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The purpose of this study was to examine the effects of MoBeGo, a mobile self-monitoring app, on the initial and sustained academic engagement and disruptive behavior of third- to eighth-grade students with challenging behavior. Student-teacher pairs (N = 57) were randomly assigned to the treatment (MoBeGo) or control (business-as-usual) condition. We conducted systematic direct observation of students' behavior throughout prebaseline, baseline, intervention, and postintervention conditions of the study. Multivariate multilevel models revealed differential improvement for the MoBeGo group in student outcomes (less disruptive behavior; more academic engagement) from baseline to intervention, as well as successful postintervention effects for disruptive behavior. Limitations, future directions, and implications for practice are discussed.

High school students, particularly those with disabilities, often struggle with academic engagement in general education classes. One empirically supported method for improving academic engagement includes self-regulation interventions. However, individual effects of frequently used self-regulation strategies' goal setting and self-monitoring remain unknown. To address this issue, we implemented a multiple-probe single-case design with embedded alternating treatments to evaluate the differential impact of behavioral goal reminders and self-monitoring. The sample consisted of three high school students with emotional or behavioral disorders (EBD) in general education classes who also received special education services. Innovative approaches to intervention design included student-determined behavioral goals and self-monitoring procedures informed by triangulated behavioral assessment data. Although visual analysis indicated only moderate improvements in academic engagement, and no functional relationships were determined for either the multiple-probe or alternating treatments designs, the intervention was rated with high social validity from teachers and students, and the study represents an exemplar of high-quality special education single-case research. Practical implications, limitations, and directions for future research are discussed.

Self-monitoring is one of the most widely used and widely researched strategies for improving student behavior. However, specific research-based guidance about how to design effective self-monitoring interventions and to whom they should be delivered does not yet exist. To this end, we examined how various treatment components and participant characteristics moderated response to self-monitoring interventions. We included 66 single-case studies on academic engagement and 21 single-case studies on disruptive behavior. These studies included 290 participants with challenging behavior, 183 of whom had a disability. After extracting raw data from original studies, we analyzed data using multilevel modeling for each dependent variable (i.e., academic engagement, disruptive behavior). Across both dependent variables, student age and educational setting impacted treatment effects, as did the inclusion of goal-setting, feedback, and reinforcement. Based on our findings, we describe implications related to designing self-monitoring interventions. We also discuss limitations and future directions.

Self-monitoring interventions for students with challenging behavior are often teacher-managed rather than self-managed. Teachers direct these interventions by completing parallel monitoring procedures, providing feedback, and delivering contingent reinforcement to students when they monitor accurately. However, within self-monitoring interventions, the degree to which teachers and students agree in their assessment of students' behavior is unknown. In this study, a self-monitoring intervention in which both teachers and students rated the students' behavior, we analyzed 249 fixed interval ratings of behavior from 19 student/teacher pairs to determine the relationship between ratings within and across teacher/student pairs. We found a strong correlation overall (r=0.91), although variability existed within individual pairs and student ratings tended to be higher than teacher ratings. We discuss implications for practice, limitations, and future directions.

Data-based individualization (DBI) is a process of collecting and analyzing data on students' response to intervention and then making intervention adaptations accordingly. Although this process can lead to better student outcomes, very few teachers are trained in the components of DBI, particularly in relation to behavior. Improving practice requires not only ongoing professional development but also understanding about how teachers' experiences in training can lead to better outcomes. Within the context of implementing a behavior intervention, the purpose of this study was to evaluate how participating in ongoing professional development on DBI affects teachers' perceptions of themselves in relation to the DBI framework over time. Using a convergent, parallel mixed-methods research design, we evaluated the conceptual understanding, self-efficacy, and perceptions associated with DBI before, during, and after professional development of 16 general and special education teachers. Data analysis indicated teachers reported significant improvements in all three areas over time. Qualitative data indicated active practice and collaboration with other professionals contributed to these improvements. Key findings, limitations, and future directions are discussed.

School-Wide Positive Behavior Interventions and Supports (SWPBIS) relies on effective implementation of Tier 1 practices to ensure accurate identification of students in need of more intensive supports at Tier 2 or Tier 3. While measures of school-level fidelity are widely used, measures of classroom-level implementation of Tier 1 supports are less common. If classroom levels of Tier 1 supports are variable, schools may identify students for Tier 2 supports when, instead, teachers need support implementing Tier 1 in classrooms. The purpose of this case study was to assess the impact of a self-monitoring intervention, Monitoring Behavior on the Go (MoBeGo), on the academic engagement and disruptive behavior of a middle school student. Initially, the impact of the self-monitoring intervention was inadequate. In the context of evaluating the impact of a Tier 2 intervention, we identified an opportunity to assess whether a class-wide Tier 1 program, Class-Wide Function-Related Intervention Teams (CW-FIT), enhanced the effectiveness of the Tier 2 intervention. Using an A-B-BC-B-BC design, we compared the effectiveness of a Tier 2 intervention alone with a combined Tier 1 + Tier 2 intervention. When the class-wide Tier 1 program was layered on top of the Tier 2 intervention, the student's academic engagement showed an increase in level and stability.

The majority of students with disabilities and behavioral challenges are taught in general education classrooms. Although these students may receive interventions resulting in positive behavioral changes, little is known about the collateral effects of implementing behavior intervention plans (BIP) on classroom peers with similar behavioral problems who are not receiving an intervention. The purpose of this study was to investigate the effects of functional behavioral assessments (FBAs) and BIPs for students with challenging behavior as well as their peers. We measured target student and peer academic engagement, as well as treatment integrity and social validity. As a result of the intervention, target students demonstrated increased academic engagement. In addition, results suggest that the FBA-BIPs had small effects on engagement for some peers.

With the advent of Precision Teaching more than 50 years ago, researchers and practitioners began to examine how to use K-12 students' academic data to guide instructional decisions. Although the field has advanced with the use of curriculum-based measurement and data-driven decision rules for reading and math, the same is not true in the area of social behavior. In this article, we provide a brief retrospective of academic decision making to inform an initial call for research related to behavioral decision making. Then, we highlight areas for exploration related to baseline data, measurement tools, and features of behavior that, if answered via rigorous scientific inquiry, can move the field forward in making data-based decisions to improve behavioral outcomes.

The COVID-19 global pandemic left many educators making an emergency transition to remote instruction when schools were initially closed. Although this transition was likely difficult for most students, it may have been particularly difficult for students with emotional or behavioral disorders, who have complex and resource-intensive social, emotional, and behavioral needs. The purpose of this study was to examine the extent to which special educators and related service providers felt they were able to meet those needs in the context of the pandemic occurring in the Spring of 2020. Results indicated respondents' perceptions of their ability to meet students' needs and implement their students' Individualized Education Programs (IEPs) were moderated by policies on remote instruction and students' access to technology. In addition, respondents suggested district- and school-level response strategies, professional development on remote instruction, access to the internet at home, and additional technology would be helpful in future school closures. Implications and limitations are discussed.

Targeted Tier 2 interventions are critical to supporting students with challenging behavior and decreasing the resources associated with highly individualized and intense interventions. This study extends findings from recent single-case design studies and case example applications of the Tier 2 Identification and Intervention framework with the first large-scale evaluation of school-level outcomes following district implementation. We employed a pretest-posttest design within one large urban school district (N = 23,042 students) to evaluate school-level discipline outcomes for elementary schools who received training and coaching on the Tier 2 framework. Fidelity (i.e., Tiered Fidelity Inventory) and school-level demographics (e.g., poverty status, race) were entered as covariates into the generalized linear models. Results indicated statistically significant decreases in office discipline referrals and in-school suspensions for schools with adequate Tier 2 fidelity. Implications, limitations, and future directions are discussed.

In this descriptive study, we analyzed survey data regarding communication, instruction, and assessment strategies school personnel in K-12 settings reported using during the COVID-19 pandemic for students with emotional and behavioral disorders (EBD). Results indicate, whether instructional continuity was mandated or not, support personnel serving students with EBD reported using a variety of communication, instruction, and assessment strategies. Several strategies special educators reported using were significantly different than those provided by related service providers (e.g., school psychologist, counselor) during school site closures. Implications for future planning, policy, and research are discussed.

In recent years, high schools have turned to PBIS to address issues related to dropout rates, school climate, and disciplinary practices. However, high schools pose unique implementation challenges when compared to elementary and middle schools, such as large school sizes, organization and culture focused on academics rather than behavior, and the developmental level of students. These challenges can impact buy-in, fidelity, and outcomes, as well as long-term sustainability. Thus, the purpose of this case study is to describe one high school's approach to Tier 1 systems, data, and practices; including professional development, roll-out, and implementation procedures. Through a one-year partnership with a local university, the high school demonstrated improvements in fidelity, student outcomes, and buy-in. Limitations and implications for research and practice are discussed.

An emerging body of research shows Tier 1 Positive Behavioral Interventions and Supports (PBIS) can be successfully implemented in high schools to improve school climate and graduation rates and reduce problem behaviors. However, high schools are often hesitant to adopt PBIS because of contextual barriers such as school size, organizational culture, and student developmental level. Resistance to high school implementation is also related to teachers perceiving PBIS as less socially valid for high school students. Although previous systematic reviews of Tier 1 have examined implementation and effects, none have exclusively focused on the unique contextual needs related to high school implementation. In this review, we synthesized 16 published research studies conducted at the high school level, described how authors addressed the unique challenges of implementing PBIS in high schools, reported findings related to academic and behavioral outcomes, and made recommendations for future research and practice based on our findings.

The purpose of Tier 2 positive behavior interventions and supports (PBIS) is to address identified social, emotional, and behavioral needs with efficient, targeted interventions. Although only 10% to 15% of each school's population will require Tier 2 supports, without effective systems, practices, and data, students will continue to demonstrate unwanted behavior, which may lead to increased rates of exclusionary discipline (e.g., office discipline referrals and suspension). This article extends the logic of Tier 1 PBIS, which is founded in systems, practices, and data, by addressing research related to implementation issues of systems, practices, and data in Tier 2. First, we present current research and practice in systems with a specific focus on Tier 2 teaming, resources, and professional development (i.e., initial training and coaching). Second, we discuss Tier 2 practices and the need to consider intervention matching, as well as initial and in vivo intervention adaptations to improve acceptability and effectiveness. Third, we present Tier 2 data considerations for informing intervention design, progress monitoring, and treatment fidelity. Across Tier 2 systems, practices, and data, we offer recommendations for future research.

Data-based individualization (DBI) is a systematic process used to guide teachers in making decisions related to students' responsiveness to intervention. Whereas this process has been used extensively with academic interventions, far less is known about DBI used within the context of behavioral interventions. In this study, elementary general and special education teachers (a) implemented a technology-based, self-monitoring intervention with students exhibiting challenging behavior; and (b) used DBI to evaluate student progress and make intervention adaptations accordingly. Results of multilevel modeling indicated students improved their positive behavior significantly (p < 0.001) from baseline to intervention. For most students, once they began intervention, positive behaviors either maintained or increased gradually when teachers made adaptations to the self-monitoring intervention. In addition to these results, an analysis of the effects of different intervention adaptations (e.g., raising or lowering goals, increasing or decreasing interval length) and visual analysis of individual students' response are discussed.

Tier 2 social behavioral interventions are designed to support up to 15% of the school population; as such, they must be efficient and effective. The purpose of this article is to propose an adaptive, responsive approach to the implementation of social behavioral Tier 2 interventions, considering both core components and malleable features to increase the likelihood of improved student outcomes. We describe horizontal adaptations, which are based on student characteristics and contextual factors, as well as vertical adaptations, which are based on data indicating a student's response (or nonresponse) to intervention. These adaptations are discussed within the context of previous research on three commonly implemented Tier 2 interventions: check- in/check-out, self-management strategies, and social skills training.

Positive Behavioral Intervention Supports (PBIS) is a preventative and responsive three-tiered framework comprised of a continuum of evidence-based practices and interventions. Adaptation, or tailoring is a critical component to the PBIS system, as it is not intended to be a standard treatment protocol, particularly at the Tier 2 level. Tier 2 interventions require fidelity to core ingredients that make the intervention effective but issues still arise concerning the targeted intervention's implementation, student response, intensity need, and social validity that inform the tailoring of interventions at Tier 2. Currently, there is no clear protocol for adapting Tier 2 intervention. The purpose of this paper is guide implementers with the adaptation process by providing descriptions and examples of possible intervention adaptations based on (1) student characteristics, (2) intervention characteristics, and (3) setting characteristics.

For more than 20 years, the schoolwide positive behavioral interventions and supports (SWPBIS) literature base has been growing as it relates to implementation and sustainability across various settings and grade levels. While the research is clear that SWPBIS is an effective multitiered framework, gaps in the literature exist. Specifically, the extent to which SWPBIS has been implemented in traditionally underrepresented schools has yet to be fully examined. This systematic review of the SWPBIS literature base resulted in 46 articles that were coded across 13 variables. The number of articles highlight underrepresentation in the SWPBIS literature. Researchers demonstrated variable (a) reductions in rates of disciplinary infractions and exclusionary responses, (b) implementation with fidelity, and (c) positive student outcomes across academics, attendance, and achievement.

This study examined the relationship of teachers' ratings of students' 21st century skills (i.e., persistence, curiosity, externalizing and internalizing affect, and cognition) via the Human Behavior Rating Scale: Brief (HBRS: Brief; Eaves & Woods-Groves, 2011) with student performance. Midwestern K-11 teachers (n = 96) rated students (n = 1,689) via the HBRS: Brief and the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997). Students' academic (i.e., standardized tests) and behavioral (i.e., office discipline referrals [ODRs] and absences) performance was compared with HBRS: Brief ratings. Hierarchical linear modeling revealed that teachers' ratings of students' 21st century skills were related to the following: (a) Persistence with SDQ conduct problems, academic performance, and absences; (b) curiosity with SDQ emotional symptoms; (c) externalizing affect with SDQ conduct problems, academic performance, and ODRs; (d) internalizing affect with SDQ emotional symptoms and academic performance, and (e) cognition with academics.

This study examined the effects of coping power (CP) and the combination of CP with check-in/check-out (CICO) to determine whether the addition of CICO as a classroom component enhances the effects of CP alone. CP was delivered outside the classroom by research assistants, and all CICO components were implemented by classroom teachers. We conducted a study with a single-case experimental multitreatment design (i.e., A-B-BC-B-BC) with three elementary students at risk for aggressive behavior. We collected daily progress report scores as the primary dependent variable and periodic direct observation probes of disruptive behavior. In addition, we evaluated intervention fidelity for both interventions and students' and teachers' perceptions of the interventions. Visual inspection indicated variable responses to the combination of CP and CICO compared with CP alone, with one participant demonstrating a functional relation. Key findings, limitations, implications, and future directions are described.

Delivering high rates of opportunities to respond (OTR) has been shown to improve student outcomes for students with challenging behavior. High rates of OTR can maximize student engagement while providing ways for teachers to quickly assess student content mastery. Given the increasing trend of technology use in schools, teachers can leverage technology for delivering OTR. We discuss three technology-based tools teachers can use to enhance OTR delivery with examples of how to incorporate these tools into classrooms.

The Peacock Hill Working Group (PHWG) published a seminal position article nearly 30 years ago on the state of the field of special education for children with emotional and behavioral disorders (EBD). They concluded their discussion with a set of recommendations for practice, policy, and research. The purpose of the present article is to revisit the PHWG's calls to the field with an emphasis on setting a research agenda related to children and youth with EBD. As a follow-up to the problems and promises identified by the PHWG, we identify progress and priorities for each of their six calls for research to improve outcomes for students with EBD. We address the broader context underlying each recommendation and how it has changed over time, describe research progress to date, and identify priorities to move the field forward. The overarching goal of this article is to inform and help shape the next phase of research on EBD, which in turn will advance the implementation and scale-up of effective programs and practices to better meet the needs of students with EBD in schools.

The multitiered framework for preventing and addressing discipline and school climate, school-wide positive behavioral interventions and supports, is widely adopted across the United States with much of the focus on Tier 1, universal prevention supports. The following case example describes district-wide adoption of a systematic framework for Tier 2 identification and intervention in a rural, low-income Southwestern district. Both process and outcome measures are presented with regard to implementation fidelity, social acceptability, and tier movement as a preliminary evaluation of the framework. Implications for future research and practice as well as limitations are discussed.

Reports show that only 40% of 4th-grade students are proficient in math and American students are failing to demonstrate proficiency in key areas of mathematics (National Center for Educational Statistics 2011). Improving students' fluency of basic math multiplication facts has been recommended as a way to increase math proficiency ("Psychology in the Schools," 47:342-353, 2010). Incremental rehearsal is one promising strategy for improving multiplication skills. In this study, three 5th-grade students with disabilities who had Individual Education Plan math goals received one-to-one multiplication instruction using an incremental rehearsal strategy twice per week for 7 weeks. Data indicated immediate and large effects with intervention and growth rates for each student that exceeded expectations. Implications are discussed including the importance of considering both statistically significant and instructionally meaningful results in interpretation.

Students who are at risk for or show low-intensity behavioral problems may need targeted, Tier 2 interventions. Often, Tier 2 problem-solving teams are charged with monitoring student responsiveness to intervention. This process may be difficult for those who are not trained in data collection and analysis procedures. To aid practitioners in these worthwhile tasks, we offer a step-by-step guide to collecting and evaluating Tier 2 behavioral progress monitoring data. This systematic approach includes (a) selecting an appropriate method of measurement, (b) planning for data collection and evaluation, (c) collecting and analyzing data, (d) considering treatment fidelity, and (e) adjusting intervention based on student responsiveness. Each step is described in detail with specific examples and additional resources are provided.

The purpose of this commentary is to provide observation on the contributions to the special issue and remark on the broader implications of the research. As noted throughout the special issue, the intent was to demonstrate the use of progress monitoring within a problem-solving framework to evaluate student social and behavioral development using direct behavior ratings (DBR). Leveraging single-case research methods through adherence to the What Works Clearinghouse (WWC) standards, the articles included in the special issue provide examples for using DBR to assess student response-to-intervention while also illustrating a number of psychometric considerations that can strengthen the evidence base for progress-monitoring tools more broadly. In this commentary, we argue that the research included in the special issue provides a framework for conceptualizing evidence-based assessment for progress-monitoring instruments using single-case methods. Toward this end, the commentary provides an overview of the concept of evidence-based assessment and uses examples from the included studies to describe various facets.

Students who misbehave represent a range of backgrounds, and behavior problems are likely to be present in both general and special education classrooms. To this end, thousands of schools across the country have adopted positive behavior interventions and supports (PBIS) as a way to prevent and respond to challenging behavior. PBIS is a federally endorsed, three-tiered approach for promoting positive behaviors and implementing a continuum of data-driven interventions to students (Individuals with Disabilities Education Act, 2004). All students who attend schools that employ PBIS receive Tier 1 supports, which include (1) teaching universal, prosocial behaviors to prevent future problems; (2) implementing evidence-based classroom management strategies; and (3) acknowledging students when they display positive behaviors. Students who fail to respond to Tier 1 supports move to Tier 2, which are typically small-group, evidence-based behavioral interventions and supports. Finally, in Tier 3, students with high-risk behaviors who fail to respond to Tier 1 and Tier 2 supports (<5% of school population) receive highly individualized, intense behavioral interventions. Ensuring that newly acquired behavioral skills continue after an intervention has ended (i.e., maintenance) is the ultimate goal of behavioral interventions, but no matter how effective an intervention is, positive behavior is unlikely to sustain if the intervention is stopped abruptly (or "cold turkey") after the student experiences success. Instead, the intervention must be faded systematically by gradually reducing and eventually eliminating key elements, such as: (1) goals; (2) feedback; (3) reinforcement; (4) dosage; or (5) other intervention components. This iterative process of reducing or removing intervention components continues until all intervention components are faded completely, with the ultimate goal of transitioning students back to only Tier 1 supports.

Direct behavior ratings have been identified as a practical and feasible alternative to direct observation of behavior for monitoring behavioral progress. Despite the evidence of usability, there have been calls for further examination of direct behavior ratings using different behaviors and scales. To this end, we examined the ratings of schoolwide behavioral expectations by teachers and outside observers, as well as direct observation of academic engagement by outside observers in upper elementary school language arts classrooms. Across sessions, correlations between raters (range r = 0.82-0.91) and between measures (range r = 0.64-0.98) were moderate to high; significant differences between raters existed when rating students identified with negative behavior (n = 12) as opposed to positive behavior (n = 12). Findings are discussed in terms of implications for research and practice, limitations of the study, and the necessity for further research and development.

Paraprofessionals carry out behavior interventions for students with challenging behavior in inclusive classroom settings. Examination of paraprofessional involvement in behavior interventions informs how paraprofessionals may best support intervention implementation. The researchers used a withdrawal design to evaluate the effects of a multiple-component intervention primarily conducted by paraprofessionals in decreasing one sixth-grade student's disruptive behavior. They then used a systematic approach to functional behavior assessment to identify the function of the student's behavior and to design an intervention, which was tested using a single-subject design. Results demonstrated a functional relation between the student's disruptive behavior and intervention. Further, the paraprofessionals and classroom teacher regarded the intervention as favorable, suggesting the intervention was feasible and suitable for the student. Discussion includes implications for practice and future research.

Students with or at risk of emotional and behavioral disorders can benefit from a variety of self-regulation strategies. One such strategy is goal setting, which can be used to improve both academic and behavioral outcomes in the classroom. In this article, we discuss the importance of goal setting and current research in this area. In addition, we provide a step-by-step process for implementing goal-setting interventions in the classroom.

Multitiered frameworks like Positive Behavior Interventions and Supports (PBIS) have been recommended for preventing and remediating behavior problems. In this study, technology-based self-monitoring was used as a Tier 2 intervention to improve the academic engagement and disruptive behavior of three middle school students who were identified as at risk for failure and needing immediate intervention. Results of the multiple baseline design across settings indicated the intervention was highly effective for one student and moderately effective for another. The third student required more intense support than offered in Tier 2. Issues of matching students to Tier 2 intervention based on multiple data sources, the alignment of technology-based self-monitoring with key features of Tier 2, limitations of the study, recommendations for future research, and implications for practice are discussed.

Social skills instruction has been recommended as a way of improving behavioral and social outcomes for students with emotional and behavioral disorders (EBD). A brief social skills intervention ("Stop and Think" (Knoff in "The stop & think social skills program," Sopris West, Longmont, CO, 2001) was used to extend the current literature base for students with EBD. A multiple-baseline across classrooms design was used to examine negative social behavior of five participants attending a self-contained school setting for students with challenging behavior. The primary intervention components included: (a) teach, (b) model, (c) role play, and (d) performance feedback. Specific social skills addressed in intervention were listening, using nice talk, accepting consequences, ignoring others, and following directions. Participants were taught to use a 5-step process for each social skill: (1) stop and think, (2) identify good and bad choices, (3) identify steps to performing the good choice, (4) implement steps, and (5) reflect on the good choice you made. Results indicated students benefitted from 12 sessions of explicit social skills instruction as evidenced by decreases in negative social behavior. Social behavior improvements maintained during 2-week follow-up observations. Decreasing negative social behaviors is important in improving general social and behavioral outcomes as well as demonstrating growth toward being prepared to transition back to less restrictive environments. Limitations, recommendations for future research, and practice implications are discussed.

Students requiring Tier 2 behavioral supports frequently display behavioral deficits in multiple domains (e.g., emotional symptoms and peer problems). The Tier 2 framework developed by McDaniel, Bruhn, & Mitchell (2015a) is a responsive structure for identifying and intervening at Tier 2. This process is described with a practical case example of a student with multiple areas of risk. Stacking Tier 2 behavioral interventions for students who score in the "abnormal" range in multiple areas on the Strengths and Difficulties Questionnaire is described. A description of this process for delivering Tier 2 supports and the results from the case example are presented.

Keeping students engaged in the curriculum is extremely important when attempting to close the achievement gap for students with and at risk for disabilities. This is particularly important for students with learning disabilities or behavior disorders. This article discusses the use of applications (apps) for mobile technologies that may be used to motivate and thus engage students in the classroom by supporting best instructional practices. These apps are matched to specific strategies that researchers have suggested for increasing motivation and engagement.

There is substantial empirical evidence that the Functional Behavioral Assessment (FBA) process is an effective means to reduce student problem behavior and increase desirable behaviors (e.g., What Works Clearinghouse, 2016). The use of an FBA as the basis for a behavior intervention plan (BIP) has been a requirement for certain disciplinary actions since the amendments to the Individuals with Disabilities Education Act in 1997 (IDEA; 2006). This article provides an over view of the FBA-BIP process, and describes four common pitfalls associated with fidelity to the FBA-BIP process. Each pitfall is paired with a technical assistance suggestion. Implementing FBA-BIPs in a manner consistent with best practice will allow educators to create FBAs and BIPs that are not only helpful for students and teachers but also comply with legal requirements. Although the FBA-BIP process is a complex and time consuming endeavor, being aware of and able to avoid potential pitfalls will likely result in generating a valid hypothesis regarding the function of the behavior and increase the likelihood that a well-designed and implemented BIP will result in positive behavioral change.

Students with ADHD often struggle with self-regulation skills. One strategy demonstrating considerable success in helping these students regulate their behavior is self-monitoring. Although there is an abundance of research on self-monitoring, research on the use of technology for self-monitoring is only beginning to emerge. The primary goal of this single-subject study was to examine the effects of an iPad application ("SCORE IT") for self-monitoring on the behavior of three fifth-grade students with or at risk for ADHD who were exhibiting low rates of academic engagement in a general education environment. A secondary goal was to gain an in-depth understanding of the teacher's perceptions of the feasibility and value of the intervention. Overall, the "SCORE IT" intervention resulted in substantial improvements in academic engagement, and teacher perceptions of the feasibility and worth of the intervention were reported as highly favorable. Limitations and future directions for research are discussed.

AbstractHigh rates of teacher praise are associated with positive student outcomes (Royer et al., 2019). Research shows secondary teachers deliver more reprimands than praise (e.g. Floress et al. 2022). Performance feedback (PF) is a strategy used to change teacher behaviors. However, it is unknown if PF targeting praise and reprimands for secondary teachers is an evidence-based practice. Although reviews on PF exist, none focus exclusively on secondary teachers. This review was to synthesize 14 PF intervention studies targeting praise and reprimands for secondary teachers. We evaluated PF studies to determine if PF is an evidence-based practice. Results indicate PF targeting praise and reprimands cannot yet be determined as an evidence-based practice for secondary teachers. Limitations, implications, and future directions are discussed. [ABSTRACT FROM AUTHOR]

Check-in/check-out (CICO) is a Tier 2 behavioral intervention that has demonstrated effectiveness for students with challenging behavior in a variety of educational settings. Existing research has focused primarily on testing the intervention's effectiveness and the role of behavioral function in moderating response to intervention. Only a handful of studies have included examinations of different procedures for fading CICO to promote maintained behavioral change. These have included decreasing the frequency of teacher feedback, using a mystery motivator to thin the schedule of reinforcement, and increasing goal contingencies over time. In this study, two middle school females with conduct problems were identified for participation in CICO with goal modification. During intervention, the first modification entailed setting the CICO card goal for each participant based on averages obtained on the CICO card during baseline rather than the commonly used 80% goal. Then, predetermined decision rules about how to modify subsequent goals were executed according to student progress. Effects on student behavior were evaluated using a changing-criterion with withdrawal design, and scores on the CICO card improved and classroom problem behavior decreased for both participants. Limitations and recommendations for future research are discussed.

Technology in schools is abundant as is the call for evidence-based interventions for students who need additional support to be successful. One promising use of technology is for self-monitoring interventions aimed at improving classroom behavior. In this study, two middle school students with disabilities used a multicomponent, self-monitoring app on an iPad during their reading classes. Using a data-based individualization approach, teachers worked with the primary investigator to monitor students' response to the intervention and adapt the intervention accordingly. A single-subject design was used to test the effects of the intervention, and a functional relation was established for both participants who improved their academic engagement and decreased their disruptive behavior. Additionally, participants indicated the intervention was socially valid. Limitations, implications, and future directions are discussed.