Self Monitoring

Introduction

What are you doing right now? If you just read the previous sentence, then you are reading, right? In addition, since this is in an educational journal you might also consider this as part of your professional development by learning a practice and/or engaging in research. Could you also say that you were self-monitoring? Well, if you answered either of these opening questions, then you were.

Article Purpose

In the coming pages we discuss the process of self-monitoring, which is an essential skill for all students to master. We have chosen to write this article for three reasons. First, we believe that the practice of having students self-monitor their own academic and/or social-emotional behavior makes sense, especially for those with emotional disturbance. Second, any one of us – students, teachers, support professionals, and administrators – can use self-monitoring to help us become a better professional. Rispoli et al. (2017) summarized findings from 17 studies in which teachers self-monitored their own implementation of behavioral interventions, and found self-monitoring to be a promising practice for increasing implementation accuracy. Third, as educational researchers we are interested in learning what components of a written document help you in knowing about or using a given research- or evidence-based educational strategy, intervention, or approach to improve the lives of students with emotional and behavioral disorders (EBD). Your reading of this manuscript and answering a series of survey questions once you are through reading will help us learn what a good practitioner article looks like.

Self-Monitoring: A Definition

We chose a definition of self-monitoring that was written by Mace, Belfiore, and Hutchinson (2001) and included in previous empirical reviews of the broader self-management/self-regulation literature for students with EBD (Mooney, Ryan, Uhing, Reid, & Epstein, 2005; Popham, Counts, Ryan, & Katsiyannis, 2018). According to Mace and colleagues (2001), self-monitoring is a two-stage process of observing one’s behavior wherein the person monitoring discriminates occurrence or non-occurrence of a target behavior (Step 1) and then self-records some aspect of the target behavior (Step 2). We want you to think of the self-monitoring intervention or process as noticing (a behavior) and noting (its existence), to help improve behavioral performance.

Make yourself a student for a few seconds. If before having you read this article we had set up a self-monitoring program designed to improve your use of down time in school, we could have identified silent reading as an activity to monitor and an activity useful to engage in during free time. We could have then trained you to monitor your silent reading activity, identified a specific time in which to have you practice self-monitoring (and better use of down time), and then asked you to read the first page of this article and self-monitor – notice and note – how you did. All of this is written to describe and provide an example of self-monitoring in action, both its planning and implementation. We want you to be able to teach your students to notice and note their own behavior, which is another example of the process. You doing the monitoring for the student, in contrast, would be a nonexample of a student’s self-monitoring.

Self-Monitoring: A Rationale for Use

It is likely that if you have a student with EBD in mind who could benefit from a self-monitoring intervention, then others know him or her as well. This population of students sticks out in the school setting, most likely for behavioral excesses. One, this student’s behavior has become a problem in the school context. By definition, a student verified with emotional disturbance has been formally evaluated by a team of school professionals and parents/caregivers Nelson, Benner, & Mooney, 2008). Team members have collectively indicated that the student’s behavior is – and for a long time has been – so problematically different from same age peers as to warrant an individualized program of instruction. The behaviors of concern can result in the student acting out on the environment through noncompliance or aggression and/or acting in on himself or herself through displays of depressive or anxious symptomology (Nelson et al., 2008).

As a group, students with EBD have walked and likely still traverse a troubling path. In addition to the behavioral concerns which contribute to consideration for special education, these students often have co-occurring academic and/or language deficits which collectively make school a tough place to succeed (Lane, Barton-Arwood, Nelson, & Wehby, 2008; Nelson, Benner, Neill, & Stage, 2006). Once these students are through with schooling, negative pathways may remain as these individuals are more likely to be involved in the criminal justice or welfare systems and less likely to be fully employed and self-supporting (Walker, Ramsey, & Gresham, 2004). These negative outcomes signal a need for intervention and the earlier the better. Developing self-sufficiency through the fostering of self-monitoring and/or other responsible behaviors like goal setting and self-advocacy allow a student with EBD to exert more control over his or her behavior, performance, and environment and, we hope, experience more instances of accomplishment and success (Carter, Lane, Crnobori, Bruhn, & Oakes, 2011). Since the monitoring of behavior is designed to change behavior for the better, the inclusion of self-monitoring development in the programs of many students who struggle in school makes sense.

A second rationale for promoting self-monitoring is because of its flexibility of use within the schoolhouse doors. Think about it. Self-monitoring interventions can be applied to students from preschool through high school and all grades in between. Self-monitoring interventions can and have been applied across teachers and subject areas and even settings. Self-monitoring interventions can include many elements, including with or without technology. There are as many self-monitoring applications as there are students and situations for which they are needed. Moreover, there is a body of research that, when reviewed, displays positive findings across student types, subjects, settings, and scenarios. The scholarship related to students with EBD is what we describe next.

Self-Monitoring and EBD: The Empirical Support for Use

Researchers can report the results of single experimental studies on students with EBD or they can summarize findings from a collection of studies – literature reviews – looking for similarities and differences across inquiries. We highlight two takeaways from three literature reviews conducted over the past 20 years (Bruhn, McDaniel, & Kreigh, 2015; Mooney et al., 2005; Popham, Counts, Ryan, & Katsiyannis, 2018). First, results from all of the reviewed studies, which were described as targeting either self-monitoring, self-management, or self-regulation, were positive when treatment condition scores are compared to baseline results. In the most recent review (Popham et al., 2018), treatment outcomes for the self-monitoring studies were calculated using three metrics and described as mildly to moderately effective, with moderate to large effects reported for both the reading and math content areas. Second, the makeup of the self-monitoring interventions was varied. Bruhn and colleagues (2015) discovered that components within the self-monitoring interventions they evaluated included the use of feedback, reinforcement, and technology. Specifically, in 25 of 41 studies feedback was provided. In 25 studies reinforcement was provided, nearly always (n = 24) reinforcement contingent on either accurate recording, achieving a goal, or following procedures. Technology was examined in two ways. The first result was that in 22 of 41 studies a prompting device was utilized to elicit the recording of student behavior. The second result was that in only two studies did students record their behavior on devices other than paper and pencil.

Self-Monitoring: A Step-by-Step Process

As just noted, a number of different self-monitoring interventions are described in the literature (Bruhn et al., 2015). We chose to combine treatment models described by Menzies, Lane, and Lee (2009) in a previous issue of Beyond Behavior and Reid and Lienemann (2006) in a book on strategy instruction for students with learning disabilities. The decision to merge structures came because we believe that both sets of authors were clear in describing the planning, implementation, and evaluative features of fostering self-monitoring. With Beyond Behavior a practitioner journal, we also appreciated Menzies and colleagues’ (2009) attention to the “balance between scientific rigor and feasibility within the classroom context” (p. 29). To us, that meant that the authors were thinking of you, the reader and practitioner, trying to foster understanding of a scientifically-researched practice (which is a legal mandate) and increasing the likelihood of it being understood and used effectively in the real world with students with EBD.

As we describe the steps, we organize them in terms of a planning (before and while teaching the student), implementing (while monitoring its effectiveness), and evaluating (after some monitoring time) framework so that all of the elements in which you will engage if you choose to implement the intervention are emphasized. We include a checklist of implementation items that can be used to facilitate the fostering of student self-monitoring. Table 1 includes these steps as well along with elements of each step and a place for you to indicate if, when developing student skill, you complete the action (YES), do not complete an action called for (NO), or do not complete an action because it was not applicable or necessary in the given situation (NA). We also include a graph later on in our vignette that displays the effects of implementation over time (see Figure 1).

 

Table 1
Self-Monitoring Implementation Guide and Treatment Integrity Checklist

Self-Monitoring Intervention Action

Planning

 

Implementing 

Evaluating 

Note: NA = Not Applicable. Adapted from content included in Menzies, Lane, and Lee (2009).

Planning

Step 1: Determine appropriateness.

Your first job is to determine if a self-monitoring intervention is a smart choice for the present circumstance. Menzies et al. (2009) developed four yes/no questions to answer in making this determination, with four yeses allowing you to conclude that, yes, self-monitoring is a reasonable route to follow. The first question asks you if the student can perform the expected behavior that you will soon define clearly (Menzies et al., 2009). The question is asked so that you are targeting a performance deficit in the student or a “won’t do” issue rather than a “can’t do” (acquisition deficit) concern. If the student can do the expected behavior, then proceed. If the behavior cannot be completed by the student, then some degree of explicit teaching is warranted before you move forward.

The second question asks you to determine if the student can control the behavior (Menzies et al., 2009). You need for the answer to be yes in order to proceed. If the answer is no, then successful intensive intervention that is informed through an assessment of behavioral function is warranted before self-monitoring of an expected controllable behavior is initiated. The third question asks you to gauge the frequency of the problem behavior that you want changed (Menzies et al., 2009). Again, if the answer is yes, that the behavior occurs regularly, then proceed with consideration of self-monitoring. If the answer is no, then the answer is to choose an alternate behavioral intervention approach. The fourth question addresses whether or not the behavior (problem and replacement) can be readily observed and recorded (Menzies et al., 2009). If it can, then self-monitoring has merit as an intervention avenue to pursue. If it does not, then a better understanding of the concern is warranted and maybe a behavioral consultant or problem-solving team can help you move forward.

A final question is suggested by Reid and Lienemann (2006) and a common practice in cognitive strategy instruction/intervention. You need to secure the student’s commitment to the process. After all, if the student is not willing to monitor himself or herself at the moment, then your next steps may lead to more frustration than what you are presently experiencing regarding the problem behavior. Reid and Lienemann (2006) suggest that you schedule a conference with the student and describe your concerns as well as what options lie ahead in terms of the potential benefits of self-monitoring and the drawbacks of doing nothing. Reid and Lienemann (2006) caution against promising too much and suggest that a contract be drawn up that establishes a desired reward provided upon the student meeting the intervention expectations. This is the contingent reinforcement element that Bruhn et al. (2015) described in their review of research. Commitment on the part of the student may even be enough to change the behavior in a positive direction. With four yeses and a commitment, then the noticing and noting actions can take place. It is time to clearly define the problem and replacement behaviors.

Step 2: Operationally define the behaviors.

Since you have answered the previous set of questions, you already have in your mind a problem behavior of sorts, and maybe even an appropriate replacement behavior. Now it is time to clearly define both. With your student, come up with a written definition of the behavior of concern that is concrete, replicable through role play, and identifiable and recordable to a stranger/outside observer. Menzies et al. (2009) suggest that you and your student discuss and role-play the suggested problem behavior so that there is both understanding of and agreement with the behavior as defined. The same or similar identification process follows for the replacement behavior.

In selecting the behavior that you will ultimately support your student in observing and recording, Reid and Lienemann (2006) recommend that in addition to the target behavior being specific and observable, that it is appropriate and a personal match. In terms of appropriateness, Reid and Lienemann (2006) advise that you attend to both setting and task, making sure that there is a fit between the student intervention action and the location – for example, the student is not embarrassed by self-monitoring during independent work time – and task – for example, that the intervention does not detract from active engagement during a small-group reading lesson. Reid and Lienemann (2006) describe personal match in terms of ensuring that the student is old enough and developmentally capable of understanding that the reason for the self-monitoring intervention is to improve performance of a particular behavior. Change may not take place, the authors suggest, if that cognitive connection is not made.

The behavior that you and your student choose as the replacement can either be academically- or behaviorally-focused. Menzies et al. (2009) suggest that there be a focus on academic productivity, which makes sense given the broad-based achievement delays that are characteristic of students with EBD (Lane et al., 2008). Usable, easily measurable examples of specific, measurable, appropriate, and personally-matched target replacement behaviors include the number of passage words read correctly or the time spent actively engaged in instruction. Non-measurable target behavior examples could be “poor problem solving” or “being good.”

Step 3: Collect baseline data.

A major part of the planning process is determining the present level of behavioral performance. Think of the contents of the individualized education program (IEP) that describe your student’s special education program. One of the critical elements is the present level of academic achievement and functional performance from which annual goals can be written and progress can be evaluated. These baseline data serve the same purpose as establishing a starting point to which future goals can be directly connected.

If there is an academic focus to your target behavior (review Step 2 findings), and the number of passage words read correctly is your focus, then have the student read equivalent grade- or instructional-level passages on three successive days and count the number of words read correctly in the passage or in a time frame (e.g., one minute). Choose the median number of the three and consider that your baseline and then maintain the probes along with other equivalent passages so that progress monitoring can take place. If the goal is behavioral, such as active engagement, then determine what the observational time frame will be and develop a time-sampling approach, such as partial-interval recording. In that case, you or a named observer is going to block out a series of timed increments, such as 15-second blocks, and look up in the first 5 seconds of each block to ascertain if active engagement is or is not occurring. At the end of the time period, the number of active engaged blocks is divided by the number of active and nonactive blocks and then multiplied by 100 so that you have a measure of active engagement for which future comparisons can be made. It may make sense to collect these behavioral data on three consecutive days to ensure that there is stability in terms of the measurement of active engagement. In that case the middle score – like the academic approach – could be considered your baseline. It also makes sense to collect similar data on an appropriately achieving peer in the class so that data-based and context-considered comparisons can be made for evaluation purposes.

Step 4: Design the intervention and monitoring form.

Now that you and your student have a clear and shared idea of what behavior you want to see flourish in your classroom – raising a hand to speak to you; hands, feet, and body to self for two-minute segments at a time in the lunch line, greater correct responding during reading or math work – as well as what you want to see vanished, it is time for you to develop the self-monitoring plan that you will teach to your student. That will include how the student will notice and on what he or she will note the target behavior. Plan development first involves determining when and where the student self-monitoring is going to take place. The time for self-monitoring might depend on the behavior chosen. That is, the keeping one’s hands, feet, and body to one’s self behavior in the lunch line gives you a clear delineation of when that will take place. Increases in correct academic responding, on the other hand, could be monitored for part or all of a day, in one, two, or all subjects.

The where self-monitoring takes place enables you to plan for the short- and long-term development of student proficiency. Sure, in the short-term, you want your student to be well-behaved with the data to prove it in your classroom for the next few weeks. But what about five weeks from now? Next semester? With your paraprofessional or a substitute teacher? Now is also the time for longer-term maintenance and generalization planning. In the short-term, that is accomplished through development of the monitoring sheet. So match the behavior to the chosen when and where on paper or through technology. In the longer-term, think when and where else the behavior can take place and contact relevant parties to share with them what your intentions are and short-term plan and monitoring sheet look like. We include a sample self-monitoring sheet in an application vignette that will follow description of the intervention steps.

One last thing to consider in the design process is how complicated you want the intervention to be at its inception. That is, do you want the complete focus on student self-monitoring, so that the above elements are addressed and that is all? Or do you want to add elements such as feedback and/or reinforcement to the mix. (Remember the results of the Bruhn et al. [2015] literature review). Menzies et al. (2009) proposed that a self-monitoring intervention could be bolstered by adding goal setting and reinforcement contingency features to the intervention. In this example, you could examine your baseline data to determine a performance goal for which a student can strive to reach. That goal could be derived from improvement in the student’s own performance or it could come from the performance of peers, presumably what you think is appropriate behavioral performance in the classroom. Then Menzies et al. (2009) suggested that you could structure your intervention so that there is either access to preferred activities such as adult or peer praise or additional computer time for meeting the predetermined goal or breaks from nonpreferred activities such as writing time. By adding these features you could be engaging in your own assessment of the purpose or function of the student’s behavior that has bothered you and led you to the point of developing an intervention and crafting your intervention so that the student gains either preferred or nonpreferred activities through a more appropriate display of behavior.

Step 5: Teach the self-monitoring procedures.

You might think implementation starts now but we maintain that it does not because you remain responsible for directing activities. The student is not yet independently self-monitoring because you are teaching him or her how to. So consider it still part of the planning process. You have already been in discussion with the student in developing the target behavior. See this teaching process as an extension of that.

Be explicit in your instruction, using effective instruction principles (I do, We do, You do) that are recommended for use with all students, but particularly for students with disabilities. That is, reiterate the rationale that was part of your thinking in initiating a self-monitoring program in the first place and part of your discussion with your student when the appropriate behavior was identified. Model the actions that you want the student to carry out using a think aloud, which adds your dialogue about why you are taking the action steps as you are modeling them. Once your model is finished, then guide the student through a shared practice, where he or she is completing the steps as you ask questions about what is next and why we are doing what we are doing. When the student is answering all of your questions about the complete intervention correctly, then move to independent practice to let him or her complete the entire process – or some form of it if it involves correct academic responding over a full day – by himself or herself.

Implementation

Step 6: Oversee self-monitoring implementation.

With data confirming that the student can perform the task, your job becomes monitor and supporter of student action. You watch the student self-monitor from a distance and evaluate his or her mastery of the process and discipline in proceeding or lack of one or both. Use the monitoring form that you have trained your student to use to track progress. (See Figure 2 for an example form.) This allows you to help determine the accuracy and honesty of the student’s intervention process. It also permits you to informally evaluate the utility of the developed intervention. In the best of circumstances, you learn that the intervention as developed is a good fit for the context in which it is being implemented. Alternatively, you may realize that some pieces can be fine-tuned following a period in which student data are collected.

Neither Menzies et al. (2009) nor Reid and Lienemann (2006) provide suggestions for how long the intervention is to take place, though Reid and Lienemann (2006) note that if there is success that it will be noticed quickly. What may guide your process is the stability of the data. That is, is measured performance consistently at baseline level for the replacement (ineffective) or above baseline (potentially effective) for at least the number of data points that you collected during baseline? If there is instability in the series of data, then continued data collection is warranted along with problem solving to ascertain what may be contributing to the instability. If a goal has been established as an element of the intervention, then you might consider setting a number of consecutive times that meeting or exceeding the goal will be considered a reaching of the short-term objective. This goal determination process is much like that completed with the measurable annual behavioral goals that are included in an IEP.

Step 7: As the data allow, program for maintenance and generalization.

If you have stable data that are above your baseline data or you have met the pre-established number of consecutive goals, then the data warrant a celebration of short-term success and a consideration of the longer term ambitions. For maintenance of the behavior, you can suggest that student self-monitoring continue and you check the data periodically to evaluate its ongoing effectiveness and potentially offer reward contingent on continued student action or continued meeting an established success criterion. Think to yourself and consider sharing with your student that you want this successful behavioral activity – self-monitoring and more correct responding or body parts to him or herself in the lunch line – to continue for the next month or quarter or year. For generalization, you want this successful behavior exhibited elsewhere for the benefit of the student, his or her teachers, and potentially others including the student’s parents or caregivers. In this part of the intervention process, then, others are brought in to support evaluation and to expand the intervention’s reach, all in the name of attempting to foster continued success and build this into the student’s unconscious behavioral practice.

Evaluation

Step 8: Determine effectiveness and next steps.

As you have probably noticed, your evaluation of the intervention’s effectiveness has been ongoing for a while. But it is important to mention them explicitly as part of the overall intervention implementation process. Understanding if the steps of the process are manageable and meeting the initial expectations, then determining whether the data collection – noting – process is workable in the context, comparing the accuracy of the reported scores to what you observe, and determining where else that intervention is warranted are all pieces of determining the effectiveness of the intervention. An objective “read” of the data by you, your student, and others who you may involve will help you determine where you move from here. Making sure that those next steps have a direct connection to the annual measurable goals of the IEP for a student with EBD is a relevant action for you and/or the IEP team members to take. That way, we believe that your actions would demonstrate that you offered, as the 2017 Endrew F. v. Douglas County School District United States Supreme Court decision made clear, “an IEP reasonably calculated to enable a child to make progress appropriate in light of his circumstances” (p. 16).

It is also important for you and your student to determine if either or both of you liked the process and thought it was beneficial. Acceptability of treatment may make one or both of you more likely to engage in the behavior in the future when a relevant problem needing this type of solution presents itself. Perceptions of treatment acceptability may be influenced by the success by which the intervention was implemented as intended. What is known as treatment integrity is important because it helps you determine what led to the success or lack thereof experienced during implementation. Treatment integrity data can be collected by using information in Table 1 to determine the proportion of relevant steps implemented – those marked yes – versus the number of relevant steps needed to implement – those marked yes plus those marked no. A criterion for successful implementation is any proportion at or above 80 percent. If implementation data fall below 80 percent, then any potential intervention failure might be attributable to the fact that the intervention was not implemented as intended.

Self-Monitoring: A Vignette

Johnny was a third grade student verified with emotional disturbance the grade previously. His general education teacher Ms. Rowley’s review of the multidisciplinary evaluation report indicated that regular verbal outbursts directed at adults and peers across settings and regular fights with peers were the behaviors of concern leading to the evaluation. It was difficult to ascertain what interventions had previously been tried prior to special education evaluation from a review of records. A lone IEP annual behavioral goal indicated that Johnny would cooperate with peers in academic and nonacademic settings. Unfortunately, it was unclear from a reading of the document how cooperation was expected to be measured, and what baseline levels of performance and future goals were. The present levels of performance section of the IEP also indicated reading and math achievement delays for Johnny, both in terms of standardized achievement test results and curriculum-based measurement (CBM) benchmark scores. CBM norms placed Johnny at below the 10th percentile in oral reading fluency and at the 20th percentile in math concepts and applications.

Ms. Rowley felt fortunate that in the first six weeks of third grade she had not observed any aggressive outbursts in the school setting, but she was concerned that Johnny’s frequent expressions of frustration with peers in the classroom and on the playground were isolating him from prosocial interactions. And, yes, there was the fall reading benchmark score suggesting that any reading intervention that had been attempted in second grade had not been effective in developing his reading skills in comparison to peers. His median oral reading fluency score of 40 words correct per minute in a third grade passage was well below the low-risk performance of 70 words correct per minute. Ms. Rowley decided that she was going to partner with Johnny to improve his academic and behavioral performance and show him that he could succeed in school with concerted effort. With consent obtained from Johnny’s parents Ms. Rowley scheduled a meeting with Johnny and his special education teacher, Ms. Haney.

Developing Johnny’s self-monitoring skills was an immediate thought of Ms. Rowley as she contemplated moving forward. One, she knew that it was a pathway to Johnny learning self-control, which would be good for Johnny and those around him inside and outside her classroom. It might even have a positive impact on the IEP goal of building cooperation skills. Two, she and her colleagues had received training on the subject from the school psychologist during the year-opening inservice. It had been presented as a potential teacher response to students not meeting schoolwide/classwide behavioral expectations. Ms. Rowley believed that a proactive approach to dealing with Johnny’s early classroom social struggles made sense and she decided that she would involve the school psychologist, Ms. Porter, in the process.

When general education teacher and school psychologist eventually met, they used a checklist similar to that in Table 1 and created on Google Sheets as their guide forward, realizing that the odds of success would increase if they implemented the intervention as intended versus moving forward piecemeal with what self-monitoring intervention elements both thought would be useful. Use of Google Sheets also ensured that the data could be viewed regularly by both colleagues.  Ms. Rowley and Ms. Porter identified active student engagement as their target behavior for two reasons. One, it had been described during the opening inservice, so both were familiar with it. Two, it seemed to both colleagues that the behavior would have the largest positive impact on Johnny’s behavior, allowing him, in the best of circumstances, to receive reinforcement across subjects, settings, and people. The Shapiro (2011) definition of active engaged time (AET) was utilized: “those times when the student is actively attending to the assigned work” (p. 42). Examples of AET included writing, reading aloud, raising a hand, and talking to the teacher or one or more peers about the assigned material. Nonexamples of AET included talking about nonacademic material, moving about the classroom without having been directed to, calling out non-task-oriented information, and any other off-task behavior (Shapiro, 2011).

Ms. Rowley went through the initial planning checklist items, answering the first four questions listed in Table 1 (e.g., can the student control the behavior?) and then soliciting Johnny’s commitment. It took a week or so of convincing Johnny that the intervention might be useful to him. She wanted him to understand the potential benefits of self-monitoring so she paid attention to academic successes and struggles in the classroom and let him know during one-on-one conversations that the successes that he was experiencing could be increased if he changed his behavior. At the same time, she made a concerted effort to identify students that she believed were self-monitoring their work performance and verbally praised those efforts in group settings in which Johnny was a participant. During her conversations with him Ms. Rowley let him know that he could be the one that was being praised during instructional activities if he agreed to be a part of the intervention. After receiving a few positive words on the potential for self-monitoring from his parents one night after school, Johnny agreed to develop his self-monitoring skills and told his teacher the next morning upon entering the classroom.

Baseline data collection commenced shortly thereafter. Ms. Rowley decided that she was going to start small with the process and asked the psychologist to observe active engagement behaviors for Johnny and a compliant peer for three days during reading instruction. Ms. Rowley also asked the special education teacher, Ms. Haney, to progress monitor weekly in reading, something that had not been occurring consistently at the time. A look at the left-most data points on Figure 1 indicated that active engagement was evident about 40 percent of the time before the intervention was developed and explained. Reading CBM data using grade-level oral reading fluency probes confirmed that Johnny’s performance was well below grade level and comparable to the September benchmarking scores.

The self-monitoring intervention consisted of a technologically-assisted notice and note routine. That is, the MotivAider prompting device was purchased and set to pulse at 2-minute intervals. For the 30 minutes of small-group reading instruction, whenever the pulse was activated, the student was to determine whether he was or was not actively responding to small-group instruction and record his response (YES or NO) on his Google Sheets self-monitoring form (see Figure 2). Johnny was shown the self-monitoring form and the intervention was explained to him by Ms. Rowley, who used a think aloud routine to encompass the “I do” portion of the explicit instruction training. The “We do” portion involved Ms. Rowley asking and Johnny answering questions about the process and Ms. Rowley leading Johnny through practice scenarios in which active engagement examples and nonexamples were presented. When Johnny said he felt comfortable knowing how to complete the intervention, Ms. Rowley allowed him to practice independently for brief portions of consecutive start-of-the-day homeroom settings so that an “I do-We do-You do” sequence was completed. After two independent sessions, the intervention process began for small-group reading instruction. The school psychologist agreed to monitor the reading period three times over the first 10 days of the intervention period so that an effort could be made to confirm Ms. Rowley’s own thoughts about the accuracy and honesty of Johnny’s self-monitoring. Otherwise, it was Johnny’s reporting that sufficed for data recording. Data were entered into a graphing program daily (see Figure 1 for results and Figure 2 for one day’s example of data collected). Ms. Rowley checked in with Johnny daily to offer her support for his behavior change efforts as well as to gauge how Johnny felt he was doing. Ms. Porter’s observations came later in the intervention period and confirmed Johnny’s reporting of meeting an 80% goal.

 

Johnny's Self-Monitoring Sheet, Day 9

 

Ms. Haney began twice weekly progress monitoring using the oral reading fluency CBM instrument. An end-of-year goal was set for the 35th percentile in grade level material and data-based individualization procedures were initiated with the help of the school psychologist to increase the intensity of specially designed reading instruction.

Ms. Rowley met with Johnny after 10 days of self-monitoring to give her own data-based reflections on the process and to elicit his perceptions of his performance and ability to maintain the behavior. Johnny was pleased with his progress and wanted others to know, so Ms. Rowley agreed to send a copy of the graph home with him so that she could refer to it when she called his mother. Ms. Rowley also arranged for “chance” celebratory meetings with Ms. Haney, Ms. Porter, the principal, and his second grade teacher. She also promised Johnny that she would catch Johnny being good twice a day for the next week at times of her choosing, agreeing to award Johnny double school bucks for every time that occurred.

Ms. Rowley also let Johnny know that she wanted his improved engaged behavior to continue and asked him to think of a new classroom and teacher to which the self-monitoring plan would expand. She enlisted additional support from the school psychologist in ensuring that the expansion would take place as seamlessly as it could.

 

Self-Monitoring: Tips for Teachers

We offer two tips for teachers willing to build the self-monitoring skills of students with EBD. First, increase the probability of implementation success by soliciting help from your professional peers. In simpler terms, get help; do not initially try this alone. Students with EBD, by virtue of the special education identification process, have behavioral excesses and/or deficits that have confounded multiple professionals before you. Also, effective intervention implementation involves a good bit of planning. So build your support network. Researchers Ennis and colleagues (2018) supported a resource special educator in completing a self-monitoring study for students with disabilities and included a student teacher and classroom teacher in the plan’s implementation. Teachers involved in the experiment indicated that the process was acceptable in the classroom setting and student outcomes included increased academic engagement for all three students targeted. In the vignette, general education teacher Ms. Rowley solicited help from the school psychologist and then her special education teacher colleague. In real life, these professionals may be great resources for you, along with members of schoolwide behavioral and/or academic support teams. Colleagues may be able to provide help in determining a measurable and meaningful variable to track implementation effectiveness. They may help you with data collection. They may be a constant voice of support in your ear at the end of the day.

Second, utilize technology. The Bruhn et al. (2015) review of self-monitoring interventions for students with behavior problems evaluated how technology was utilized in the research and found that it was regularly used in the “noticing” but not the “noting” components. Devices such as the MotivAider and cell phones were used to prompt behavioral monitoring in 22 of 41 studies. The MotivAider was used in the vignette as well. However, Bruhn et al. (2015) found that technology was used to record behavior following monitoring in only two studies. The vignette highlighted the use of Google Docs and Sheets so that data on AET could be collected and shared across parties. In recent years, other technologies such as the SCORE IT app (Bruhn, Goin, & Hasselbring, 2013) that is available on iTunes may be utilized not only to eliminate paper-pencil recording, but also to facilitate sharing and interpretation of relevant data. Additional technology-focused article references are included in Table 2.

 

Table 2
Listing of Technology-Oriented Publications to Assist with Self-Monitoring Intervention Implementation

Conclusion

Self-monitoring interventions have been demonstrated to be effective mechanisms to improve the behavioral performance of students with EBD. The present article provided a definition of self-monitoring, rationale for its use, summary of available research, step-by-step procedures for planning, implementing, and evaluating use, an application vignette, and tips for successful practice. The article was also written to include all of the elements that it was thought would increase the likelihood of practitioner knowledge gain and successful implementation with a student with EBD.

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