Effects of Coaching on Teachers’ Use of Function-Based Interventions for Students With Severe Disabilities

Abstract

This study used a delayed multiple-baseline across-participants design to analyze the effects of coaching on special education teachers’ implementation of function-based interventions with students with severe disabilities. This study also examined the extent to which teachers could generalize function-based interventions to different situations. In addition, this study examined the effects of function-based interventions on students’ problem and replacement behaviors. After an initial training on functional behavior assessment and implementation of function-based interventions, the experimenter coached each teacher. Results indicated a functional relationship between coaching and an increase in teacher fidelity scores. Teachers generalized the strategies to other situations with the target students. Although some improvement in student behavior was noted upon teachers’ use of function-based interventions without coaching, this improvement was not consistent for all students and across the replacement behaviors. A functional relationship was found between accurate implementation of the function-based interventions and an increase in the students’ primary replacement behaviors.

Keywords

coaching functional behavior assessment function-based interventions

Research has shown that the prevalence of challenging behaviors is higher among individuals with disabilities compared with challenging behaviors of their typically developing peers (Sigafoos, Arthur, & O’Reilly, 2003). Emerson et al. (2001) determined that as many as 10% to 15% of the total population of individuals diagnosed with intellectual disability (ID) display challenging behaviors. In addition, individuals who have a dual diagnosis of autism spectrum disorder (ASD) and ID are at even higher risk for exhibiting challenging behavior (Blacher & McIntyre, 2006; Rojahn, Wilkins, Matson, & Boisjoli, 2010). More specifically, individuals with ASD and ID are more likely to exhibit self-injurious behavior and stereotypic behaviors than individuals with ID alone (Rojahn et al., 2010).

Not only are students with disabilities more likely to exhibit challenging behaviors, but they are also at higher rates of expulsion and suspension (Evenson, Justinger, Pelischek, & Schulz, 2009). Students with disabilities are the recipients of reactionary consequence strategies, such as suspension and expulsion, at higher rates than typically developing peers (Evenson et al., 2009). Students with disabilities are 11% of the total school population; however, they account for 20% of total school suspensions (Evenson et al., 2009).

Challenging behaviors negatively impact a student’s school progress, progress of other students, educational planning, and the well-being of caregivers (Blacher & McIntyre, 2006; Chandler & Dahlquist, 2006). Some of the negative effects of challenging behavior for students include (a) failure to reach their academic potential, (b) increased school suspensions and increased school absences, (c) higher rates of peer rejection accompanied by a lack of an appropriate social network, (d) disruption of other students’ learning, and (e) an increase in the time required for planning from the entire educational team, which negatively impacts the time teachers can spend on academic planning (Chandler & Dahlquist, 2006).

Functional behavior assessment (FBA) is a process that allows teachers, researchers, psychologists, and other practitioners to create hypotheses regarding the potential relationship between the environment and a student’s challenging behavior (O’Neill et al., 1997). FBA is a broad term that includes a set of processes to identify the relationship between the challenging behavior and the environment. FBA includes interviews, rating scales, direct observations, and functional analysis (FA) where the variables are systematically and experimentally manipulated (O’Neill et al., 1997).

The FBA is then used to create and implement function-based interventions. Function-based interventions are positive interventions used to target challenging behavior and increase a functionally appropriate alternative behavior (Horner, 1994). These plans typically include a range of environmental manipulations (e.g., changes to motivating, antecedent, or consequence variables) that create an intervention package that includes teaching replacement behavior, altering the environment, and adjusting student contingencies and consequences (Umbreit, Ferro, Liaupsin, & Lane, 2007).

The Individuals With Disabilities Education Act of 2004 (IDEA) mandates use of FBA with students who have disabilities and challenging behaviors that interfere with learning and/or participation in school activities. FBAs and resulting function-based interventions have been more successful in reducing challenging behaviors than non-function-based interventions (Filter & Horner, 2009; Mustian, 2010; Umbreit et al., 2007). Many school personnel fail, however, to implement this process with the fidelity needed to achieve successful outcomes (Blood & Neel, 2007; Scott et al., 2005). At this time, there is no sufficient research demonstrating that school personnel can use the outcomes of FBAs to develop function-based interventions (Scott et al., 2005). Nahgahgwon, Umbreit, Liaupsin, and Turton (2010) specifically recommend additional research to examine the type and intensity of training procedures necessary for school personnel to create sustained implementation of FBAs and function-based interventions with fidelity.

Schools frequently use the workshop training method to train school personnel on a range of topics; however, research has suggested that this model alone is insufficient to successfully train school personnel to develop function-based interventions and that school staff continue to rely on punitive and exclusionary strategies that are unrelated to behavioral function (Scott et al., 2005). Scott, McIntyre, Liaupsin, Nelson, and Conroy (2004) found that after a 1-day workshop, school-based teams were unable to correctly identify the function of behavior from their students when compared with expert’s analysis of the function. In addition, Van Acker, Boreson, Gable, and Potterton (2004) examined FBAs and behavior intervention forms from teachers in Wisconsin. They found that even after a state-provided 1-day training, the FBAs and behavior intervention forms contained substantial mistakes, including lack of clear definitions of behaviors, lack of verification of hypothesized functions, and not using the results of the FBA to drive creation of the behavior intervention plans. Due to difficulty in implementing FBAs and function-based interventions, teachers may need additional support through other training and support methods.

Coaching is a model used to increase teachers’ accuracy when implementing evidence-based practices (EBPs) and has been shown to have promising results toward improved student achievement (Kretlow & Bartholomew, 2010). Coaching includes initial training on a procedure or curriculum, individual follow-up observations, and feedback from an expert in the targeted area (see Kretlow & Bartholomew, 2010). Coaching has been effective in increasing teacher accuracy in a range of areas including implementation of classwide positive behavior supports (PBS; Filcheck, McNeil, Greco, & Bernard, 2004), reading interventions (Jager, Reezigt, & Creemers, 2002; Kohler, Ezell, & Paluselli, 1999; Lignugaris-Kraft & Marchand-Martella, 1993; Morgan, Menlove, Salzberg, & Hudson, 1994), explicit math instruction (Kretlow, Cooke, & Wood, 2011; Kretlow, Wood, & Cooke, 2011), and teacher praise in a response-to-intervention (RTI) model (Myers, Simonsen, & Sugai, 2011). In addition, Iovannone et al. (2009) used a randomized controlled trial to measure the effects of the “Prevent–Teach–Reinforce” model, to packaged intervention designed to increase schoolwide PBS that includes a coaching component, in public school Grades K-8. Results indicated significantly higher academic engagement, social skills, and decreased problem behavior. Dunlap, Iovannone, Wilson, Kincaid, and Strain (2010) used the Prevent–Teach–Reinforce model in an elementary school and reported two case studies that utilized a coaching component for two teachers of students with individualized behavior support plans as one component of the overall package intervention.

Coaching may be a successful model to teach teachers how to implement function-based interventions; however, there is no research examining coaching and teachers’ implementation of function-based interventions as the primary dependent variable. Therefore, the purpose of this study was to evaluate the effects of coaching on special education teachers implementation of function-based interventions with students with severe disabilities. This study answered four research questions.

Research Question 1: What are the effects of coaching on special education teachers’ accuracy of implementation of function-based interventions?

Research Question 2: What is the effect of coaching on teachers’ ability to generalize a function-based intervention (developed using the same process) to a second identified challenging behavior and/or setting with their students?

Research Question 3: To what extent do students’ challenging behaviors decrease and replacement behaviors increase as teachers implement function-based interventions with increasing fidelity?

Research Question 4: Do teachers and administrators find the use of coaching appropriate and efficient?

Method

Participants

Participants were certified special education teachers. Participating teachers each referred one student with moderate to severe disabilities and who demonstrated challenging behavior. Mrs. Yacht (pseudonyms used throughout) taught in an exceptional children preschool classroom for students with disabilities and their typically developing peer models. Mrs. Yacht was a master’s level teacher and had 14 years of teaching experience. Mrs. Yacht referred Susan as her target student. Susan was a 4-year-old Caucasian girl. She was diagnosed with trisomy 9 mosaicism, a disorder associated with failure to grow, severe ID, facial abnormalities, and joint abnormalities (Accardo & Whitman, 2011). Susan was nonverbal and communicated through crying, facial expressions, and occasionally pointing to items. Susan also wore a patch on one eye due to esotropia (turning in of one eye) and glasses to correct her vision. She was referred to participate in this study due to the problem behavior of taking off her glasses, which then lead to her attempting to remove her eye patch.

Mrs. Williams taught in one of the school’s resource rooms. She taught small groups of students in math and language arts. Mrs. Williams was a master’s level teacher and had 4 years of teaching experience. Mrs. Williams referred Karla to be involved in this study, an 8-year-old Caucasian girl who attended a typical third-grade class and received resource support with Mrs. Williams in the areas of math and language arts. Karla had a diagnosis of Down’s syndrome. Karla was able to vocally communicate in full sentences and read at approximately a second-grade level. She was referred to participate in this study due to the problem behavior of noncompliance, refusal to complete assigned classroom tasks by saying no, pushing away work, putting her head on the desk, leaving the designated work area, and physically refusing to move.

Mr. Carlisle taught in a separate classroom that was targeted toward the needs of students with moderate to severe autism. Mr. Carlisle had 3 years of teaching experience. Mr. Carlisle referred Michael as his target student to be involved in this study, a 5-year-old boy with a diagnosis of autism. Michael was nonverbal and communicated by grabbing items and displaying challenging behaviors. Michael’s challenging behaviors included screaming, hitting self and others, swiping materials, biting, and dropping to the floor.

Mrs. Green also taught in a classroom for students with autism; however, the students in this classroom had higher academic skills, and most students were included in general education classes for at least some of their school day. Mrs. Green had 15 years of teaching experience. Mrs. Green referred Jack as her target student to be involved in this study, a 10-year-old boy with a diagnosis of autism who attended Mrs. Green’s classroom for the majority of his school day but attended specials (i.e., gym, art, computers, music) and recess with a general education classroom. Jack was vocal and was able to communicate his wants and needs using short sentences, phrases, and one-word requests. Jack was referred by his teacher to participate in this study due to his off-task behavior during work time. These behaviors included noncontextual echolalia, refusal to respond, and screaming.

Setting

The study was conducted at a public elementary school located in the southeastern United States. The school was a semirural elementary school. The study occurred in multiple locations throughout the school including the conference room (for the initial FBA training) and each teacher/student’s classroom for the intervention. The intervention took place during a teacher-identified activity that was part of each student’s day, so no additional classroom modifications were required.

Materials

Materials used in the study were both created and aggregated from a number of published resources. During the in-service, teachers completed the Functional Assessment Interview (FAI) form developed by O’Neill and colleagues (1997). The experimenter (first author) and teachers also completed the function matrix as described by Umbreit and colleagues (2007). Subsequently, the experimenter and teachers used the Building a Support Plan form also developed by O’Neill and colleagues (1997). The in-service included PowerPoint presentations training teachers on the basics of applied behavior analysis (ABA) and development and implementation of FBAs and function-based interventions.

Data Collection

Dependent Variables

The first dependent variable was percentage accuracy of teacher implementation of the function-based intervention during probe sessions as measured by the procedural fidelity checklist. Fidelity checklists were standardized to the use of function-based interventions; however, each checklist was tailored to the individual student’s behavioral function and needs. Each checklist included items such as engaging students in appropriate work task as previously specified, providing appropriate instruction (e.g., least to most prompts) on targeted replacement behavior, reinforcement of correct responses (either appropriate task completion or demonstration of targeted replacement behavior), reacting as specified to targeted challenging behavior, and collecting data accurately on student behavior (see Figure 1). Data were graphed as percentage of steps completed correctly.

Figure 1.

An example of a teacher-specific function-based intervention procedure fidelity checklist.

The second dependent variable was a measure of the students’ problem behavior during probe sessions (as selected and defined by the teacher and researcher during the afternoon portion of the workshop training). Each measurement system was selected to best gain an accurate measure of student behavior based on the topography and definitions. The experimenter calculated the frequency or percentage of intervals of specified challenging behaviors that occurred during the same teacher-selected activity for a 10-minute observation. The frequency or percentage interval of targeted challenging behaviors displayed was graphed on an equal-interval graph. In addition, data were collected on the same behavior in a different setting. This behavior had an FBA-conducted and function-based intervention developed in the same manner as the primary challenging behavior, but was used to measure teacher generalization.

The third dependent variable was a measure of the students’ replacement behavior during probe sessions (as selected and defined by the teacher and researcher during the afternoon portion of the workshop training). Data were measured and collected in the same manner, and at the same time, as the data for the problem behavior.

Susan’s problem behavior was taking her glasses off. Taking glasses off was defined as anytime Susan attempted to or actually removed the glasses from their correct position. This was recorded using a frequency count. Susan’s chosen replacement behavior was appropriate use of materials, which was defined as interacting with adapted circle time materials. This was tracked using momentary time sampling with 1-minute intervals.

Karla’s problem behavior was noncompliance. Noncompliance was defined as anytime Karla left the designated work area without permission, physically pushing away work materials, verbally refusing to complete a teacher-assigned task or request, not starting a task or assignment within 30 seconds of the teacher prompt, or physically refusing to move. This was recorded using partial interval recording with 1-minute intervals. Karla’s first replacement behavior was compliance. This was recorded using whole interval recording with 1-minute intervals. Karla’s second replacement behavior was functional communication (i.e., raising her hand to request a break or help). This was tracked using a frequency count.

Michael’s problem behavior was tantrums. A tantrum was defined as anytime Michael attempted to or actually bit others, hits himself/others/objects, threw or swiped objects, banged his head against objects, or dropped to the floor. This was recorded using partial interval recording with 30-second intervals. His first replacement behavior was on-task behavior. This was recorded using whole interval recording with 30-second intervals. His second replacement behavior was functional communication (i.e., exchanging a photograph of a preferred break item to request a break from the activity). This was recorded using a frequency count.

Jack’s problem behavior was off-task behavior during work tasks. Off-task was defined as anytime Jack pushed away work, repeated works/phrases that were unrelated to the activity, screamed (using volume above conversational level), or did not respond to a teacher directive within 10 seconds. This was recorded using partial interval recording with 1-minute intervals. Jack’s first replacement behavior was on-task behavior. This was recorded using whole interval recording with 1-minute intervals. His second replacement behavior was independently initiated functional communication (i.e., appropriate break requests). This was recorded using a frequency count.

Interobserver Reliability

Interobserver reliability was conducted on 32.2% of teacher sessions distributed evenly across phases (baseline, post-in-service, coaching, generalization, and maintenance) and averaged 100%. Reliability for teacher fidelity was point by point and calculated by dividing the total agreements by the total opportunities and multiplying by 100.

Interobserver reliability was conducted on 31.3% of student behavior sessions distributed evenly across phases (baseline, post-in-service, coaching, generalization, and maintenance) and averaged 99.7% accuracy for problem behavior (range = 90%-100%) and 96.0% for replacement behavior (range = 90%-100%). Reliability for the student behavior was either the gross method for frequency measures or interval-by-interval for interval measures of behavior. Gross method was calculated by dividing the smaller frequency divided by the larger frequency and multiplying by 100. The interval-by-interval method was calculated by dividing the total number of agreements by the total intervals.

Procedural Fidelity

To ensure that coaching sessions were implemented as designed, the second observer collected data on the fidelity of the experimenter’s implementation of the coaching session with the teacher using a coaching fidelity checklist. Fidelity data were collected across 50% of coaching sessions and averaged 100% accuracy.

Social Validity

Social validity was collected by asking the classroom teacher and school psychologist to complete social validity questionnaires. The questionnaire focused on four areas: (a) whether coaching was an effective method to improve teachers’ implementation of function-based intervention, (b) whether coaching was a feasible method to improve teachers’ implementation of function-based intervention, (c) whether coaching was a socially acceptable method for improving teachers’ implementation of function-based intervention, and (d) whether teachers will use function-based interventions with students in the future.

Experimental Design

The study used a delayed multiple-baseline across-participants design for teachers and a multiple-baseline across-participants design for students (Cooper, Heron, & Heward, 2007). The decision to use a delayed multiple rather than a standard multiple baseline was made as a result of practical difficulties encountered after the beginning of student data collection (i.e., a teacher was on family leave and could not begin baseline phase immediately). Phase changes occurred based on teacher behavior—once a minimum of five data points and a stable or decreasing trend was established for the first teacher participant. A second teacher was introduced once a change in level or trend was identified for the initial teacher. Each subsequent teacher was added in the same manner. Teachers moved to the maintenance phase once a minimum of five data points in intervention were collected and each had scored minimally 80% accuracy in the final three consecutive probe sessions. Students’ behavioral data were collected to measure changes. However, phase changes were not dependent on student responding; instead, phase changes occurred based on teachers’ performance (the primary dependent variable).

Procedures

Initial Observation

Prior to beginning formal data collection, the experimenter observed each teacher–student pair to familiarize herself or himself with the students and ensure the behavior met the criteria for this study. During this 1-week period, the experimenter used ABC (Antecedent Behavior Consequence) observation forms to collect direct observation data on the primary challenging behavior. These data were used during the second portion of the teacher in-service training to complete a function matrix and develop a function-based intervention.

In-Service

Participating teachers attended a 1-day 6-hour in-service prior to the baseline phase. The experimenter provided basic training on development and implementation of FBAs. The in-service began in a lecture format via PowerPoint, providing the necessary information on how to conduct FBAs and relevant information on ABA, the process of completing an FBA, and developing/implementing function-based interventions as described by Umbreit et al. (2007).

The second portion of the in-service was conducted in a workshop format. The experimenter worked with the participants to begin completion of an FBA and develop function-based interventions for their paired students. Function-based interventions were developed for the primary challenging behavior. This included finalization of student behavior definitions, completion of an FAI form (O’Neill et al., 1997), function matrix (Umbreit et al., 2007), and Building a Support Plan form, including competing pathways summary (O’Neill et al., 1997). Teachers left the in-service with the technical information needed to implement the function-based interventions with their targeted student.

Student Baseline

Baseline was conducted by observing the teacher work with the identified student during completion of a previously identified task or classroom activity. Duration of these sessions was held constant at 10 minutes for all sessions. This activity was selected by the teacher and researcher, and was held constant throughout the study. The task/activity was one where the student had frequently exhibited the challenging behavior in the past. For Susan, sessions occurred during circle time; for Karla, they occurred during English language arts small group resource room instruction; for Michael, they occurred during one-on-one discrete trial implementation; and for Jack, they occurred during small group English language arts instruction. Data were also taken on the frequency or percentage intervals of the student challenging and replacement behaviors during this session.

During the student baseline, the experimenter did not provide prompting, reinforcement, or corrective feedback for teachers. Teachers did not start implementation of the function-based intervention during this phase; instead, he or she continued instruction as had been previously conducted. Once a minimum of five data points and a stable or decreasing trend was established across all included students, the teachers were brought into the teacher baseline phase.

FA

Prior to conducting the teacher baseline phase, the experimenter tested the effectiveness of the intervention developed by conducting a brief alternating treatments design (Cooper et al., 2007). The researcher used free-play conditions alternating with conditions designed to test the hypothesized function of each students’ problem behavior (i.e., attention for Susan, and escape for all other participants) for brief alternating intervals until a divergent data path emerged. Completion of the alternating treatments design served to confirm that the hypothesized function was accurate and that the designed intervention would be more likely to be effective. Once the function of the problem behavior was confirmed for each student by the researcher, the teacher baseline phase was introduced for all teachers.

Teacher Baseline (Function-Based Intervention)

Data were collected on accuracy of implementation of the function-based intervention by observing the teacher work with the identified student during completion of a previously identified task/activity. The teacher was scored on the accuracy of each step of the fidelity checklist. Data were also taken on the frequency or percentage intervals of the student challenging behavior and replacement behavior during these sessions. The researcher did not provide prompting, reinforcement, or corrective feedback for teachers during the teacher baseline phase. When a minimum of five data points were collected and a stable or decreasing trend was established, each teacher began intervention (coaching) in a staggered fashion.

Coaching

The intervention consisted of the experimenter using side-by-side coaching with the teacher as they worked with the target student during the identified task. The coaching intervention consisted of three main parts: (a) a preobservation meeting, (b) the coaching session, and (c) a postcoaching feedback meeting. During the 5- to 10-minute preobservation meeting, the experimenter provided specific instructions as to how to implement the function-based intervention. During the coaching process, the researcher provided an initial model on how to implement the function-based intervention and then provided immediate feedback on the teacher’s accurate use of the function-based intervention with the student. The coaching process took approximately 10 minutes. No teacher implementation data were collected during the coaching. During the postcoaching feedback meeting, which typically lasted less than 5 minutes, the experimenter reviewed the teacher’s progress, highlighting steps that were correctly implemented and reviewing steps where errors were made.

Once the coaching was provided, the researcher immediately observed the teacher implementing the same task with the student and recorded the percentage of accuracy on the fidelity checklist. The second teacher was introduced once a change in level and/or trend was identified for the initial teacher. The third and fourth teachers were added in the same manner. Data were taken on student performance (frequency or percentage intervals of challenging and replacement behavior) to observe whether a reduction in challenging behavior was noted; however, phase changes were not dependent on student behavior.

Teachers were provided with coaching sessions until they scored minimally 90% accuracy in two consecutive sessions. After teachers scored at this level of accuracy, the coaching session was no longer provided; instead, the researcher simply observed the teacher using the function-based intervention. If a teacher’s accuracy had fallen below 90%, coaching would have been reintroduced (however, this did not occur during this study).

Generalization and Maintenance

Generalization data were taken by observing each teacher work with the same student during a different task where the student was likely to exhibit the same behavior. This behavior went through the FBA process and had a function-based intervention developed along with replacement behavior identified during the in-service. For the students in this study, their problem behaviors demonstrated the same functions across the settings, and replacement behaviors were held constant. Teachers made some changes to the function-based intervention as necessary to accommodate changes in setting and materials. For example, Susan’s teacher’s materials were very different during lunch (generalization setting) verses morning circle time (primary setting). Data were collected on the teachers’ accuracy of implementation of the function-based intervention based on the fidelity checklist. Generalization data were collected once during baseline and once during maintenance phases. For participants completing the coaching phase ahead of other participants, maintenance data were collected once per week until all participants had completed the coaching phase. After all participants had completed the coaching phase, maintenance data were collected 2.5 weeks later.

Results

Results of Coaching on Teacher Behavior

Results showing the effects of coaching on the three participant teachers’ implementation of function-based interventions are shown in Figure 2. The graph shows participants’ results across teacher baseline (teacher-implemented function-based interventions), during the coaching phase, and throughout maintenance. Each of the three teachers had low performance during baseline, which was followed by coaching to increase to higher performance levels. Results indicated a functional relationship between coaching and an increase in teachers’ accurate implementation of function-based interventions. The fourth participant’s results (Mrs. Green) are shown in Figure 3. Mrs. Green had a high, stable baseline and did not require coaching.

Figure 2.

Teachers’ percentage accuracy implementing function-based interventions.

Figure 3.

Fourth participant’s percentage accuracy implementing function-based interventions.

Mrs. Yacht’s baseline showed a stable, decreasing trend. Her scores ranged from 47.8% accuracy to 7.7% accuracy, steadily declined throughout baseline (M = 29.4%). Once coaching was introduced, the data showed an immediate change in level and trend. The data for the coaching phase are stable at a high level, with little variability. Her scores ranged from 95.8% accuracy to 100% accuracy (M = 99.2%). It is also important to note that Mrs. Yacht required only two coaching sessions before meeting the criteria to stop implementing coaching sessions. During maintenance, her data remained stable at a high level of 100% accuracy.

Mrs. Williams’ baseline showed a low, slightly variable data path with no trend. Her scores ranged from 17.2% accuracy to 4.0% accuracy (M = 11.0%). Once coaching was introduced, there was an immediate change to a high level with no variability or trend. Mrs. Williams consistently scored 100% accuracy during the coaching phase and also required only two coaching sessions. During maintenance, Mrs. Williams’ data path continued to remain stable with a high level of 100% accuracy.

Mr. Carlisle’s baseline data were low and slightly variable with no trend. His scores ranged from 10.5% accuracy to 21.3% accuracy (M = 15.8%). Once coaching was introduced, there was an immediate change to a high level, stable data path with no trend. His scores ranged from 98.4% accuracy to 100% accuracy (M = 99.7%). Mr. Carlisle also required only two coaching sessions. During maintenance, Mr. Carlisle also continued to perform at 100% accuracy.

Mrs. Green’s data were at a stable, high level with no trend during baseline. Her scores ranged from 94.3% accuracy to 100% accuracy (M = 98.2%). Due to Mrs. Green’s high performance during baseline, coaching was not introduced. During maintenance, Mrs. Green also continued to maintain her performance at 100% accuracy.

Teacher Generalization

Results of generalization data points are shown in Figures 2 and 3 as closed diamonds. Results indicated that coaching improved teachers’ ability to generalize the function-based intervention to another situation with the same student when the behavior served the same function. It is important to note that generalization probes were conducted during the teacher implementation of function-based intervention (e.g., teacher baseline) and maintenance phases. Generalization probes were not conducted during student baseline.

Student Behavior Results

To verify the hypothesis about the function of each student’s problem behavior, functional analyses were implemented comparing a condition designed to test the hypothesized function with a play condition for each student. The results of the FA indicated that Susan’s problem behavior was motivated by an attempt to secure teacher attention, while the remaining three students’ problem behaviors were maintained by escape from demands.

Results on the effects of the function-based interventions and the function-based interventions plus coaching on student behavior are shown in Figure 4. The graphs on the left show the results of the implementation of function-based interventions and implementation of function-based interventions plus coaching on the students’ challenging behaviors. The graphs on the right show the results of the implementation of function-based interventions and implementation of function-based interventions plus coaching on the students’ replacement behaviors. The graphs show student baseline, teacher implementing function-based interventions (teacher baseline), function-based interventions plus coaching, and maintenance phases.

Figure 4.

Students’ problem and replacement behavior.

Results show improvement for all students’ challenging behaviors either upon implementation of the function-based intervention (teacher baseline) or upon function-based intervention plus coaching. In addition, increases in students’ primary replacement behaviors are seen either upon implementation of the function-based intervention (teacher baseline) or upon function-based intervention plus coaching. There is a functional relationship demonstrated between implementation of the function-based intervention plus coaching and an increase in students’ primary replacement behaviors.

During baseline, Susan’s data for her problem behavior were highly variable, at midlevel, and with no clear trend. Her problem behavior ranged from 1 to 8 per session (M = 3.0). Her replacement behavior, appropriate use of materials, was at 0.0%, with no variability or trend. Once the teacher implemented the function-based intervention, Susan’s problem behavior dropped to zero rates, with no trend or variability. No problem behaviors were observed during this phase. Her replacement behavior demonstrated an immediate change in level, with some variability and no trend, and ranged from 30% to 50% of intervals per session during this phase. Once the coaching phase began, Susan’s problem behavior remained at zero and showed no change. Her replacement behavior demonstrated an immediate change in level and remained slightly variable with no trend and ranged from 60% to 80% of intervals (M = 66.0%). During the maintenance phase, Susan’s problem behavior remained at zero. Her replacement behavior had a slightly lower level than in the coaching phase; however, it remained at a slightly higher level than with the function-based intervention alone. Susan’s replacement behavior ranged from 40% to 50% of intervals (M = 45%).

During baseline, Karla’s problem behavior was highly variable with no clear trend and a fairly high level. Her problem behavior ranged from 0% to 90% of intervals (M = 52.5%). Her primary replacement behavior (compliance) was also highly variable with no clear trend and was at a midlevel. Compliance ranged from 10% to 100% of intervals (M = 47.5%). Her secondary replacement behavior (functional communication) was at zero and did not occur at any point during baseline. During the teacher-implemented function-based intervention phase (teacher baseline), Karla’s behavior showed a lower level, more stability, and decreased before stabilizing. Her problem behavior ranged from 0% to 30% of intervals (M = 10.0%). Her primary replacement behavior demonstrated a higher level, with increased stability, and increased before stabilizing. Compliance ranged from 70% to 100% of intervals (M = 90%). Her secondary replacement behavior occurred one time on the first session of the teacher-implemented function-based intervention; however, it did not occur during future sessions (range of 1 to 0 with M = 0.2 occurrences). Once teacher coaching began, Karla’s problem behavior showed a lower level with no trend or variability. She exhibited zero noncompliant behaviors during this phase. Karla’s primary replacement behavior showed an increase in level to 100% of intervals with no trend or variability. Her secondary replacement behavior (functional communication) did not occur during this phase. It is worth noting that Karla expressed being highly motivated to stay engaged in the activities to earn her reinforcer as quickly as possible and therefore stopped using her functional communication phrases. In maintenance, Karla’s problem behavior remained at zero. Her primary replacement behavior remained at 100% with no variability or trend. Karla’s secondary replacement behavior (functional communication) did not occur during maintenance phase.

During baseline, Michael’s problem behavior was initially stable at a midlevel with no trend. Then, Michael’s problem behavior showed a change in level to a lower level but did stabilize at the new lower level. It is unclear what caused this change in his behavior; however, because his behavior did stabilize, the function-based intervention phase (teacher baseline) was introduced. Michael’s problem behavior ranged from 15% to 60% of intervals during baseline (M = 39.2%). His primary replacement behavior (on task) showed a reverse pattern, with stable behavior initially at a midlevel, then a change to a higher level where it stabilized. On-task behavior ranged from 40% to 85% of intervals (M = 60.8%). His secondary replacement behavior (functional communication) occurred zero times during baseline. Once the teacher began the function-based intervention, Michael’s problem behavior demonstrated a slightly lower level with low variability. The problem behavior ranged from 10% to 25% of intervals (M = 19%). His primary replacement behavior demonstrated a slight increase in level with low variability and no trend. It ranged from 75% to 90% of intervals (M = 81.0%). His secondary replacement behavior (functional communication) showed an increasing trend with low variability. Functional communication ranged from 0 to 13 occurrences per session (M = 6.4). Once the coaching phase began, Michael’s problem behavior decreased to a lower level and was fairly stable with no trend. The problem behavior ranged from 0% to 10% of intervals (M = 4.0%). His primary replacement behavior showed an immediate change to a higher level, was relatively stable, and showed no trend. It ranged from 90% to 100% of intervals (M = 96.0%). His secondary replacement behavior (functional communication) was stable and variable. Functional communication ranged from 5 to 10 occurrences per session (M = 7.4). During maintenance, Michael did not display any problem behavior, which is reflected in his data path. His primary replacement behavior occurred in 100% of intervals. Michael’s secondary replacement behavior remained consistent with previous levels with a frequency of 6.0 occurrences of functional communication.

During baseline, Jack’s problem behavior was highly variable, at a high level, and with no clear trend. The problem behavior ranged from 30% to 100% of intervals (M = 65.0%). His primary replacement behavior (on-task behavior) also showed a high amount of variability with a midlevel and no clear trend. It ranged from 0% to 70% of intervals (M = 35.0%). His secondary replacement behavior (functional communication) had zero occurrences during baseline. During the function-based intervention phase (teacher baseline), Jack’s problem behavior showed a decreasing trend, with a lower level, and less variability. It ranged from 10% to 50% of intervals (M = 36.0%). His primary replacement behavior had an increased level, with an increasing trend, and less variability. It ranged from 50% to 90% of intervals (M = 64%). His secondary replacement behavior (functional communication) did not occur during this phase. During maintenance, Jack’s problem behavior occurred in 10% of intervals, which is as low as his lowest data point during the function-based intervention phase. His primary replacement behavior occurred for 90% of intervals, and his secondary replacement behavior did not occur, which remains consistent with the function-based intervention phase.

Social Validity

The teacher participants answered a social validity questionnaire to determine their perception of the effectiveness of the function-based interventions, the feasibility of implementing function-based interventions, the effectiveness of coaching, and whether coaching was a socially acceptable method for improving accuracy of implementation of function-based interventions. Teachers also had the opportunity to write additional comments in an open-ended comments section. Only the three teachers who received coaching answered questions that asked about the coaching procedure. Teachers rated the degree to which they agreed or disagreed to statements on a Likert-type scale. The rating scale was labeled with numbers 1 through 5, with 1 being strongly disagree and 5 being strongly agree.

Each of the four teachers strongly agreed with the following statements: “Implementing function-based interventions is important when working with students with challenging behaviors,” “I will use function-based interventions with other students in the future,” and “I will continue to implement the designed function-based intervention with the target student.” Of the three teachers who responded to the following statements, all three strongly agreed: “Coaching helped me better implement function-based interventions with this student,” “The coaching sessions were not intrusive to my daily routine,” “Coaching was cost efficient,” and “Using coaching is a socially acceptable way to provide additional training beyond the workshop model.” Three of the teachers strongly agreed and one teacher scored a 3 for the following two statements: “The student demonstrated an increase in his or her adaptive behavior” and “The student demonstrated a decrease in his or her challenging behavior.” Finally, one teacher wrote the following response in the comments section:

I learned a lot from the coaching and implementing function-based interventions. I am going to try and implement these interventions in the regular education classroom. I am going to provide coaching to the regular education teacher. I am very happy with the coaching and results.

In addition, the school psychologist completed a different questionnaire that included a question about the intrusiveness of the coaching procedure on the school schedule and whether she would recommend coaching as a follow-up to workshop training. The school psychologist strongly agreed with each of the following statements: “Implementing function-based interventions is important when working with students with challenging behaviors,” “Coaching helped the teachers implement the function-based interventions with students with challenging behaviors,” “Coaching was cost efficient,” “The students demonstrated an increase in their adaptive behavior,” “The students demonstrated a decrease in their challenging behavior,” “I would consider recommending coaching as a way to help teachers implement new strategies following a workshop training,” and “Using coaching is a socially acceptable way to provide additional training beyond the workshop model.” She rated a four for the following statement: “The coaching sessions were not intrusive to the school’s daily routine.”

Discussion

The purpose of this study was to evaluate the effects of coaching on special education teachers’ implementation of function-based interventions with students with severe disabilities through the use of a delayed multiple-baseline across-participants design. This study also sought to examine whether teachers could generalize function-based interventions to different situations with their students. In addition, this study examined the effect of the function-based intervention on the students’ problem and replacement behaviors.

After an initial training on completion of FBAs and implementation of function-based interventions, coaching was provided by the researcher to each teacher. Results indicated that there was a functional relationship between implementation of the coaching procedure and an increase in teacher fidelity scores. Three of the teachers had low levels of accuracy during baseline (e.g., after the workshop training alone). These teachers’ data each have an immediate change in level after coaching to high, stable data paths. Each of the three teachers’ behavior show immediate increases after the implementation of the coaching procedure. The fourth teacher (Mrs. Green) was able to implement the function-based intervention with high accuracy after the workshop alone. Her data path demonstrated a high level of accuracy, and therefore, she was not introduced to the coaching intervention. It is important to note that Mrs. Green had previous experience and training in ABA and FBA.

The results of the study demonstrate that all teachers were able to generalize their skills to a different activity with the target students. Each of the three teachers who required coaching had low levels of generalization during baseline. Their generalization scores during the baseline period were similar to their baseline data. After the coaching phase was complete, the teachers each demonstrated the ability to generalize to a different activity with 100% accuracy. This change in fidelity can be attributed to the coaching intervention, as generalization data remained at unacceptable levels during the baseline phase, but rose to acceptable levels after the teachers received the coaching intervention. The fourth teacher was able to generalize the function-based intervention during baseline and maintained this skill when observed again during the maintenance phase. This indicates that once teachers have been coached on how to implement function-based interventions during one activity, they may be able to generalize those procedures to similar activities throughout the school day for that specific student.

A functional relationship was also found between accurate implementation of the function-based interventions and an increase in the students’ primary replacement behaviors. All students’ data paths for their primary replacement behaviors indicate an immediate change in level upon accurate implementation of the function-based intervention. In addition, each student’s problem behavior decreased during implementation of the study; however, some students’ problem behavior decreased upon initial implementation of the function-based intervention (teacher baseline) even when the intervention was not implemented accurately. Other students’ problem behavior did not, however, decrease until the coaching procedure was implemented (corresponding with accurate implementation of the function-based intervention).

There are a number of conclusions that can be drawn from these data. First, the data show that for some students, partial implementation of a function-based intervention is enough to produce a reduction in the problem behavior. For some students, however, accurate implementation is required before a reduction in problem behavior is observed. Second, accurate implementation of the function-based intervention is required to create sufficient changes in the students’ primary replacement behavior. This has important implications toward the potential for students to maintain behavioral decreases over time. Interventions that focus solely on reducing problem behaviors, but do not teach replacement behaviors, do not maintain strongly when the intervention is removed because students have not been taught an appropriate way to fulfill the function of their problem behaviors (Cooper et al., 2007). This indicates the reductions observed in the students’ problem behaviors upon occurrence of the partially implemented function-based interventions (during the teacher baseline phase) may not have maintained over time. These results indicate that attempting to implement portions of a function-based intervention may be better than not implementing an intervention; however, accurate implementation of function-based intervention produces the best student outcomes.

Limitations and Implications for Future Research

There are several limitations to the current study. First, the study did not examine removal of the expert (i.e., the experimenter) from initial completion of the FBA process. The experimenter worked with each teacher during the workshop training to develop the hypothesis for the function of each student’s problem behavior and develop the corresponding function-based interventions. The experimenter also conducted the FA to confirm the hypothesis. Teachers working with students on a daily basis may not need to confirm the hypothesis through use of an FA; however, conclusions cannot be drawn regarding teachers’ ability to complete FAs from the results of this study. This prevents the researcher from drawing conclusions about how to fade expert support from completion of the FBA process and limits conclusions to accuracy of teacher implementation of function-based interventions. Teachers in schools often work as part of a team to develop FBAs for students with problem behaviors; therefore, future research should focus on accuracy of completion of FBAs by school teams in addition to teacher implementation of function-based interventions.

A second limitation was the use of the experimenter as the coach. Because the experimenter acted as the coach, it is unclear how and whether the coaching procedure could be transferred to another professional within the school system. It may be possible to train psychologists, Board Certified Behavior Analysts, or teachers who perform well in baseline to act as coaches; however, this study did not examine how much or what type of training would be required to ensure that the coaching procedure could be successfully taught to other professionals. Future research should examine what type of professional would best translate into future coaches and what type of training and preparation is required.

A third limitation of this study was the use of relatively long intervals when measuring student behavior using partial and whole interval or momentary time sampling (1-minute or 30-second intervals). The intervals needed to be long enough that teachers could reasonably take data while instructing the student or a group of students during normally scheduled classroom activities. Use of longer intervals could lead to over or underestimation of behavioral occurrences when compared with shorter intervals (Cooper et al., 2007). For example, when tracking Karla’s noncompliant behavior using 1-minute partial intervals, she may exhibit the problem behavior during the first 5 seconds of a 1-minute interval, but then she may have been on task for the remainder of the interval. This means the teacher and researcher would record that the behavior did occur for the 1-minute interval; however, if shorter 10-second intervals were used, the data would reflect that she was noncompliant during the first 10-second interval but on task for the remaining five 10-second intervals. Future research could use alternate methods for data collection (e.g., videotaping student behavior). Thus, shorter intervals could be used while not sacrificing teacher accuracy of data collection.

A fourth limitation surrounds the changes in student behavior. It is not clear, at this time, which students’ problem behaviors will decrease with inaccurate implementation of function-based interventions and which students require accurate implementation. It is also unclear what percentage of teacher accuracy is required to produce consistent results across all students. Future research should examine what degree of accuracy is required from teachers to consistently produce behavior change from students.

Implications for Practice

The results of this study indicate a number of implications for practice. First, in-service/workshop training alone is not sufficient to train most teachers to accurately implement FBAs and function-based interventions. School districts and administrators might consider adopting a training model based on expert coaching to provide teachers individualized support. Workshop and in-service trainings should include time for teachers to work with experts to plan for implementation of FBAs and function-based interventions with their individual students.

A second recommendation for practice is for school systems to identify a group of qualified professionals who have demonstrated success in developing and implementing FBAs and function-based interventions, and who could serve as coaches. The coaches can then spend a short amount of time with each teacher in need to provide targeted coaching. This will hopefully allow school systems to utilize coaching methods in a time- and cost-efficient manner.

A third recommendation arises from the fourth teacher participant in this study. This teacher demonstrated the ability to implement the function-based intervention accurately with her student after the workshop training alone; however, this teacher was not implementing a function-based intervention for this problem behavior with this student prior to the workshop. This suggests that some level of support is still required to help teachers complete FBAs and develop appropriate function-based interventions. It might be helpful for schools to develop an FBA team that meets regularly to review cases and help teachers complete FBAs and implement function-based interventions. These teams could consist of administrators, teachers, school counselors, and/or school psychologists.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Keri S. Bethune is an assistant professor at James Madison University and is a BCBA-D (Board Certified Behavior Analyst–Doctoral). Her research interests include applied behavior analysis, teacher education (including coaching), general curriculum access for students with severe disabilities, and autism.

Charles L. Wood is an associate professor at the University of North Carolina at Charlotte. His research interests include high-incidence disabilities, students at risk, evidence-based practices, reading instruction, and applied behavior analysis.

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