. The multiple-baseline design may not be practical for some teachers, as it can be challenging for teachers to find the time it takes to observe two or more behaviors of a single student or to observe the behaviors of a single student in multiple settings. However, the multiple-baseline design is appropriate for observation of the effectiveness of a single intervention strategy on the same target behavior of two or more students in a single observation period. What Would You Do? Joseph Joseph is a seventh-grade student in your state history class. When he becomes annoyed with other students, he punches them in their arms. The perceived offenses committed by other students include being in Joseph’s way, making seemingly negative comments about him, and appearing to stare at him. You have completed a functional behavioral assessment and a functional behavior analysis and have concluded that the function of Joseph’s behavior is peer attention. Based on this information, you develop an intervention strategy in which Joseph has 10 minutes of time-out at the isolation table in the back of the classroom. The following are the results of a single-subject design: Is there a functional relationship between Joseph’s behavior and the intervention? Does the intervention seem to be effective? Based on your analysis of the results of the single-subject design, what would you do about Joseph’s behavior? Summary Single-subject designs are methods of evaluating the effectiveness of intervention strategies. Single-subject designs require repeated measures of the target behavior and repeated measures of the behavior during an intervention strategy that has been implemented to modify the behavior. The first step of a single-subject design is to collect and record baseline data on the student’s target behavior. The next step is to measure the effectiveness of an intervention strategy in modifying the target behavior. The data collected on the observed behavior under the intervention strategy are the intervention data. Single-subject designs determine the functional relationship between the baseline data and the intervention data. Once the baseline and intervention data have been collected and charted on a graph, changes in the target behavior are examined along one or more of three parameters: level, trend, and variability. Level is the average rate of the behavior during a condition. Trend is a consistent one-direction change (increasing or decreasing) in the rate of the behavior during a condition. Variability is fluctuation of the behavior during a condition. Several types of single-subject designs can be used to measure the effectiveness of interventions. The basic single-subject design is the AB design, which uses one baseline condition and one intervention condition. However, the AB design may not accurately evaluate the functional relationship between the behavior and the intervention. The withdrawal design (ABAB) is simply an extension of the AB design that adds a second baseline after the intervention strategy and then reintroduces the intervention strategy after the second baseline. The withdrawal design is fairly simple to implement and provides replication of the intervention strategies. The alternating treatment design (ABAC) is similar to a withdrawal design, but instead of the same intervention being reintroduced, a second, different intervention (Condition C) is added. The alternating treatment design compares the results of two or more intervention strategies and determines which intervention has been most effective in modifying the student’s target behavior. The changing criterion design enables evaluation of the effectiveness of an intervention strategy by progressively increasing or decreasing the behavior in stepwise changes through manipulation of the conditions of the intervention. The changing criterion design starts with an initial baseline condition, which is followed by a series of intervention conditions based on “stepwise” changes in the criterion for the behavior. Finally, the multiple-baseline design examines intervention strategies across students, behaviors, or settings. The multiple-baseline design may provide information on causality between the behavior and the intervention when there is a change in the target behavior. Review Activities 1. For each of the following examples, explain why you would or would not implement an intervention strategy based on the baseline data. 2. Why is a withdrawal design better than an AB design for evaluating the effectiveness of an intervention strategy? 3. Erika and Marty are first-grade students. Both have difficulty remaining in their seats. You have developed an intervention strategy utilizing a token system. Using the data below, create a single-subject design to visually display the functional relationship between the behavior and the intervention. Then use visual analysis to make a statement about the level, trend, and variability of the data. Was the intervention more effective for Erika or for Marty? Justify your answer. 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