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2012 14: 47 originally published online 7 June 2011Journal of Positive Behavior InterventionsAimee Faul, Karoline Stepensky and Brandi Simonsen

The Effects of Prompting Appropriate Behavior on the Off-Task Behavior of Two Middle School Students  

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There are a growing number of students displaying problem behavior in schools (Sugai & Horner, 1999). Many teachers do not have the skill set to manage these problem behaviors (Begeny & Martens, 2006). For example, a recent national teacher survey of 1,001 K-12 teachers revealed that 20% of first-year teachers did not feel adequately prepared to maintain order and discipline in their classroom (Markow, Moessner, & Horowitz, 2006). Similarly, a study of in-service teachers’ perceptions indicated that they received little systematic training in classroom management; instead they learned how to manage their classrooms mostly by “trial and error” (Tillery, Varjas, Meyers, & Collins, 2010, p. 96). Given the increasing number of students displaying prob-lem behavior and teachers’ lack of preparation in classroom management, it is important to identify simple classroom management strategies that teachers can implement with success (i.e., strategies that result in desired student behav-ior change).

One of the simplest, empirically supported classroom management strategies is precorrection. A precorrection is delivered before desired behavior is expected, and it is used to increase appropriate and prevent inappropriate student behavior, especially in settings where problem behaviors are likely to occur (Colvin, Sugai, Good, & Lee, 1997). Pre-corrections can take various forms, including a verbal cue or reminder, modeling, or behavioral practice of appropriate behaviors. All precorrections should be framed positively (e.g., tell students what to do, rather than what not to do).

Perhaps the easiest precorrection to implement is a verbal prompt, or reminder, of appropriate social behavior. Verbal prompts require minimal training and effort to implement, and have the potential to positively affect student behavior.

There is minimal research focusing specifically on ver-bal prompts given to “typical” students in a general educa-tion setting. However, emerging research suggests that various prompts (verbal, visual, gestural, and physical) may be effective with students of various age and ability levels across a variety of settings. Specifically, prompts have been demonstrated to effectively increase appropriate behavior, decrease inappropriate behavior, or both for preschool students without disabilities (Wilder & Atwell, 2006), preschool students with autism (Gena, 2006), elementary school students with Attention-Deficit/Hyperactivity Disorder (Flood, Wilder, Flood, & Masuda, 2002), a middle school student with disabilities (Arceneaux & Murdock, 1997), and an adult with intellectual disabilities (Crockett & Hagopian, 2006). In two cases, prompts were paired with social (Gena, 2006) or peer-mediated (Flood et al., 2002)

410702 PBI14110.1177/1098300711410702Faul et al.Journal of Positive Behavior Interventions© 2012 Hammill Institute on Disabilities

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1University of Connecticut, Storrs, CT, USA

Corresponding Author:Brandi Simonsen, 249 Glenbrook Road, Unit 2064, Storrs, CT 06269-2064, USA Email: brandi.simonsen@uconn.edu

Action Editor: Richard Albin

The Effects of Prompting Appropriate Behavior on the Off-Task Behavior of Two Middle School Students

Aimee Faul1, Karoline Stepensky1, and Brandi Simonsen1

Abstract

Prompting is a simple strategy that has been demonstrated to increase appropriate (and decrease inappropriate) behavior when used (a) as a stand-alone strategy with preschool students and individuals with disabilities and (b) in combination with other strategies (e.g., active supervision) with K-12 students in general education settings. Until now, no studies have specifically investigated the effectiveness of prompting as a stand-alone strategy in a general education setting. This study used a single-subject alternating treatment design, with a baseline phase, to explore the relationship between the presence (or absence) of prompting and off-task behavior of two male middle school students in general education. Study results document a decrease in off-task behavior with prompting. Results and implications are discussed in light of limitations.

Keywords

prompting, precorrection, classroom strategies, off-task behavior, middle school

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48 Journal of Positive Behavior Interventions 14(1)

reinforcement. Across studies, prompts were delivered in classroom (Arceneaux & Murdock, 1997; Gena, 2006; Wilder & Atwell, 2006), simulated classroom (Flood et al.), or sim-ilar structured settings (Crockett & Hagopian, 2006) by instructors (Crockett & Hagopian, 2006; Gena, 2006; Wilder & Atwell, 2006) or peers (Arceneaux & Murdock, 1997; Flood et al., 2002).

Researchers have manipulated dimensions of prompting (i.e., specificity, frequency) to determine the most effective way to prompt. Hunsaker (1983) demonstrated that specific prompts were more effective than general prompts. That is, face-to-face conversations (specific) were more effective than a written flyer (general), when paired with reinforcement, at increasing pages written (i.e., work completion) by Hispanic youth with a history of juvenile delinquency. Lancioni and colleagues (2001) demonstrated that more frequent prompts (delivered every 30 s) resulted in greater increases in appro-priate behavior than less frequent prompts (delivered every 1.5–2 min) for individuals with intellectual disabilities. Therefore, prompts should be specific and frequent.

Research in community settings has lead to further clarifi-cation about the dimensions of effective prompts. Specifically, prompts delivered by employees of a restaurant (Austin, Alvero, & Olson, 1998) and grocery store (Engerman, Austin, & Bailey, 1997) resulted in increased seat-belt use by patrons. In addition, prompts delivered over the phone to encourage people to exercise were effective at increasing exercise behav-ior, and frequent prompts (once a week) were more effective than less frequent (once every 3 weeks) prompts (Lombard, Lombard, & Winett, 1995). Although these studies did not take place in a school setting, the findings illustrate that prompts may still be effective when delivered in a different setting, minutes (or more) before the expected behavior. Furthermore, they provide support for increasing the fre-quency with which prompts are delivered but demonstrate that the frequency of the prompt may be matched to the learner and behavior (i.e., average learners may not need prompts every 30 s).

Although the majority of the prompting literature focuses on students with disabilities, several studies have explored the use of prompts in elementary school settings. Specifically, researchers demonstrated that pairing prompting with active supervision is an effective intervention in general education settings with elementary school students (Colvin et al., 1997; De Pry & Sugai, 2002; Lewis, Colvin, & Sugai, 2000). In each study, the staff at an elementary school was trained to (a) give verbal prompts, or precor-rections, to students and (b) actively supervise (move around, visually scan, and interact with students in the envi-ronment) during transitions (Colvin et al., 1997), within the classroom (De Pry & Sugai, 2002), and at recess (Lewis et al., 2000). Across the three studies, results demonstrated a clear decrease in the level of off-task behavior after prompts and active supervision were implemented.

However, because prompting was paired with active supervision, the effects of prompting in isolation cannot be inferred for these settings.

In sum, researchers have demonstrated that prompting is an effective strategy for increasing appropriate, and decreas-ing inappropriate, behavior across a range of individuals (preschool students, individuals with disabilities, and adults) and settings (school and community). The most effective prompts are specific (Hunsaker, 1983) and frequent (Lancioni et al., 2001; Lombard et al., 1995), with the actual frequency determined by characteristics of the learner and desired behavior(s). Although prompts are typically delivered in the setting where behavior is expected, prompts may still be effective when delivered in a different setting and minutes (or more) before the behavior (Austin et al., 1998; Lombard et al., 1995). In addition, prompting is effective when paired with other strategies, including reinforcement (Flood et al., 2002; Gena, 2006) and active supervision (Colvin et al., 1997; De Pry & Sugai, 2002; Lewis et al., 2000). Although research on the effects of prompts is emerging, no studies have directly examined the effects of prompting as a stand-alone strategy with general education students in a K-12 setting.

We conducted the present study to address this gap in the literature. The purpose of this study was to investigate the effectiveness of prompting with middle school students in a general education setting. Specifically, this study addressed the following research question: Was there a functional rela-tionship between teacher-delivered verbal prompts (indepen-dent variable) and off-task behavior (dependent variable) for two middle school students in a general education setting?

MethodSetting

The study took place in an urban middle school that served approximately 1,000 students (ages of 10–14) across Grades 5 through 8. The middle school adopted School-wide Positive Behavior Support (SWPBS; Horner & Sugai, 2005; Safran & Oswald, 2003; Sugai et al., 2000; Sugai & Horner, 2002) as its approach to improve school climate and discipline. SWPBS is a positive and preventive approach composed of three tiers of prevention and inter-vention: Tier 1 (universal or primary) to support all stu-dents, Tier 2 (targeted-group or secondary) to support students with at-risk behavior, and Tier 3 (intensive, individualized, or tertiary) to support students with chronic high-risk behavior (Sugai et al., 2000; Sugai & Horner, 2002; Walker et al., 1996).

At the time of the study, the school was in the third year implementing Tier 1, the second year of implementing Tier 2, and was piloting Tier 3. As part of Tier 1, school staff established three positively stated expectations (i.e.,

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Faul et al. 49

respect, responsibility, and pride), which they called “keys” to success; posted the keys throughout the school; taught students how to follow the keys across all school routines; and reinforced students for following the keys (using a schoolwide token economy and other reinforcers). At Tier 2, the school implemented the Behavior Education Program (BEP; Crone, Horner, & Hawken, 2004). Toward the end of the year, the school also piloted small-group social skills instruction as an additional Tier 2 intervention. At Tier 3, the school was piloting brief and full functional behavioral assessments, which led to the development of brief and full, respectively, function-based individualized behavior sup-port plans.

ParticipantsTwo middle school students participated in this study. “Owen” (pseudonym chosen for the study), an 11-year-old male in fifth grade, had a 504 plan but was not receiving services. Owen engaged in high levels of off-task behavior across classes, especially reading and math. “Tom,” a 12-year-old male in sixth grade, engaged in high levels of off-task behavior in science and math classes. Both students were in general education classrooms all day, and teachers reported that both students were academically able to complete the work assigned correctly and accurately when not engaging in off-task behaviors.

Owen and Tom were identified to participate in this study on the basis of not responding to the school’s Tier 2 intervention (i.e., the BEP). Prior to the study, both students were identified as demonstrating at-risk behavior by the school’s BEP team, based on teacher nominations and office discipline referral (ODR) data. Teachers nominated students by completing a request for assistance form, which described (a) the antecedents, consequences, and nature of each student’s problem behavior and (b) the previous strate-gies the teacher tried to change the behavior. In addition to teacher nominations, the BEP team examined the number and nature of ODRs received by each student. Owen had one and Tom had five ODRs, which all resulted in obtaining attention from either peers or teachers. Based on these data and recommendations from other members of the BEP team, both students were enrolled in the BEP (Tier 2 inter-vention). However, the students did not participate consis-tently in the BEP (i.e., they did not pick up and return their point sheets on a daily basis), and on the few occasions they fully participated, they did not meet their goal for points earned.

As a result, Owen and Tom were identified as potential participants for this study. After obtaining informed con-sent, the researchers conducted informal direct observations to confirm the presence of off-task behavior. The observa-tions revealed the following specific off-task behaviors (defined in the dependent measures section) for the

students: getting out of seat, talking out, making disruptive noises, and talking to peers. Data collection took place across the two classroom settings where problem behaviors were most likely to occur for each student (i.e., math and science for Tom, reading and math for Owen). The classes had a range of 14 to 17 students per class and the same classroom layout (e.g., desk facing forward) throughout the observation days. The duration of each class period was 49 min. Owen had the same teacher for both classes (i.e., math and reading). Tom had a different teacher for each class (i.e., math and science).

MeasuresIn this study, two measures were used: systematic direct observation to document students’ on- and off-task behav-ior (the dependent variable for the study) and anecdotal recording to document the fidelity with which each teacher provided (or did not provide) a verbal prompt to each stu-dent (the independent variable for the study).

Systematic direct observation of student behavior. Data were collected every day over a 13-day period (5 days of baseline and 8 days of alternating treatments). During base-line phase, data were collected in one class period per day, alternating between the two classes (for 5 days). During the alternating treatments phase, data were collected in both class periods (for 8 days).

Trained behavioral observers collected data during the first 15 min of each targeted class period (i.e., math and reading for Owen, math and science for Tom) using a 10-s partial interval recording measurement system. That is, dur-ing each observation, the observer coded whether the stu-dent was engaging in on- or off-task behavior (i.e., getting out of seat, talking out, disruptive noises, and talking to peer). On-task behavior included any behavior related to the task at hand (e.g., looking at the teacher during teacher-directed instruction, interacting with materials appropri-ately for the task). The following definitions were used for each discrete off-task behavior.

1. Getting out of seat was defined as the student standing up. This included the student staying at his desk but not sitting in the chair and the stu-dent walking away from his desk without teacher direction or permission.

2. Talking out included any point where the student talked without being called on during whole group instruction. This included moments where he made comments about material being presented or answering a question without raising his hand. In small group instruction, talking out was recorded when the student spoke out loud when another student was speaking or when the student spoke and it was not his turn.

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3. Disruptive noises were defined as the student pop-ping his mouth with his hand, clicking his tongue, and whistling. This also included any noises that the student made with his hands, which included tapping his pencil on his desk and hitting the bottom of his desk with his hand.

4. Talking to peers during whole group discussion and independent seat work was defined as any-time the student talked with someone sitting next to him or yelled across the room to a peer when he was supposed to be listening or doing independent seat work. Talking to peers during group work or partner work was defined as any time the student went off topic (e.g., talking about video games when he should have been discussing the peri-odic elements). Talking to peers during group and partner work was also recorded when the student talked to peers outside of his group when he was instructed not to.

During each 10-s interval, observers recorded a minus (–) sign if the student was off-task during any part of each 10-s interval and plus (+) sign if the student was on-task during the entire 10-s interval. Thus, on- and off-task behaviors were reciprocals of each other, as students were marked either on- or off-task for each interval.

Establishing and calculating inter-observer agreement (IOA). The observers, who were also the primary researchers (first two authors), completed coursework related to their School-wide Positive Behavior Support specialization. Across mul-tiple courses, they were trained to collect systematic direct observation data and given opportunities to practice. For this study, the observers developed specific operational definitions of behaviors considered on- and off-task (pre-sented previously). Then, observers practiced using the observation tool in the same classroom by observing a stu-dent selected for convenience. They established IOA on the tool, reaching 98% agreement, before taking data on the study participants.

IOA was checked throughout the baseline and alternat-ing treatments phases. The observers used the same clock to ensure that they tracked time similarly and sat separately so that neither observer could see the other’s data collection sheet. IOA was calculated by summing the number of inter-vals that the observers agreed (i.e., when both recorded either on-task or off-task), dividing by the total number of intervals observed (i.e., 90 intervals), and multiplying by 100% (Cooper, Heron, & Heward, 2007). IOA was estab-lished for 40% of the observations (4 of 10 observations) with 99% agreement for the baseline phase. During the alternating treatments phase, reliability was checked for 31% (10 of 32) of the observations, and the observers had 98% agreement.

Documenting the fidelity of teacher prompting. During the alternating treatments phase, a teacher gave a prompt at the beginning of one class (of two classes observed) per day. To ensure fidelity of implementation, teachers were given a script to read, and observers recorded (wrote down) the exact wording of the prompt delivered by the teacher at the beginning of each observation session throughout the study (i.e., 21 sessions for each participant). They also listened to make sure that no other prompts were used.

Experimental Design and ProcedureTo examine the effectiveness of teacher-delivered prompts at reducing students’ off-task behavior in the classroom, researchers used an alternating treatments design. An alter-nating treatments design allows the comparison of (a) two (or more) treatment conditions or (b) treatment and no treat-ment conditions. This design allows researchers to deter-mine which treatment condition is associated with desired behavior change, and it controls for many threats to internal validity (e.g., Barlow & Hayes, 1979; Gast, 2010). In this study, researchers employed two phases: baseline and alter-nating treatments (prompt vs. no prompt).

Baseline. During baseline, no changes were made to the students’ or teachers’ usual routines. Each student’s behav-ior was observed and recorded for 15 min at the beginning of one class period per day. Because two classes were tar-geted for each student, a coin was flipped to determine in which class observations would take place each day. Each student had 5 data points for baseline phase across both tar-geted classes.

After baseline data were collected, researchers trained each student’s teacher(s) to prompt using a script, thereby increasing the likelihood that prompts would remain stan-dardized. The script was specific to each student’s behavior in class. For Owen, the teacher read, “Owen, remember the three keys today, Be Respectful, Be Responsible, and Have Pride. Do your best!” For Tom, the teacher stated, “Are you ready for class today? Remember the three keys, Be Respectful, Be Responsible, and Have Pride. Do your best!” Researchers instructed the teacher to read the script during the prompting condition, and researchers told the teacher before class started which condition (prompt or no prompt) was happening during that class period. Researchers also asked the teacher not to comment on the student’s behavior during or at the end of the class to minimize the likelihood that other potential antecedent or consequence variables would influence student behavior.

Alternating treatment. During the alternating treatment phase, observers watched and recorded student behavior dur-ing both targeted classes. The two treatments (i.e., prompt or no prompt) were randomly assigned each day by flipping a coin, such that each condition was assigned to one of the

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two class period each day. In other words, each student received a prompt at the beginning of one class and did not receive a prompt in the other class each day. Random assignment of conditions (i.e., the coin flip) was used to randomize variables that may affect the student’s behavior (e.g., condition order, time of day, class subject, other stu-dents in class).

In each period, the teacher implemented the randomly assigned condition (prompt or no prompt). The observer sat within hearing range of the prompt, in order to ensure that each condition was implemented correctly and the teachers did not deliver any extra prompts or cues. In the no-prompt condition, the teachers did not prompt or say anything to the student other than a greeting of “hi” at the door. This greeting was part of the teachers’ normal routine of active supervision; school administration required teach-ers to be at their door to monitor the hall during passing periods. In the prompt condition, the teachers stood by the door at the front of the classroom, greeted the student, and used the script to prompt him. Across both treatments, teachers were instructed not to give additional or unplanned prompts, and they were asked to ignore any behaviors that may have resulted in prompting the student on how to behave.

ResultsFor systematic direct observation data, visual analysis was used to examine changes in stability, level, and trend within and across phases. Specifically, we followed the guidelines set forth by Horner and colleagues (i.e., Horner et al., 2005; Horner & Spaulding, 2010). Accordingly, a functional relationship was inferred if three demonstra-tions of change were observed at three or more points in time (Horner et al., 2005), and three demonstrations were established by collecting three or more data points in each

alternating treatment condition (Horner & Spaulding, 2010). For fidelity of prompting, narrative data were recorded and reported.

Systematic Direct Observation of Student Behavior

Baseline. During baseline, Owen engaged in off-task behavior during an average of 16% of intervals (range = 13%–19%) during the first 15 min of class (see Figure 1). Throughout the phase, Owen’s data were fairly stable, with no clear trend. Tom engaged in off-task behavior for an average of 57.4% of intervals (range = 41%–69%) during the first 15 min of class (see Figure 2). Throughout the phase, Tom’s data were somewhat variable, with a slight decreasing trend.

Alternating treatment. During the alternating treatment phase, Owen engaged in less off-task behavior when he was prompted than when he was not. During sessions with-out prompts, Owen engaged in levels of off-task behavior that were comparable to baseline (mean = 17% of intervals off-task, range = 9%–27%); there was minimal variability and no clear trend. During sessions with prompts provided at the beginning of class, Owen’s intervals of off-task behavior decreased to an average of 7% of intervals off-task (range = 0%–23%); there was low variability and a down-ward trend in his data (Figure 1).

During alternating treatment design, Tom’s behavior also changed as a result of prompting. When Tom did not receive a prompt, his off-task behavior occurred during an average of 61% of intervals (range = 50%–87%); data dem-onstrated moderate variability, and a slight increasing trend. During the sessions that began with a prompt, Tom’s inter-vals of off-task behavior decreased to an average of 28% of intervals (range = 19%–51%); data were fairly stable, and demonstrated a slight decreasing trend (Figure 2).

Figure 1. Alternating treatment design evaluating the effects of two different treatments (i.e., prompting at beginning of class vs. no prompt) on off-task behavior of OwenNote. A 1-week school break occurred between Observations 9 and 10 (indicated by arrow).

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52 Journal of Positive Behavior Interventions 14(1)

For both students, the level of off-task behavior without prompts was comparable to baseline, and the level of off-task behavior with prompts was clearly lower. Of particu-lar note, there was no overlap in data paths across the two conditions (prompt or no prompt) throughout the alternat-ing treatments phase for either student. The eight data points in each condition represent eight demonstrations of effect (e.g., Horner & Spaulding, 2010). Thus, even though the effect was smaller for Owen than for Tom, a functional rela-tionship may be inferred for both students.

Fidelity of Teacher PromptingTeachers delivered prompts with a high degree of fidelity. The same teacher taught Owen’s two target classes. During the prompting treatment for Owen, the teacher consistently used the same prompt with no variability of wording: she accurately implemented the scripted prompt across 21 of 21 (100%) opportunities. The teacher introduced no other social prompts (i.e., no comments were made on how the student should be behaving) and no reinforcement was given for on-task or off-task behavior during the 15-min observation session at the beginning of class. Although two teachers prompted Tom (he had different teachers for his two target classes), the prompt delivered to Tom during the observation period was the same. Both of the teachers used the same verbal instructions when delivering the prompt; that is, both teachers delivered the prompt with fidelity across 21 of 21 (100%) opportunities. Neither teacher intro-duced any social prompts or reinforcement during the 15-min observation session.

DiscussionThe purpose of this study was to assess whether a teacher-delivered verbal prompt affected students’ off-task behavior.

Because this study used an alternating treatments design, it was possible to directly compare students’ behaviors with and without a prompt. For both Owen and Tom, a teacher-delivered verbal prompt at the beginning of class was associated with a clear decrease in off-task behavior and an increase in on-task behavior in class. The levels of off-task behavior exhibited by both students during ses-sions without a prompt were comparable to the levels dis-played during baseline. In contrast, the levels of off-task behavior exhibited by both students during sessions with a prompt were lower than levels exhibited during baseline or the no prompt condition. In fact, the data paths associated with each condition (prompt and no prompt) showed clear separation (no overlap) throughout the alternating treat-ments phase; thus, a functional relationship between prompt-ing and student behavior was demonstrated. However, the effects appeared stronger (i.e., there was greater separation) for Tom than for Owen. Throughout the study, Owen demonstrated lower levels of off-task behaviors, making decreases in off-task behavior appear less dramatic. The effects of prompting did not generalize to other class peri-ods during the same day. To be clear, these results suggest that providing one prompt at the beginning of class may result in a decrease in off-task behavior immediately fol-lowing the prompt.

During the study, teachers informally commented that they saw an improvement in academic performance during classes when the student was prompted, and they were eager for the study to end so that they could consistently use prompting with these students. Thus, teacher comments provide further support that prompting was a simple and effective strategy that positively affected the behavior of both students in this study. However, we did not collect fur-ther social validity data.

The results of this study begin to fill the gap in previous research. Specifically, previous research demonstrated that

Figure 2. Alternating treatment design evaluating the effects of two different treatments (i.e., prompting at beginning of class vs. no prompt) on off-task behavior of TomNote. A 1-week school break occurred between Observations 9 and 10 (indicated by arrow).

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prompts were effective (a) with preschool students and indi-viduals with disabilities (e.g., Crockett & Hagopian, 2006; Flood et al., 2002; Gena, 2006) and (b) in combination with active supervision with elementary school students in gen-eral education (Colvin et al., 1997; De Pry & Sugai, 2002; Lewis et al., 2000). This is the first study to examine prompt-ing as a stand-alone strategy with middle school students in a general education setting, and the results provide further support for this simple and effective strategy.

Discussion of Study LimitationsAlthough the results are promising, it is important to remain aware of the limitations of this study. First, attempts were made to randomize extraneous classroom variables (class subject, time of day, etc.) across conditions through random assignment (coin flip). However, schedule changes, which are typical in a middle school setting, occurred during the study. For three days of data collection, the students were on a modified testing schedule; the start time and duration of class periods were adjusted to accommodate statewide testing. Because an alternating treatments design was used, these changes would have affected both class periods in the same day and should not have interfered with a comparison between conditions.

Second, two male middle school students participated in this study. Although both students were identified through the school’s typical nomination process for Tier 2 inter-ventions, additional data on students’ specific academic and behavioral histories were not collected. Future researchers should examine the potential impact of different academic abilities and behavioral histories. For example, descriptive data (i.e., teacher nominations, ODRs, and direct observa-tions) indicated that both students may have had a history of positive reinforcement (i.e., obtained peer and teacher attention) for off-task behavior. Because prompts are a form of teacher attention, these students may have responded more favorably to prompting than students with a different learning history (e.g., students whose behaviors are main-tained by escaping attention or work). Given the small and restricted sample, generalization of study results to other populations or groups of students (e.g., students with differ-ent ages, sex, academic abilities, or learning histories) is not appropriate.

Third, there were limitations with respect to data col-lection. Data were only collected during the first 15 min of class, and the remaining 34 min were not observed. Therefore, the duration of behavior change as a result of prompting is unknown and merits exploration in future research. In addition, two of the researchers (first two authors) collected all study data. In other words, observers were aware of study conditions and monitored fidelity of implementation. Although procedures were put in place to ensure objective and reliable data collection (i.e., observer training, collection of IOA data throughout both phases of the

study), it is possible that observer bias affected systematic direct observation data. When possible, researchers should ensure that observers are blind to study conditions to elimi-nate the potential for observer bias.

Fourth, as the purpose of this study was to explore the effects of prompting, we did not implement more compre-hensive behavior support strategies. It is possible that greater behavior change would have resulted from implementation of additional strategies, including those used in combina-tion with prompting in previous research (i.e., active super-vision and reinforcement).

Finally, we did not collect social validity data. Future researchers should collect data on the feasibility, accept-ability, and perceived effectiveness of interventions from the perspective of the participants (in this case, students and teachers).

Discussion of Study ImplicationsDespite these limitations, this study provides further evi-dence that prompting is a simple and effective strategy that may be implemented successfully with students who engage in off-task behavior in a general education class-room setting. Given the increased numbers of students displaying off-task behaviors in general education settings and given that teachers are often not well prepared to address these behaviors, it is important to identify simple classroom management strategies. Prompting requires min-imal training and effort to implement, making it an ideal strategy for managing student behavior in a general educa-tion classroom.

In this study, the prompt was specific and linked directly to the positively stated schoolwide expectations, and prompt-ing resulted in decreased off-task behavior for study par-ticipants. Given these results, teachers should consider providing a brief prompt to remind students how to behave appropriately before class starts. Teachers may also con-sider pairing prompts with other effective classroom man-agement strategies (e.g., reinforcement, active supervision), as previous research supports use of these combined strate-gies. Whether used in isolation or in conjunction with other strategies, prompts are a quick and positive way to prevent students’ off-task behaviors in the classroom.

This study also highlighted areas for future research. First, this study demonstrated the effectiveness of prompt-ing with two male middle school students. Researchers should seek to systematically replicate these results with general education students with various demographic char-acteristics (i.e., sex, age), academic abilities, and learning histories (i.e., history of negative reinforcement for off-task behaviors). Second, because prompting appears to be effec-tive with individual learners, researchers should investigate the effectiveness of prompting as a stand-alone classroom or group management strategy. Specifically, researchers should explore the effectiveness of a prompt for social

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54 Journal of Positive Behavior Interventions 14(1)

behavior delivered to a group of learners in a general edu-cation setting. Third, researchers should continue to explore the conditions (e.g., group size, setting, learner characteris-tics) and dimensions (e.g., frequency, specificity) under which prompting is most effective for individuals and groups of learners.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, author-ship, and/or publication of this article.

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About the Authors

Aimee Faul, MA, was a graduate student at the University of Connecticut’s Neag School of Education at the time of the study.

Currently, she is a special education teacher at Bethel Public Schools. Working with students with autism and challenging behaviors are among her interests within education.

Karoline Stepensky, MA, was a graduate student at the University of Connecticut Neag School of Education at the time of the study. She is now a special education teacher and an active member of the Positive Behavior Interventions and Supports team at a Capitol Region Education Council magnet school in Enfield, Connecticut.

Brandi Simonsen, PhD, is an associate professor of special education at the Neag School of Education at the University of Connecticut. Her current interests include schoolwide positive behavior support in alternative settings, classwide positive behav-ior support, and secondary and tertiary supports for students with more intensive needs.

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