Research on Self-Management Techniques Used by Students with Disabilities in General Education Settings: A Promise Fulfilled?

Dennis McDougall, Jim Skouge, and Anthony Farrell
University of Hawai’i, Manoa

Kathy Hoff
Illinois State University


Abstract
This comprehensive review synthesizes findings from 43 studies in which students with disabilities utilized behavioral self-management (BSM) techniques in general education settings. Findings suggest that the long-standing promise of BSM as an inclusive technique has been partially fulfilled. The review identifies strengths and limitations of BSM studies and BSM techniques, provides recommendations for future research and practice, and identifies BSM training materials.

Recent Research on Self-Management Techniques Used by Students with Disabilities in General Education Settings: A Promise Fulfilled?

Researchers and practitioners have long noted the promise of behavioral self-management (BSM) to improve academic and social outcomes, especially for students with disabilities and their teachers, and to promote inclusion of such students in general education (GE) settings (McDougall, 1998). Extensive support for BSM efficacy is evident in early reviews (McLaughlin, 1976; O’Leary & Duby, 1979), later reviews (Hughes, Ruhl, & Misra, 1989; Martin & Mithaug, 1986; Nelson, Smith, Young, & Dodd, 1991; Skiba & Casey, 1985; Stage & Quiroz, 1997; Wolery & Schuster, 1997), and recent reviews (Barry & Haraway, 2005; Hitchcock, Dowrick & Prater, 2003; Lancioni & O’Reilly, 2001; Mooney, Ryan, Uhing, Reid, & Epstein, 2005; Post & Story, 2002). However, very few of the hundreds of BSM studies  published since 1970 have targeted students with disabilities in GE settings. In this review, we examine BSM efficacy for students with disabilities in GE settings. We also evaluate how BSM has fulfilled its promise as an inclusive technique and provide corresponding recommendations.

The Promise and Benefits of BSM for Students, Teachers, and Inclusive Education
For students, BSM: (a) “has offered the promise of a set of procedures to modify undesirable behavior without relying on external agents (such as parents, teachers, peers) to administer reinforcement and punishment contingencies” (Christie, Hiss, & Lozanoff, 1984, p. 392); (b) “encourages the child to become a more responsible agent in the education process [and] engenders initiative and independence” (Rooney, Hallahan, & Lloyd, 1984, p. 360); (c) reduces dependence on external agents and teachers for reinforcement, control, and guidance (Nelson, Smith, Young, & Dodd, 1991; Workman & Hector, 1978); (d) helps students “learn and behave in the absence of adult oversight” (Prater, Hogan & Miller, 1992, p. 44); (e) helps students meet teacher expectations for routine performance in GE settings, including completing tasks accurately, arriving punctually at class, having materials ready, and completing homework  (Clees, 1994-5); (f) promotes self-regulation, responsibility, and skills that students use throughout their lifetime (Hogan & Prater, 1993); (g) reduces excessive or coercive adult control (Dunlap, Dunlap, Koegel, & Koegel, 1991; Falk, Dunlap & Kern, 1996); and (h) promotes active involvement and counters inactive learning styles, strategy deficiencies, inattentiveness, and passivity (Hallahan, Marshall, & Lloyd, 1981; Prater, Joy, Chilman, Temple, & Miller, 1991; Rooney, Hallahan, & Lloyd, 1984).

For teachers, BSM ‘frees up’ time to plan lessons, design learning environments, and instruct lessons rather than manage problem behaviors (Rosenbaum & Drabman, 1979; Trammel, Schloss & Alper, 1994). BSM requires less supervision compared to teacher-directed strategies (Dunlap, Dunlap, Koegel, & Koegel, 1991) and it increases efficiency by saving teachers’ time and money (Clees, 1994-5; Gardner, Clees, & Cole, 1983).

After passage of the Education of All Handicapped Children Act of 1975 and its corresponding mandate to provide services in the least restrictive environment, the literature noted the promise of BSM as an inclusive technique (McDougall, 1998). Rooney, Hallahan, and Lloyd (1984) reported that BSM “holds promise of use in mainstream settings” (p. 363) and “seems particularly well-suited for use in regular classrooms” (p. 360). In addition, Edwards, Salent, Howard, Brougher, and McLaughlin (1995) noted that BSM “holds promise for use in mainstream settings for students with very compelling educational needs” (p. 12) and that BSM “techniques are a powerful tool which might allow otherwise segregated children to be included in the regular classroom” (p. 16). The literature consistently cites a few reasons why BSM has the potential to promote inclusion. First, BSM techniques are portable across settings (Thoreson & Mahoney, 1974). Second, BSM techniques can promote maintenance and generalization of performance from training and special education settings to GE settings (Falk, Dunlap & Kern, 1996; Osborne, Kiburz & Miller, 1986; Rhode, Morgan, & Young, 1983). Third, BSM techniques are adaptable, unobtrusive, easy to implement, and accommodate individual students needs without overburdening teachers (Dunlap, Dunlap, Koegel, & Koegel, 1991). Thus, GE teachers, whose classes now include more students with disabilities than in the past, might be more willing to implement BSM than more intrusive procedures (Hogan & Prater, 1993; Prater Hogan, & Miller, 1992; Rooney, Hallahan, & Lloyd, 1984).

BSM Efficacy and the Need for Research and Application of BSM in General Education
In a comprehensive review of BSM studies published from 1970 to 1997, McDougall (1998) concluded that BSM produced relatively consistent moderate-to-strong outcomes for students with disabilities in inclusive GE settings. However, like Hughes, Ruhl, and Misra (1989) one decade earlier, McDougall (1998) lamented the unfulfilled promise of BSM, as evidenced by the paucity of Category III studies (n = 13), in which students with disabilities applied BSM techniques in GE settings, compared to more than 240: (a) Category I studies, in which students with disabilities applied BSM techniques in non-integrated settings, such as resource rooms; and (b) Category II studies, in which students without disabilities applied BSM techniques in GE settings. McDougall also identified issues for researchers and teachers to address when having students with disabilities use BSM in GE settings. See Table 3, left column. First, train students directly in the GE settings where they will use BSM techniques, rather than training them in special education settings and expecting generalization to GE settings. Second, ensure via periodic monitoring that students actually use the BSM techniques in the manner expected (i.e., punctually and accurately). Third, apply BSM techniques (self-evaluation, self-graphing, self-reinforcement, self-modeling, and self-instruction) and target dependent variables (social interaction, homework completion, and aggressive behaviors toward self and others) that are rare in Category III students, but which have empirical support via Category I and II studies. Likewise, expand use of BSM beyond: (a) academic classes, to the playground, cafeteria, hallways, gym, music, and art; and (b) students with learning disabilities, emotional-behavioral disorders, and AD/HD, to students with mental retardation, autism, and other disabilities.

BSM Models and Techniques
BSM techniques reviewed here are based on cognitive-behavioral models that attribute self-directed learning and behavioral self-control (BSC) to the reactive effects of cognitive factors, such as awareness and self-talk, and behavioral factors, such as antecedents, observable actions, and consequences (Kanfer & Karoly, 1972a, 1972b; Meichenbaum, 1977; Rachlin, 1974; Skinner, 1953). In 1973, Glynn, Thomas, and Shee proposed a four-component model of BSC: (a) self-assessment (e.g., covert questions about performance, such as “Am I on-task?”); (b) self-recording (e.g., overt responses to self-assessment questions, such as checking yes or no on a self-recording form); (c) self-determination of reinforcement (i.e., specifying types, amounts, and schedules of reinforcement); and (d) self-administration of reinforcement (i.e., delivering reinforcement contingent on performance). The first two components in this BSC model comprise self-monitoring, which can be cued covertly (i.e., student reminds self) or overtly (e.g., via tape-recorded audio cues). Meichenbaum (1977) described another traditional BSC component, self-verbalization or self-instruction, in which students talk themselves through a task (e.g., studying, “Look at the first word, say and spell it. Car, c-a-r.”).

In the 1980s, the term BSM replaced the term BSC. Researchers and practitioners reported that BSM skills were necessary for self-determination, whereby individuals with disabilities have “the capacity to choose and to have those choices be the determinants of one’s actions” (Deci & Ryan, 1985, p.38). Researchers have developed additional BSM components, such as: (a) self-graphing, whereby students obtain on-going feedback by charting results soon after they perform a task (DiGangi, Maag, & Rutherford, 1991; McDougall & Brady, 1998); (b) self-evaluation, whereby students judge the quality of their own performance (Grossi & Heward, 1998); and (c) video self-modeling (VSM), whereby students view videotaped images of themselves performing tasks and, thereby, serve as their own model (Dowrick, 1999; Hitchcock, Dowrick & Prater, 2003; Lonnecker, Brady, McPherson, & Hawkins, 1994).

Purposes of this Literature Review 
Our purposes were to analyze critically Category III BSM studies published since McDougall’s (1998) review and to provide corresponding recommendations for researchers and practitioners. We expanded upon McDougall’s three major questions.

1. “To what extent have researchers investigated the use of BSM techniques by students with disabilities in general education settings?” (p. 312). Have researchers expanded investigations of BSM techniques in integrated or inclusive settings?

2. “How have these BSM techniques been implemented (e.g., specific procedures used, participants and types of disabilities selected, and outcome variables targeted)?” (p. 312). Have investigators diversified BSM techniques and applied novel BSM techniques in integrated or inclusive settings?

3. “How effective have BSM techniques been in improving academic and social outcomes for students with disabilities in general education settings?” (p. 312). To what extent have BSM techniques fulfilled their oft-cited potential as inclusive techniques?  


Method

Search Process
The first author searched for Category III BSM studies using: (a) EBSCOhost, Academic Search Premier, ERIC, Professional Development Collection, PsycINFO, and Psychology and Behavioral Sciences Collection; (b) published reviews on BSM; (c) manual inspection and computer-index scanning of recent journal issues; and (d) reference lists of articles from the aforementioned sources. Initial web-based searches utilized the terms self and management and disabilities in the default field. Subsequent searches combined BSM terms (see Criteria for Selecting BSM Studies, item 4) with other terms (general education, special education, video, learning disabilities, emotional, behavioral, disorders, disturbance, impairment, autism, speech, hearing, visual, mental retardation, developmental disabilities, attention deficit, and hyperactivity). The first author read and eliminated all search-generated abstracts for articles that clearly failed to qualify for this review. Then he obtained, read, and screened full-text articles for all remaining abstracts via on-line services, interlibrary loans, and visits to libraries at major universities in five states in the US. We also contacted authors of difficult-to-access articles.

Criteria for Selecting BSM Studies
We used the following inclusion and exclusion criteria, which we adapted from McDougall (1998), to identify studies that qualified as Category III BSM interventions.

1. Study participants included at least one student with an identified disability according to guidelines from: (a) the 1997 Amendments of the Individuals with Disabilities Act or the Individuals with Disabilities Education Act of 1990; (b) Section 504 of the Rehabilitation Act of 1973; (c) state and local education agencies; and (d) national or provincial sources. We excluded studies that did not document disability status and those that only identified participants as being at risk or having learning or behavior problems.

2. Study settings included at least one GE classroom or school-related environment that included the concurrent presence of students with and without disabilities. Settings could not be only non-integrated locations, such as self-contained classrooms, resource rooms, or special programs, where only students with disabilities, or students with disabilities and ‘at-risk’ students, were present (e.g., Category I studies). Settings also could not be locations where only students without disabilities were present (e.g., Category II studies).

3. Dependent variables included quantitative measures of: academic engagement, performance, or outcomes; related academic variables; or social behaviors. We excluded descriptive studies without quantitative measures of targeted outcomes and studies that reported only qualitative measures, verbal reports, or anecdotal information.

4. Interventions included one or more BSM components: self-monitoring and its two constituent components, self-assessment and self-recording; self-evaluation; self-instruction; self-reinforcement; self-graphing; and self-modeling.

5. Studies were published in professional journals from January 1997 to June 2005.

Finally, because extensive documentation exists already (cf: Algozinne, Browder, Karvonen, Test, & Wood 2001; Graham, Harris, & Troia, 2000; Palmer & Wehmeyer, 2003), we excluded studies of self-regulated strategy development and self-determination unless the studies used BSM as the primary intervention.

Framework for Reporting Data and Coding Information from Category III BSM Studies
We adapted McDougall’s (1998) framework to report descriptive data in Table 1 and findings about procedural and outcome variables in Table 2. To bolster the credibility of information reported in Tables 1 and 2, we operationally defined variables of interest, used coding directions, and trained independent coders. The first author was the primary coder and the remaining authors and research assistants were secondary coders. We calculated appropriate indices of agreement that included: (a) percentage of inter-coder agreement (I-CA = equals number of agreements divided by number of agreements plus disagreements, multiplied by 100%); (b) Kappa (k) to adjust I-CA for chance agreements on dichotomously coded variables (Cohen, 1960); and (c) correlation coefficients (r).

Agreement for variables reported in Table 1 was as follows: total number of participants, number of female participants, and number of male participants in each study (r = 1.00); number of participants by disability (r = 1.00); settings (I-CA = 100%); dependent variables and dependent variables measurement (IC-A = 96%); independent variables (I-CA = 100%); research designs (I-CA = 100%). Agreement for variables reported in Table 2 was as follows: magnitude of intervention efficacy (IC-A = 86%); presence of information on intervention integrity (I-CA = 100% and k = 1.00 for both initial training and ongoing adherence to intervention procedures); magnitude of reliability of dependent variable measurement (I-CA = 100%); use of Kappa (I-CA = 100%, k = 1.00); formal use of maintenance probes or follow-up (I-CA = 100%, k = 1.00); formal use of generalization probes (I-CA = 100%, k = 1.00); social validity [(I-CA = 100% and  k = 1.00 for both the social comparison and subjective evaluation methods (Kazdin, 1982)].

Findings for Descriptive Variables
Table 1 and the following paragraphs summarize descriptive data from the 43 Category III studies that qualified for this review.

Authors and Year of Publication. The most prolific authors were Wehmeyer, Hughes, and Agran, who teamed and co-authored 9 studies. Buggey, Copeland, Fowler, and Rock authored 3 studies each. Blanchard, Church-Pupke, DuPaul, Horner, and Todd authored 2 studies each. Four to five studies were published each year from 1997 through mid-2005, except for 2003 (n = 3) and 2005 (n = 7).


Participants

Number. The 43 studies included a total of 385 participants (range = 1 to 123 participants). The median and mode number of participants was 3 (n = 11 studies). Nine studies had one participant and eight studies had two participants. Two quasi-experimental group studies had 172 (i.e., 123 and 49) of the 385 total participants. One applied behavior analysis or ‘small-n’ study with a multiple baseline design across three classrooms used 97 participants.

Gender and age. Sixty-seven percent of the participants were male and 33% were female. Authors of one study did not identify participants’ gender. Participants ranged in age from 4 to 19 years old. The number of studies that included primarily participants of the following age ranges were: 15 to 19 years (n = 6); 12 to 15 years (n = 9); 8 to 12 years (n = 17); 5 to 8 years (n = 10); and pre-k or 4 years (n =1).

Disability status. Twenty-two of the 43 studies included participants with a single disability; 21 studies included participants with more than one disability. In order of magnitude, these disabilities, with the corresponding number of studies that included participants with that disability in parentheses, were mental retardation (11), learning disabilities (10), autism (9), serious emotional disturbance or behavior disorders (7), speech-language impairments (7), AD/HD (4), Asperger (4), hearing impairments (3), developmental disabilities (3), and visual impairments (2). The following disabilities were represented in one study each – other health impairments, orthopedic impairments, physical disabilities, multiple disabilities, mild educational handicap, oppositional defiant disorder, and pervasive developmental delay.

Settings
Thirty-five of 43 studies utilized multiple settings and eight studies used a single setting. Some authors broadly identified settings as a GE classroom (n = 9 studies) or a special education classroom (n = 5 studies). However, most authors specifically identified classes. These classes, with the corresponding number of studies that utilized such settings in parentheses, were math (7), reading (5), physical education/gym (5), science (4), social studies (4), English (3), history (3), language arts (3), and art (2). In addition, each of the following classes served once as a setting in a study  – agricultural biology, agricultural mechanics, auto mechanics, cosmetology, Gaelic, life skills, occupational health, religion, and Spanish. Other settings were school hallways (4), playground and recess (3), free time (2), free play (2), work-time (2), seatwork (1), circle time (1), center time (1), lunch (1), study hall (1), homeroom (1), library media center (1), and a classroom leisure setting (1). One study used multiple settings outside the school, including a pubic library, a fast food restaurant, and a neighborhood street.

Dependent Variables
Thirty-four of 43 studies targeted multiple dependent variables. Dependent variables targeted most frequently, with the corresponding number of studies in parentheses, included: variations of on-task, engaged, and disruptive behaviors (25); social skills and communication (14); variations of academic performance (10); ‘classroom survival’ or ‘essential’ skills, such as having materials ready (9); and teacher praise (2). Homework completion was the primary dependent variable in one study, although additional studies incorporated homework completion as part of multi-faceted outcome measures. A few studies also measured teachers’ perceptions of participants’ performance or behavior. Teachers and researchers prescribed target behaviors in 37 studies. Participants selected or helped to select their target behaviors in the 6 remaining studies.

Measurement of Dependent Variables
Of the 39 studies that used observational recording systems to measure dependent variables, 24 reported data as the percentage of intervals in which the target behavior occurred. Nineteen studies reported simple frequency counts and 15 studies reported data on the percentage of responses, skills, or steps completed or completed correctly. Eleven studies collected permanent products, such as students’ written work. Eight studies used informal ratings, such as Likert-type scales, and six studies used formal instruments (e.g., published scales). Three studies reported rate, two studies reported duration, and one study reported latency. 

Independent Variables
Self-monitoring (n = 26) and self-evaluation (n = 19) were the most frequently applied BSM components, followed by self-reinforcement (n = 8), self-instruction (n = 6), VSM (n = 4), self-selection of goals (n = 3), and self-graphing (n = 2). Independent variables in 11 studies included antecedent cue regulation with visual or audio prompts, which included communication books, photo activity schedules, cards with pictures or written phrases, and self-operated auditory prompts. Independent variables in 17 studies included multiple BSM components. Finally, 29 of 43 studies combined BSM with ‘external’ intervention features, such as externally delivered reinforcement or prompts, corrective or performance feedback from teachers, and sessions when teachers and students compared their respective observations or data.     

Research Designs
Thirty-eight of 43 studies utilized small-n research designs. Three other studies utilized quasi-experimental group designs and the two remaining studies did not utilize systematic research designs (i.e., an uncontrolled case study and a descriptive demonstration). Of the 38 small-n designs, 3 used primarily reversal designs and 34 used variations of the multiple baseline, including 2 multiple probe designs. Two small-n studies used a changing conditions design rather than the designs that authors reported. A few investigators embedded additional small-n design elements (i.e., reversal phases, alternating treatments, and multiple probes) to supplement the primary research design of their respective studies. Finally, investigators often incorporated phases to fade intervention components.

Findings on Efficacy, Integrity, and Outcomes of BSM Interventions

Table 2 and the following paragraphs summarize findings for intervention efficacy, as well as procedural integrity and outcome variables.

Intervention Efficacy
For studies that used small-n research designs, we evaluated functional control of interventions. That is, we visually inspected graphed data for changes in means, changes in trends, changes in level, stability-variability, latency, and overlap (Kazdin, 1982). For studies that used quasi-experimental group designs, we examined results of inferential statistical procedures used to test research hypotheses. We also searched for author-reported effect sizes in all studies. In the 38 studies that used small-n designs, BSM interventions demonstrated: (a) strong functional control over target behaviors in 12 studies; (b) moderate-strong functional control in 8 studies; (c) moderate-mixed functional control in 9 studies; and (d) weak, limited, or no functional control in 9 studies. Three quasi-experimental group studies demonstrated mixed-moderate efficacy. Two studies failed to use systematic research designs, which precluded evaluation of intervention efficacy. Only 2 of the 43 studies reported effect sizes.

Intervention Integrity
We identified whether authors reported numerical indices to verify the quality of: (a) initial training procedures (e.g., training participants or teachers to a specific mastery criterion on BSM); and (b) treatment fidelity or adherence to ongoing intervention procedures (Mertens, 1998). Twenty-seven studies did not report an index for quality of initial training procedures and 29 studies did not report an index for adherence to ongoing intervention procedures. Only seven studies reported numerical indices for both of these elements of intervention integrity. These indices, when reported, almost always reflected high levels of intervention integrity.

Interobserver Agreement or Reliability Indices for Dependent Variable Measures
Thirty-five of 43 studies included indices of interobserver (IO) agreement or reliability for dependent variable measures. Of these 35 studies, IO agreement or reliability was high for 25 studies, moderate to high for 4 studies, and moderate in 5 studies. We could not evaluate reliability for one of these 35 studies because the IO calculation formula (A/A+D x 100%) reported appeared to be inconsistent with the dimension of measurement for the dependent variable (i.e., duration measures require the formula, shorter duration/longer duration x 100%). Although 38 of 43 studies used observational recording systems amenable to Kappa, only three studies used Kappa and only 2 of these 3 studies included clear data for Kappa.

Maintenance Probes or Follow-up
Investigators in 5 of the 43 studies formally assessed maintenance of changes in participants’ target behaviors. Formal assessment of maintenance required non-contiguous data collection - that is, an intervening period between the last session of the final intervention phase of contiguous data collection and the first maintenance probe or follow-up session. Maintenance was strong in each of these 5 studies and these investigators collected maintenance data 2 weeks to 6 months after the final intervention phase ended. Investigators in 23 of the 43 studies informally assessed maintenance when they collected contiguous data during: (a) post-training phases that immediately followed a training phase; or (b) phases when they faded, reduced, or removed intervention components. Maintenance was strong in most of these 23 studies. Finally, investigators in 15 studies failed to address maintenance.

Generalization
Investigators in most studies indirectly or directly addressed generalization of treatment impact. For example, investigators in 34 studies measured treatment impact on more than one dependent variable; 35 studies reported outcomes in more than one setting. Participants in eight studies were trained initially or first used BSM in special education settings, then applied BSM techniques in GE settings with additional or continual training, or with elements of initial training. Investigators in 35 studies trained participants or measured initial outcomes directly in GE settings and, thereby eliminated the need to determine whether intervention effects generalized from special education to GE settings. Three studies failed to address generalization in any manner, either directly (e.g., via generalization probes) or indirectly (e.g., via multiple dependent variables or multiple baseline designs).

Social Validity of Changes in Target Behaviors
Investigators in 23 of 43 studies assessed the social validity of improvements in participants’ target behaviors - 15 used subjective evaluation, 5 used social comparison, and 3 used both subjective evaluation and social comparison methods (Kazdin, 1982). Nearly all data supported the contention that changes in participants’ target behaviors were socially valid.


BSM in Inclusive Settings – A Promise Partially Fulfilled 

Based on findings from this review, BSM has partially fulfilled its oft-cited promise as an inclusive technique. However, only about half of the 43 studies reviewed here demonstrated moderate to strong efficacy, a few BSM techniques remained underutilized, and limitations plagued many studies. 

Proliferation of Category III BSM Studies
Journal publications of Category III BSM studies have proliferated greatly since 1997. McDougall (1998) identified 13 studies published in 8 journals from 1970 to 1997 – a publication rate of about one study every two years. We identified 43 studies published in 26 journals from 1997 to mid-2005 – a publication rate of about five studies per year. Consumers of these journals tend to be professionals in special education and disabilities. No studies of this type have been published in journals with GE titles. However, researchers have disseminated findings beyond special education to related services disciplines – a pattern not evident in McDougall’s previous review. Thus, we recommend further use of BSM in inclusive settings to help students monitor performance of skills acquired via speech, physical therapy, and counseling services. We also recommend that researchers publish studies in journals read primarily by general educators to promote awareness and use of BSM in GE settings.

Malleability of BSM Applications
Our second research question addressed how investigators have applied and diversified BSM techniques in inclusive settings. Since 1997, investigators have (a) applied traditional and novel BSM techniques, and (b) expanded the range of participants (disability and age), settings, and dependent variables. See Table 3. Self-monitoring in various forms continues to be the most frequently used and most versatile BSM technique. Emerging BSM techniques include self-recruitment of reinforcement and variations of self-instruction. Researchers also used BSM in conjunction with functional behavioral assessment, positive behavioral supports, and goal setting, and, thereby, established a trend toward having participants become more active agents in these interventions (e.g., by having students select target behaviors).

We recommend that teachers expand students’ use of self-monitoring in inclusive settings because it has the broadest empirical support of all BSM techniques. Moreover, self-monitoring is very versatile. Students can cue themselves to self-monitor via auditory, visual, and covert cues. Self-monitoring also can be combined with other techniques, takes relatively little time and expense to train, and can be faded quite easily. We also recommend that researchers investigate BSM techniques rarely used in Category III studies– tactilely-cued self-monitoring, VSM, and self-graphing.

Tactilely-cued self-monitoring. Tactile cues, such as those produced by vibrating pagers, might be useful for individuals who experience difficulty responding to visual and auditory cues, GE settings in which audio or visual cues might distract other students, and individuals who wish to maintain privacy. Instructional assistants also could use such cues to manage their proximity and prevent problems that arise when they ‘hover’ excessively near students with disabilities in GE settings. These problems include interfering with general educators’ ownership and responsibility of duties toward students with disabilities, promoting students’ overreliance upon instructional assistants, and limiting students’ opportunities for interaction with peers who do not have disabilities (Giangreco, Edelman, Luiselli, & MacFarland, 1997).

VSM. The paucity of Category III VSM studies is surprising for at least three reasons. First, for more than three decades, findings from studies and literature reviews provide support for the efficacy of self-modeling in various settings, for a wide range of individuals, across many behaviors, (Creer & Miklich, 1970; Dowrick, 1999; Hitchcock, Dowrick, & Prater, 2003; Hosford, 1980; Mehrag & Woltensdorf, 1990; Wert & Nesworth, 2003). Second, guidance is available on using VSM techniques, including positive self-review and video feedforward (Dowrick, 1997; Dowrick & Hood, 1978; Dowrick, Power, Manz, Ginsberg-Block, Leff, & Kim-Rupnow, 2001). Third, video technology has become more accessible and more affordable in recent years. However, VSM requires considerable time and technological effort compared to other BSM techniques. This might limit teachers’ willingness to use VSM. Studies illustrate potential use of VSM for students with disabilities in inclusive settings to improve: (a) attention span of preschoolers (Dowrick & Raeburn, 1977); (b) on-task behaviors of students with behavior disorders (Clare, Jenson, Kehle, & Bray 1986); and (c) talking among students with selective mutism (Blum, et al., 1998; Dowrick & Hood, 1978).

Self-graphing. Graphing is a simple and effective way to provide ongoing visual feedback on performance. For guidance, see two recent studies that combined self-graphing with goal setting and self-monitoring, and: (a) improved daily exercise, body weight, and cardiovascular fitness (McDougall, 2005); and (b) increased writing productivity (McDougall, in press). To maximize the reactive effects of self-graphing, students should: (a) receive systematic training in self-graphing; (b) graph their results consistently, frequently, and immediately after they complete a task; and (c) graph their performance of one or two specific, proactive tasks. Teachers can instruct students about two orientations for interpreting and acting on self-graphed data. In the personal improvement orientation, students aim to improve their performance over time and compare their current performance to their recent performance. In the normative orientation, students aim to improve their performance relative to their peers. Finally, students can post their graphs publicly or privately.

Age and time considerations. We recommend that practitioners show students how to use BSM techniques ‘sooner than later.’ Study findings suggest that students can apply many BSM techniques effectively during the early years of elementary school through young adulthood. Preschoolers might also benefit but additional studies are needed to verify this matter. We also recommend that teachers initiate BSM at the beginning of each school year as part of their classroom routine rather than waiting until problems arise. Claims about ease of use notwithstanding, BSM requires systematic training. Thus, we recommend that practitioners invest time efficiently during initial training. Moreover, practitioners should monitor students periodically, especially during initial use of BSM, to ensure that students use BSM techniques accurately and punctually. Finally, findings suggest that many GE teachers will require support in order to further the promise of BSM as an inclusive technique. Special education teachers can provide such support via direct collaboration with their GE colleagues in inclusive classrooms.

Room for Improvement – Methodological and Procedural Considerations
“Contemporary ABA [applied behavior analysis] standards require investigators to collect and report data that address not only outcomes for dependent variables but also maintenance and generalization of these targeted outcomes, along with social validity and IO agreement” (McDougall, 1998, p. 138).  In this review, 38 of 43 studies used ABA or small-N research designs. Most of these studies failed to meet one or more of the aforementioned standards. Nearly one-half of the studies failed to assess social validity and many of studies used only the subjective evaluation method. We concur with Pierce, Reid, and Epstein (2004) that the social comparison method appears to be underutilized. Thus, we recommend that researchers use, when applicable, both the social comparison method and the subjective evaluation method. In addition, many investigators failed to formally assess maintenance and generalization. Five studies failed to report any reliability data and only three investigators used Kappa to adjust IO agreement indices for the probability of chance agreements. Thus, we recommend that investigators meet contemporary standards by reporting data for maintenance, generalization, social validity, and IO agreement. See Cohen (1960) and Kazdin (1982) for guidance on these matters.

A few studies emphasized collaborative research efforts between author-investigators and teacher-practitioners. King-Sears (1999) was notable because of extensive “co-design” (p. 134) efforts between the teacher and researcher. A few other authors presented information about accommodating teacher preferences or responding to the immediate needs or daily classroom routines of teachers and students. These studies illustrate benefits and challenges of executing collaborative research. In some studies, the give-and-take required was justified. In other studies, methodological rigor was compromised not only by accommodating teachers’ preferences, but also by factors investigators could have anticipated. For example, about one-third of the authors reported they could not train all participants, complete intervention phases, or collect maintenance data because the school year ended. Thus, we recommend that investigators schedule their studies accordingly. 
Methodological and procedural weaknesses, as well as authors’ failures to report such weaknesses, raise concerns. We found that for each author-reported weakness (see superscript plus signs in Table 2), authors failed to report five other weaknesses (see superscript minus signs in Table 2). Thus, we recommend that researchers be vigilant and identify explicitly, in a limitations section, the methodological and procedural weaknesses of their studies. In addition, only one-third of the studies included systematic measures on intervention integrity. Investigators should provide this data because judgments about intervention efficacy are severely limited without clear evidence of intervention integrity.

Most small-N studies adhered to conventions for reporting data. However, graphs in a few studies included basic errors (i.e., data points connected across phase lines and across non-consecutive sessions; graph captions misplaced; graphs without phase lines; no graphs). A few studies omitted indices of central tendency and many studies omitted measures of dispersion for baseline and intervention phases. Some authors did not identify their observational recording systems. Investigators and reviewers should attend carefully to such ‘devil-in-the-detail’ matters.

Favorable Trends
Most investigators avoided three less-than-desirable trends from earlier Category III BSM studies. First, rather than targeting one dysfunctional behavior for reduction, investigators also aimed concurrently to increase at least one functional behavior. Second, rather than targeting only ‘on-task’ behavior and assuming that students accrued related benefits, investigators concurrently targeted and evaluated changes in specific academic and social behaviors. Third, most participants were trained initially in GE classrooms. We believe that students will be more successful in GE settings when teachers train students in those settings. This direct approach eliminates many challenges inherent in attempting to generalize behavior from special education or separate training settings to GE classrooms where students are expected to self-manage. 

Additional Recommendations for Practitioners and Researchers
We recommend that practitioners and researchers consult findings from Category I and II BSM studies, and studies of self-determination and self-regulated strategy development, where BSM components are incorporated frequently as part of multi-component interventions. See, for example, how to combine goal setting with self-instruction (Johnson, Graham, & Harris, 1997) or self-managed contracts (Martin, Mithaug, Cox, Peterson, Van Dycke, & Cash, 2003). BSM also might be used in conjunction with field-tested self-determination curricula and materials and to bolster goal attainment when using the Choice Maker Self-Determination curriculum (Martin & Huber Marshall, 1998), or corresponding instructional modules, such as Take Action: Making Goals Happen (Huber Marshall, et al, 1999). German, Martin, Huber Marshall, and Sale (2003) directed, “Research also needs to be undertaken to determine if the Take Action process can be successfully taught in an inclusive academic environment to students with and without disabilities” (p. 35). For guidance on effective use of BSM components with self-regulated strategy development, see Hughes, Ruhl, Schumaker and Deschler’s (2002) study on teaching students with learning disabilities, in GE classes, to improve homework via an assignment completion strategy.

Our findings also suggest that self-instruction is quite effective. This conclusion is consistent with findings from Krosenbergen and Van Luit’s (2004) meta-analysis of mathematics interventions, which deemed self-instruction effective for children with special needs. We also recommend that researchers and practitioners attempt to replicate, in inclusive settings, the positive outcomes that students in non-integrated settings achieved when they used self-correction (Morton, Heward, & Alber, 1998; Okyere, Heron, & Goddard, 1997). We also encourage BSM use in inclusive settings beyond school classrooms. See, for example, Brookman, Boettcher, Klein, Openden, Koegel, and Koegel (2003), who applied BSM as part of a larger strategy that promoted social interactions between children with and without autism in an inclusive day camp. Finally, we recommend that future Category III studies target two classes of behavior that have not yet been targeted effectively in inclusive settings – anger management-violence and health-exercise habits.

Findings from this review reinforce – with qualifications - other authors’ contentions that BSM is a best practice that helps to bridge the research-to-practice gap. Frey and George-Nichols (2003) identified BSM as 1 of 10 best practices interventions and Hughes et al. (1997) validated BSM as one of eight, practitioner-validated, transition support strategies. Gable and Hendrickson (2000) identified BSM as one of seven strategies “that hold promise for improving intervention results for students with a wide range of behavior problems” (p. 288).  The authors cautioned that six conditions might limit the utility of BSM in promoting maintenance of behavioral changes and explained how to address these conditions.

Teacher-directed instruction is essential. Effective teachers must provide instruction in the step-by-step process, model each of the steps for the student, and train across multiple stimuli. Such teachers create realistic role-play experiences, give the student feedback on both the quantitative and qualitative aspects of his or her performance, and engineer the social environment so that the student has multiple problem-solving opportunities, for which there is timely and sufficient reinforcement. (p. 289)

We conclude that BSM is a best practice in inclusive settings when students are trained systematically, GE teachers are supported, and procedural integrity is high. Support is critical because teachers throughout the US reported that they lack skills or training to teach BSM (Wehmeyer, Agran, & Hughes, 2000). Moreover, Agran and Alper (2000) indicated that only 28% of GE teachers surveyed reported that they taught BSM to students. Thus, we recommend that teacher preparation programs and professional development include BSM training for GE and special education teachers.

Limitations of Our Review
Findings from this review of Category III BSM interventions are limited in at least two ways. First, we restricted the pool of qualifying studies to articles published in professional journals. Second, we did not calculate meta-analytic indices that would illuminate relations between BSM efficacy and procedural, demographic, and outcome variables. Authors of 41 of 43 studies did not report effect sizes (ES) and most studies had insufficient data to calculate ES. Therefore, we recommend that investigators report ES or supply sufficient data to calculate such indices. The literature documents advantages and limitations of meta-analysis for small-N research (Kromrey & Foster-Johnson, 1996; Scruggs & Mastropieri, 1998; White, Rusch, Kazdin, & Hartmann, 1989). Moreover, “it is almost always necessary to include some index of effect size or strength of relationship in your Results section” (American Psychological Association, 2001, p. 25).

BSM Resources for Practitioners
Fortunately, many BSM resources are available for practitioners. Individuals can learn how to teach BSM techniques by reading “how to” articles (Alberto & Sharpton, 1987; Daly & Ranalli, 2003; Dunlap, Dunlap, Koegel, & Koegel, 1991; Frith & Armstrong, 1986; Hughes, Ruhl, & Peterson, 1988; Johnson & Johnson, 1999; Lazarus, 1998; Liberty & Paeth, 1990; McConnell, 1999; Schloss, 1987; Swaggart, 1998; Young, West, Li, & Peterson 1997). Dowrick (1991) and Gunter, Miller, Venn, Thomas, and House (2002) describe two BSM techniques – VSM and computer-assisted self-graphing – that have the potential to improve student performance in inclusive GE settings. Additional BSM training materials are available in: books (Agran, 1997; King-Sears, Wehmeyer, & Copeland, 2003); booklets (King-Sears, & Carpenter, 1997); practical guides (Dowrick, 1991); manuals (Koegel, Koegel, & Parks, 1992; Young, West, Smith, & Morgan, 1995); and instructional videos (Dowrick, 1997; McDougall, 2003).

 
References

Note:  (italic numbers indicate studies that qualified for this review)

Agran, M. (1997). Student directed learning. Pacific Groves, CA: Brooks/Cole.

Agran, M., & Alper, S. (2000). Curriculum and instruction in general education: Implications for service delivery and teacher preparation. Journal of the Association for Persons with Severe Handicaps, 25, 167-174.

1 Agran, M., Blanchard, C., Wehmeyer, M., & Hughes, C. (2001). Teaching students to regulate their behavior: The differential effects of student- vs. teacher-delivered reinforcement. Research in Developmental Disabilities, 22, 319-332.

2 Agran, M., Blanchard, C., Wehmeyer, M., & Hughes, C. (2002). Increasing the problem-solving skills of students with developmental disabilities participating in general education. Remedial and Special Education, 23(5), 279-288.

Alberto, P.A., & Sharpton, W. (1987). Prompting strategies that promote student self-management. Teaching Exceptional Children, 19(4), 54-57.

3 Alberto, P.A., Taber, T.A., & Fredrick, L.D. (1999). Use of self-operated auditory prompts to decrease aberrant behaviors in students with moderate mental retardation. Research in Developmental Disabilities, 20(6), 429-439.

Algozinne, B., Browder, D., Karvonen, M., Test, D.W., & Wood, W.M. (2001). Effects of interventions to promote self-determination for individuals with disabilities. Review of Educational Research, 71(2), 219-277.

American Psychological Association. (2001). Publication Manual of the American Psychological Association. Washington, DC: Author.

4 Apple, A.L., Billingsley, F., & Schwartz, I.S. (2005). Effects of video modeling alone and with self-management on complement-giving behaviors of children with high-functioning ASD. Journal of Positive Behavior Interventions, 7(2), 33-46.

Barry, L.M., & Haraway, D.L. (2005). Self-management and ADHD: A literature review. The Behavior Analyst Today, 6, 48-64.

Blum, N.J., Kell, R.S., Starr, H.L., Lloyds-Lender, W., Bradley-Klug, K.W., & Osbourne, M.L., et al. (1998). Audio feedforward treatment of selective mutism. Journal of the American Academy of Child and Adolescent Psychiatry, 37, 40-43.

Brookman, L., Boettcher, M., Klein, A., Openden, D., Koegel, R.L., Koegel, L.K. (2003). Facilitating social interactions in a community summer camp setting for children with autism. Journal of Positive Behavior Interventions, 5(4), 249-252.

5 Brooks, A., Todd, A.W., Tofflemoyer, S., & Horner, R.H. (2003). Use of functional assessment and a self-management system to increase academic engagement and work completion. Journal of Positive Behavior Interventions, 5(3), 144-152.

6 Bryan, T., & Sullivan-Burstein, K. (1998). Teacher-selected strategies for improving homework completion. Remedial and Special Education, 19(5), 263-275.

7,8,9 Buggey, T. (1999). Video self-modeling applications with students with autism spectrum disorders in a small private school setting. Focus on Autism and Other Developmental Disabilities, 20(1), 52-63.

Christie, D.J., Hiss, M., & Lozanoff, B. (1984). Modification of inattentive classroom behavior: Hyperactive children’s use of self-recording with teacher guidance, Behavior Modification, 8, 391-406.

Clare, S.K., Jenson, W.R., Kehle, T.J., & Bray, M.A. (2000). Self-modeling as a treatment for increasing on-task behavior. Psychology in the Schools, 37(6), 517-522.

Clees, T.J. (1994-5). Self-recording of students’ daily schedules of teachers’ expectancies: Perspectives on reactivity, stimulus control, and generalization. Exceptionalities, 5, 113-119.

Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.

10 Copeland, S.R., Hughes, C., Agran, M. Wehmeyer, M.L., & Fowler, S.E. (2002). An intervention package to  support high school students with mental retardation in general education classrooms. American Journal on Mental Retardation, 107(1), 32-45.

11 Craft, M.A., Alber, S.R., & Heward, W.L. (1998). Teaching elementary students with developmental disabilities to recruit teacher attention in a general education classroom: Effects on teacher praise and academic productivity. Journal of Applied Behavior Analysis, 31, 399-415.

Creer, T.L., & Miklich, D.R. (1970). The application of a self-modeling procedure to modify inappropriate behavior: A preliminary report. Behaviour Research and Therapy, 8, 91-92.

12 Crum, C.F. (2004). Using a cognitive-behavior modification strategy to increase on-task behavior of a student with a behavior disorder. Intervention in School and Clinic, 39(5), 305-309.

13 Dalton, T., Martella, R.C., & Marchand-Martella, N.E. (1999). The effects of a self-management program in reducing off-task behavior. Journal of Behavioral Education, 9(3/4), 157-176.

Daly, P.M., & Ranailli, P. (2003). Using countoons to teach self-monitoring skills. Teaching Exceptional Children, 35(5), 30-35.

14 Davies, S., & Witte, R. (2000). Self-management and peer-monitoring within a group contingency to decrease uncontrolled verbalizations of children with attention-deficit/hyperactivity disorder. Psychology in the Schools, 37(2), 135-147.

Deci, E.L., & Ryan, R.M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.

DiGangi, S.A., Maag, J.W., & Rutherford, R.B. (1991). Self-graphing of on-task behavior: Enhancing the reactive effects of self-monitoring of on-task behavior and academic performance. Learning Disability Quarterly, 14, 221-230.

Dowrick, P.W. (1991). Practical guide to using video in the behavioral sciences. New York: Wiley Interscience.

Dowrick, P.W. (1997). A sampler of self-modeling, feedforward, and other video features [video]. Auckland CCS and Children’s Seashore House (Philadelphia).

Dowrick, P.W. (1999). A review of self-modeling and related interventions. Applied and Preventative Psychology, 8, 23-39.

Dowrick, P.W., & Hood, M. (1978). Transfer of talking behaviours across settings using faked films. In E.L. Glynn & S.S. McNaughton (Eds.), Proceedings of the New Zealand Conference for Research in Applied Behaviour Analysis. Auckland, New Zealand: University of Auckland Press.

Dowrick, P.W., Power, T.J., Manz, P.H., Ginsberg-Block, M. Leff, S.S., & Kim-Rupnow, W.S. (2001). Community responsiveness: Examples from under-resourced urban schools. Journal of Prevention and Intervention in the Community, 21(2), 71-90.

Dowrick, P.W., & Raeburn, J.M. (1977). Video editing and medication to produce a therapeutic self-model. Journal of Consulting and Clinical Psychology, 45, 1156-1158.

Dunlap, L.K., Dunlap, G., Koegel, L.K., & Koegel, Robert, L. (1991). Using self-monitoring to increase independence. Teaching Exceptional Children, 23(3), 17-22.

15 DuPaul, G.J., McGoey, K.E., & Yugar, J.M. (1997). Mainstreaming students with behavioral disorders: The use of classroom peers as facilitators of generalization. School Psychology Review, 26(4), 634-650.

Edwards, L., Salent, V., Howard, V.F., Brougher, J., &McLaughlin, T.F. (1995). Effectiveness of self-management of attentional behavior and reading comprehension for children with attention deficit disorder. Child and Family Behavior Therapy, 17(2), 1-17

Falk, G.D., Dunlap, G., & Kern, L. (1996). An analysis of self-evaluation and videotape feedback for improving the peer interactions of students with externalizing and internalizing behavioral problems. Behavioral Disorders, 21, 261-276.

Frey, A., & George-Nichols, N. (2003). Intervention practices for students with emotional and behavioral disorders: Using research to inform school social work practice. Intervention Research, 25(2), 97-104.

Frith, G.H., & Armstrong, S.W. (1986). Self-monitoring for behaviorally disordered students. Teaching Exceptional Children, 18, 144-148.

Gable, R.A., & Hendrickson, J.M. (2000). Strategies for maintaining positive behavior change stemming from functional behavioral assessment in schools. Education and Treatment of Children in Schools, 23(3), 286-297.

16 Gansle, K.A., & McMahon, C.M. (1997). Component integrity of teacher intervention management behavior using a student self-monitoring treatment: An experimental analysis. Journal of Behavioral Education, 7(4), 405-419.

Gardner, W.I., Clees, T.J., & Coles, C.L. (1983). Self-management of disruptive verbal Ruminations by a mentally retarded adult. Applied Research in Mental Retardation, 4, 41-58.

German, S.L., Martin, J.E., Huber Marshall, L., & Sale, R.P. (2003). Promoting self-determination: Using Take Action to teach goal attainment. Career Development for Exceptional Individuals, 23(1), 27-38.

17 Gertz, J. (2000). Evaluating behavioral treatment of disruptive classroom behaviors of an adolescent with autism. Research on Social Work Practice, 10(1), 98-110.

Giangreco, M.F., Edelman, S.W., Luiselli, T.E., MacFarland, S.Z.C. (1997). Helping or hovering? Effects of instructional assistant proximity on students with disabilities. Exceptional Children, 64(1), 7-18.

18 Gilberts, G.H., Agran, M., Hughes, C., & Wehmeyer, M. (2001). The effects of peer delivered self-monitoring strategies on participation of students with severe disabilities in general education classrooms. Journal of the Association for Persons with Severe Handicaps, 26(1), 25-36.

Glynn, E.L., Thomas, J.D., & Shee, S.M. (1973). Behavioral self-control of on-task behavior in an elementary classroom. Journal of Applied Behavior Analysis, 6, 105-113.

Graham, S., Harris, K.R., & Troia, G.A. (2000). Self-regulated strategy development revisited: Teaching writing strategies to struggling writers. Topics in Language Disorders, 20(4), 1-14.

19 Gregory, K.M., Kehle, T.J., & McLoughlin, C.S. (1997). Generalization and maintenance of treatment gains using self-management procedures with behaviorally disordered  adolescents. Psychological Reports, 80, 683-690.

Grossi, T.A., & Heward, W.L. (1998). Using self-evaluation to improve the work productivity of trainees in a community-based restaurant training program. Education and Training in Mental Retardation and Developmental Disabilities, 33(3), 248-263.

20 Gumpel, T.P., & David, S. (2000). Exploring the efficacy of self-regulatory training as a possible alternative to social skills training. Behavioral Disorders, 25(2), 131-141.

Gunter, P.L., Miller, K.A., Venn, M.L., Thomas, K., & House, S. (2002). Self-graphing to success: Computerized data management. Teaching Exceptional Children, 35(2), 30-34.

Hallahan, D.P., Marshall, K.D., & Lloyd, J.W. (1981). Self-recording during group instruction: Effects on attention to task. Learning Disabilities Quarterly, 4, 407-413.

Hitchcock, C.H., Dowrick, P.A., & Prater, M.A. (2003). Video self-modeling in school-based settings: A review. Remedial and Special Education, 24(1), 36-45, 56.

21 Hoff, K.E., & DuPaul, G.J. (1998). Reducing disruptive behavior in general education classrooms: The use of self-management strategies. School Psychology Review, 27(2), 290-303.

Hogan, S., & Prater, M.A. (1993). The effects of peer tutoring and self-management training on-task, academic, and disruptive behaviors. Behavioral Disorders, 18, 118-128.

Hosford, R.E. (1980). Self-as-a-model: A cognitive, social-learning technique. Counseling Psychology, 9(1), 45-62.

Huber Marshall, L., Martin, J.E., Maxson, L.L., Hughes, W., Miller, T.L., McGill, T., & Jerman, P. (1999). Take action: Making goals happen. Longmont, CO: Sopris West.

22 Hughes, C., Copeland S.R., Agran, M., Wehmeyer, M.L., Rodi, M.S., & Pressley, J.A. (2002). Using self-monitoring to improve performance in general  education high school classes. Education and Training in Mental Retardation and Developmental Disabilities, 37(3), 262-272.

23,24 Hughes, C.A., Fowler, S.E., Copeland, S.R., Agran, M., Wehmeyer, M.L., & Church-Pupke, P.P. (2004). Supporting high school students to engage in recreational activities with peers. Behavior Modification, 28(1), 3-27.

Hughes, C.A., Kim, J.H., Bogseon, H., Killian, D.J., Fischer, G.M., & Brock, M.G., et al. (1997). Practitioner-validated secondary transition support strategies. Education and Training in Mental Retardation and Developmental Disabilities, 32(3), 201-212.

Hughes, C.A., Ruhl, K.L., & Misra, A. (1989). Self-management with behaviorally disordered students in school settings: A promise unfulfilled? Behavioral Disorders, 14, 250-262.

Hughes, C.A., Ruhl, K.L., & Peterson, S.K. (1988). Teaching self-management skills: Promising practices. Teaching Exceptional Children, 20(2), 70-72.

Hughes, C.A., Ruhl, K.L., Schumaker, J.B., Deschler, D.D. (2002). Effects of instruction in an assignment completion strategy on the homework performance of students with learning disabilities in general education classes. Learning Disabilities: Research & Practice, 17(1), 1-18.

25 Hughes, C., Rung, L.L., Wehmeyer, M.L., Agran, M., Copeland, S.R., & Hwang, B. (2000). Self-prompted communication book use to increase social interaction among high school students. Journal of the Association for Persons with Severe Handicaps, 25(3), 153-166.

26 Hutchinson, S.W., Murdock, J.Y., Williamson, R.D., & Cronin, M.E. (2000). Self-recording PLUS encouragement equals improved behavior. Teaching Exceptional Children, 32(5), 54-58

27 Jindal-Snape, D. (2004). Generalization and maintenance of social skills of children with visual impairments: Self-evaluation and the role of feedback. Journal of Visual Impairment and Blindness, 98, 470-483.

Johnson, L.A., Graham, S., & Harris, K.R. (1997). The effects of goal setting and self-instruction on learning a reading comprehension strategy: A study of students with learning disabilities. Journal of Learning Disabilities, 30(1), 80-91.

Johnson, L.R., & Johnson, C.E. (1999). Teaching students to regulate their own behavior. Teaching Exceptional Children, 31(4), 6-10.

Kanfer, F.H., & Karoly, P. (1972a). A behavioristic excursion into the lion’s den. Behavioral Therapy, 3, 398-416.

Kanfer, F.H., & Karoly, P. (1972b). Self-regulation and its clinical application: Some additional considerations. In R.C. Johnson, P.R. Dokecki, & O.H. Mowrer (Eds.), Conscience, contract and social reality (pp. 428-437). New York: Holt, Rinehart & Winston.

Kazdin, A.E. (1982). Single-case research designs: Methods for clinical and applied settings. New York: Oxford University Press.

28 King-Sears, M.E. (1999). Teacher and researcher co-design self-management content for an inclusive setting: Research training, intervention, and generalization effects on student performance. Education and Training in Mental Retardation and Developmental Disabilities, 34(2), 134-156.

King-Sears, M.E., & Carpenter, S. (1997). Teaching self-management to elementary students with developmental disabilities. Innovations: American Association on Mental Retardation, Research to Practice Series, n11, 59 pp. American Association on Mental Retardation, 444 North Capitol Street, NW, Suite 846, Washington, DC 20001-1512.

King-Sears, M.E., Wehmeyer, M.L., & Copeland, S.R. (2003). Teacher’s series on inclusive practices: Student-directed learning. Baltimore, MD: Paul H. Brookes.
29Koegel, L.K., Harrower, J.K., & Koegel, R.L. (1999). Support for children with developmental disabilities in full-inclusion classrooms through self-management. Journal of Positive Behavioral Interventions, 1(1), 26-34.

Koegel, L.K., Koegel, R.L., & Parks, D.R. (1992). How to teach self-management skills to people  with severe disabilities: A training manual. Santa Barbara: University of California.

Krosenbergen, E.H., & Van Luit, E.H. (2004). Mathematics interventions for children with special education needs: A meta-analysis. Remedial and Special Education, 24(3), 97-114.

Kromrey, J.D., & Foster-Johnson, L. (1996). Determining the efficacy of intervention: The use of effect sizes for data analysis in single-subject research. Journal of Experimental Education, 65(1), 73-93.

Lancioni, G.E., & O’Reilly, M.F. (2001). Self-management of instruction cues for occupation: Review of studies with people with severe and profound developmental disabilities. Research in Developmental Disabilities, 22, 41-65.

Lazarus, B.D. (1998). Say cheese! Using personal photographs as prompts. Teaching Exceptional Children, 30(6), 4-7.

Liberty, K.A., & Paeth, M.A. (1990). Self-recording for students with severe and multiple handicaps. Teaching Exceptional Children, 22(3), 73-75.

Lonnecker, C., Brady, M.P., McPherson, R. & Hawkins, J. (1994). Video self modeling and cooperative classroom behavior in children with learning and behavior problems: Training and generalization effects. Behavioral Disorders, 20(1), 24-34.

Martin, J.E., & Huber Marshall, L. (1998). Choice maker: Choosing, planning, and taking action. In Sands, D.E. & Wehmeyer, M.L. (Eds.), Making it happen (pp. 211-240). Baltimore, MD: Paul Brooks.

Martin, J.E., & Mithaug, D. (1986). Advancing a technology of self-control. British Columbia Journal of Special Education, 10(2), 93-100.

Martin, J.E., Mithaug, D.E., Cox, P., Peterson, L.Y., Van Dycke, L.Y., & Cash, M.E. (2003). Increasing self-determination: Teaching students to plan, work, evaluate, and adjust. Exceptional Children, 69(4), 431-447.

30 Massey, N.G., & Wheeler, J.J. (2000). Acquisition and generalization of activity schedules and their effects on task engagement in a young child with autism in an inclusive pre-school classroom. Education and Training in Mental Retardation and Developmental Disabilities, 35(3), 326-335.

McConnell, M.E. (1999). Self-monitoring, cueing, recording, and managing: Teaching students to manage their own behavior. Teaching Exceptional Children, 32(2), 14-21.

McDougall, D. (1998). Research on self-management techniques used by students with disabilities in general education settings: A descriptive review. Remedial and Special Education, 19(5), 310-320.

McDougall, D. (2003). Teaching elementary students how to manage their own behavior: A training video [Videocassette]. Available via mcdougal@hawaii.edu. DMcD-BSM, 124, Wist Hall, University of Hawai’i, Honolulu, HI 99822

McDougall, D. (2005). The range-bound changing criterion design. Behavioral Interventions, 20, 1-9.

McDougall, D. (in press). The distributed criterion design. Journal of Behavioral Education.

31 McDougall, D., & Brady, M.P. (1998). Initiating and fading self-management interventions to increase math fluency in general education classes. Exceptional Children, 64(2), 151-166.

McLaughlin, T.F. (1976). Self-control in the classroom. Review of Educational Research, 46, 631-663.

Meichenbaum, D. (1977). Cognitive behavior modification. New York: Plenum Press.

Mehrag, S.S., & Woltersdorf, M.A. (1990). Therapeutic use of videotape self-modeling: A review. Advances in Behaviour Research and Therapy, 12, 85-99.

Mertens, D.M. (1998). Research methods in education and psychology: Integrating diversity with quantitative and qualitative approaches. Thousand Oaks, CA: Sage.

32 Mitchem, K.J., Young, K.R., West, R.P., & Benyo, J. (2001). CWPASM: A classwide peer-assisted self-management program for general education classroom. Education and Treatment of Children, 24(2), 111-140.

33 Monda-Amaya, L.E., Dieker, L., & Reed, F. (1998). Preparing students with learning disabilities to participate in inclusive classrooms. Learning Disabilities Research and Practice, 13(3), 171-182.

Mooney, P., Ryan, J.B., Uhing, B.M., Reid, R., & Epstein, M.H. (2005). A review of self-management interventions targeting academic outcomes for students with emotional and behavioral disorders. Journal of Behavioral Education, 14(3), 203-221.

Morton, W.L., Heward, W.L, & Alber, S.R., (1998). When to self-correct?: A comparison of two procedures on spelling performance. Journal of Behavioral Education, 8(3), 321-335.

Nelson, J.R., Smith, D.J., Young, R.K., & Dodd, J.M. (1991). A review of self-management outcome research conducted with students who exhibit behavior disorders. Behavioral Disorders, 16(3), 169-179.

Okyere, B.A., Heron, T.E., & Goddard, Y. (1997). Effects of self-correction on the acquisition, maintenance, and generalization of written spelling of elementary school children. Journal of Behavioral Education, 7(1), 51-69.

O'Leary, S.G., & Duby, D.R. (1979). Applications of self-control procedures by children: A review. Journal of Applied Behavior Analysis, 12(3), 449-465.

34 O’Reilly, M.O., Tiernan, R., Lancioni, G., Lacey, C., Hillery, J., & Gardiner, M. (2002). Use of self-monitoring and delayed feedback to increase on-task behavior in a post-institutionalized child within regular classroom settings. Education and Treatment of Children, 25(1), 91-102.

Osborne, S.S., Kiburz, C.S., & Miller, S.R. (1986). Treatment of self-injurious behavior using Self-control techniques with a severely behaviorally disordered adolescent. Behavioral  Disorders, 12, 60-67.

Palmer, S.B., & Wehmeyer, M.L., (2003). Promoting self-determination in early elementary school: Teaching self-regulated problem-solving and goal-setting skills. Remedial and Special Education, 24(2), 115-126.

Pierce, C.D., Reid, R., & Epstein, M.H. (2004). Teacher-mediated interventions for children with EBD and their academic outcomes: A Review. Remedial and Special Education, 25(3), 175-188.

35 Possell, L.E., Kehle, T.J., McLoughlin, C.S., & Bray, M.A. (1999). Self-modeling as an intervention to reduce disruptive classroom behavior. Cognitive and Behavioral Practice, 6, 99-105

Post, M., & Storey, K. (2002). Review of auditory prompting systems in persons who have moderate to severe disabilities. Education and Training in Mental Retardation and Developmental Disabilities, 33(2), 131-143.

Prater, M.A., Hogan, S., & Miller, S.R. (1992). Using self-monitoring to improve on-task behavior and academic skills of an adolescent with mild handicaps across special and regular education settings. Education and Treatment of Children, 15, 43-55.

Prater, M.A., Joy, R., Chilman, B. Temple, J., & Miller, S.R. (1991). Self-monitoring of on-task behavior by adolescents with learning disabilities. Learning Disabilities Quarterly, 14, 164-177.

Rachlin, H. (1974). Self-control. Behaviourism, 2, 94-107.

Rhode, G., Morgan, D.P., & Young, K.R. (1983). Generalazation and maintenance of treatment Gains from resource rooms to regular classrooms using self-evaluation procedures. Journal of Applied Behavior Analysis, 16, 171-188.

Rock, M.L. (2005). Use of strategic self-monitoring to enhance academic engagement, productivity, and accuracy of students with and without exceptionalities. Journal of Positive Behavior Interventions, 7(1), 3-17. 

Rooney, K.J., Hallahan, D.P., & Lloyd, J.W. (1984). Self-recording of attention by learning disabled students in the regular classroom. Journal of Learning Disabilities, 17, 360-364.

Rosenbaum, M.S., & Drabman, R.S. (1979). Self-control training in the classroom: A review and critique. Journal of Applied Behavior Analysis, 12, 467-485.

Schloss, P. (1987). Self-management strategies for adolescents entering the work force. Teaching Exceptional Children, 19(9), 39-43.

Scruggs, T.E., & Mastropieri, M.A. (1998). Summarizing single-subject research: Issues and applications. Behavior Modification, 22(3), 221-242.

Skiba, R., & Casey, A. (1985). Interventions for behaviorally disordered students: A quantitative review and methodological critique. Behavioral Disorders, 10, 239-252.

Skinner, B.F. (1953). Science and human behavior. New York: Macmillan.

39 Snyder, M.C., & Bambara, L.M. (1997). Teaching secondary students with learning disabilities to self-manage classroom survival skills. Journal of Learning Disabilities, 30(5), 534-543.

Stage, S.A., & Quiroz, D.R. (1997). A meta-analysis of interventions to decrease disruptive classroom behavior in public education settings. School Psychology Review, 26, 333-368.

Swaggart, B.L. (1998). Implementing a cognitive behavior management plan. Intervention in School and Clinic, 33(4), 235-238.

40 Thiemann, K.S., & Goldstein, H. (2001). Social stories, written text cues, and video feedback: Effects on social communications of children with autism. Journal of Applied Behavior Analysis, 34, 425-446.

Thoreson, C.E., & Mahoney, M.J. (1974). Behavioral self-control. New York: Holt.

41 Todd, A.W., Horner, R.H., & Sugai, G. (1999). Self-monitoring and self-recruited praise: Effects on problem behavior, academic engagement, and work completion in a typical classroom. Journal of Positive Behavior Interventions, 1(2), 66-76, 122.

Trammel, D.L., Schloss, P.T., & Alper, S. (1994). Using self-recording, evaluation, and graphing to increase completion of homework assignments. Journal of Learning Disabilities, 27, 75-81.

42 Uberti, H.Z., Mastroppieri, M., & Scruggs, T.E. (2004). Check it off: Individualizing a math algorithm for students with disabilities via self-monitoring checklists. Intervention in School and Clinic, 39(5), 269-275.

Wehmeyer, M.L., Agran, M., & Hughes, C. (2000). A national survey of teachers’ promotion of self-determination and student-directed learning. Journal of Special Education, 34, 58-68.

43 Wehmeyer, M.L., Yeager, D., Bolding, N., Agran, M., & Hughes, C. (2003). The effects of self-regulation strategies on goal attainment for students with developmental disabilities in general education classrooms. Journal of Developmental and Physical Disabilities, 15(1), 79-91.

Wert, B.Y., & Neisworth, John T. (2003). Effects of video self-modeling on spontaneous requesting in children with autism. Journal of Positive Behavior Interventions, 5(1), 30-34.

White, O.R., Rusch, F.R., Kazdin, A.E., & Hartman, D.P. (1989). Applications of meta analysis in individual-subject research. Behavioral Assessment, 11, 281-296.

Wolery, M., & Schuster, J.W. (1997). Instructional methods with students who have significant disabilities. Journal of Special Education, 31(4), 61-79.

Workman, E.A., & Hector, M.A. (1976). Behavioral self-control in classroom settings: A review of the literature. Journal of School Psychology, 16, 227-236.

Young, K.R., West, R.P., Li, L., & Peterson, L. (1997). Teaching self-management skills to students with learning and behavior problems. Reclaiming Children and Youth, 6(2), 90-96.

Young, K.R., West, R.P., Smith, D.J., & Morgan, D.P. (1995). Teaching self-management strategies to adolescents. Longmont, CO: Sopris West.

 

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 TABLES 1,2 & 3

Table 1 (Click on Image to Enlarge)

Table 2 (Click Image to Enlarge)

Table 3 (Click on Image to Enlarge)

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