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Article Excerpt
Abstract. Given the importance of both academic and self-determination skills for students with disabilities, it is important to identify efficient ways to deliver instruction in these essential areas. This literature review synthesizes intervention research that has examined the effects of self-determination interventions on academic skills for students with learning disabilities (LD) and/or attention deficit/hyperactivity disorder (ADHD). Our findings revealed that self-management interventions were most often studied, followed by interventions that combined self-management with one or more other self-determination components. Effects ranged from very weak to very strong. Effects were strongest when (a) interventions that combined self-management with goal setting were used to increase students' productivity, and (b) goal-setting interventions were used to improve math skills. Most of the studies included in the review were of high quality; however, some areas could be improved.
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Despite improving trends in post-school outcomes for individuals with disabilities (Newman, 2005; Wagner, 2005), outcomes still remain at unacceptable levels for youth in all disability categories (Baer et al., 2003; Wagner). Although students with learning disabilities (LD) are considered to have "mild" disabilities, post-school outcomes for this population are also poor. For example, only 82.6% of youth with LD in their first two years out of school are engaged in postsecondary education, employment, or job training (Wagner). Although this percentage appears high and does represent an increase in recent years, it raises concern: Nearly 20% of youth with LD are not engaged in work or education shortly after leaving high school. In addition, youth with LD and other health impairments are among the most likely to be involved with the criminal justice system (Wagner, Newman, Cameto, Garza, & Levine, 2005).
Efforts to improve these outcomes have focused on identifying features of school programs that appear to contribute to positive post-school outcomes (Benz, Yovanoff, & Doren, 1997) as well as characteristics and skills of individuals with disabilities who have found post-school success (Benz et al.; Halpern, Yovanoff, Doren, & Benz, 1995; Raskind, Goldberg, Higgins, & Herman, 1999). One such predictor of positive outcomes appears to be levels of self-determination demonstrated. For example, positive correlations have been found between level of self-determination and rates of employment (Wehmeyer & Schwartz, 1997), access to benefits (e.g., vacation and sick leave; Wehymeyer & Palmer, 2003), and quality of life (Wehmeyer & Schwartz, 1998).
Further, Raskind et al. (1999) conducted a longitudinal study to determine predictors of success among individuals with LD. Forty-one adults with LD participated in interviews and cognitive and academic testing 20 years after they had left a treatment center for children with LD. Results indicated that the following attributes distinguished successful from unsuccessful adults: self-awareness, proactivity, perseverance, emotional stability, goal setting, and use of support systems. These attributes are reflected in the following description of self-determination:
Self-determination is a combination of skills, knowledge, and beliefs that enable a person to engage in a goal-directed, self-regulated, autonomous behavior. An understanding of one's strengths and limitations together with a belief in oneself as capable and effective are essential ... When acting on the basis of these skills and attitudes, individuals have greater ability to take control of their lives and assume the role of successful adults. (Field, Martin, Miller, Ward, & Wehmeyer, 1998, p. 2)
Although this definition is comprehensive and has been accepted in the field, it is still important to define self-determination in terms of its subskills or components. Wehmeyer, Sands, Doll, and Palmer (1997) identified 11 components of self-determination: choice making, decision making, problem solving, goal setting and attainment, self-observation, self-evaluation, self-reinforcement, self-instruction, self-advocacy and leadership, internal locus of control, positive attributions of efficacy and outcome expectancy, self-awareness, and self-knowledge.
These components, or some combination of them, have been studied in previous literature reviews. For example, Algozzine, Browder, Karvonen, Test, and Wood (2001) reviewed 51 self-determination intervention studies published from 1972-2000 to identify what interventions had been studied along with outcomes. Findings indicated that a range interventions are effective for teaching individuals with disabilities a variety of self-determination skills, including group instruction, individual conferences, systematic prompting and feedback, and commercially available and researcher-developed curricula.
Reviews have also looked more closely at specific components of self-determination, including choice making (Shogren, Faggella-Luby, Bae, & Wehmeyer, 2004), self-advocacy (Test, Fowler, Brewer, & Wood, 2005), and self-management (McDougall, 1998; Reid, 1996; Reid, Trout, & Schartz, 2005; Webber, Scheuermann, McCall, & Coleman, 1993). For example, Shogren et al. reviewed 13 choice-making intervention studies to determine their effects on "problem behavior" for individuals with a range of disabilities. Findings indicated that choice-making interventions are effective ways to reduce both aggressive and non-aggressive problem behavior.
Most of the studies included in these literature reviews examined behaviors related to classroom success such as on-task behavior (e.g., Reid, 1996; Webber et al., 1993), aggressive behavior (e.g., Shogren et al., 2004), assertive communication skills (e.g., Test et al., 2005), or specific self-determination behaviors such as participation in IEP meetings (e.g., Test et al.). Although some of the reviews included studies that measured academic skills, none looked exclusively at the effects of self-determination interventions on academic outcomes.
Emphasis on academic skills is increasing, in light of legal mandates for access to the general curriculum (IDEA, 2004) and participation by all students in state and district assessments (NCLB, 2001). Although this standards-based reform movement holds promise for students with disabilities, who have traditionally been excluded from the general curriculum and from state and district testing (Thurlow, 2002), the potential over-emphasis on academic skills is a concern to special educators who are also responsible for teaching self-determination skills. For example, in a survey of special education teachers conducted by Wehmeyer, Agran, and Hughes (2000), teachers identified time constraints as a primary reason for not teaching self-determination skills to their students. This is not surprising given the broad range of roles and responsibilities of special education teachers (Conderman & Katsiyannis, 2002).
Thus, there is a need to demonstrate that teaching students self-determination skills does not have to be done at the expense of academic skills instruction. Indeed, a critical question is: Can instruction in self-determination skills positively affect academic skills? The purpose of this review was to identify, describe, and synthesize intervention studies that have examined the effects of self-determination interventions on academic skills for students with LD and/or attention deficit/hyperactivity disorder (ADHD).
METHOD
Studies were identified for this review through a four-step process. First, the authors conducted a computer search of the ERIC database using terms such as self-determination, self-monitoring, choice making, problem solving, goal setting, self-regulation, self-advocacy, self-awareness, reading, mathematics, written expression, general curriculum, and disabilities. (A complete list of search terms may be obtained from the first author.) Second, the authors completed a hand search of 10 major special education journals (e.g., Exceptional Children, Learning Disability Quarterly, Learning Disabilities Research and Practice; a complete list may be obtained from the first author) from the years 20002005. The year 2000 was selected as a start date because a comprehensive literature review was published in 2001 (Algozzine et al., 2001). Third, an additional electronic search was conducted to add terms (e.g., assistance, help, recruit) after noting the term self-recruitment in association with self-advocacy during the hand search. Finally, we examined reference lists from four relevant literature reviews (Alber & Heward, 2000; Copeland & Hughes, 2002; Shogren et al., 2004; Test et al., 2005) to identify additional studies that were not captured through our computer and hand searches.
We included articles published between 1972 and May 2005 in peer-reviewed journals that included at least one student participant (pre-K through postsecondary education) with an identified disability, as defined by IDEA (2004), or a diagnosis of ADHD. In addition, the intervention and data collection had to have taken place in a school setting, including college or university settings; the independent variable had to teach a self-determination skill; and at least one of the dependent variables had to measure an academic skill. We included both experimental (e.g., single-subject or group experimental) and pre-experimental (e.g., pretest-posttest) studies. Finally, because the review included an analysis of the quality of the studies. We included all studies that met the above criteria, regardless of their quality.
With regard to the independent variables, a self-determination intervention (e.g., self-monitoring) had to be the primary component or a portion of an intervention package for which a component analysis allowed for observation of the incremental effects of the self-determination intervention. For dependent variables, academic skills were not narrowed to traditional core academic subjects (e.g., reading, math, social studies) but were narrowed to tasks within any course or subject area that involved skills such as reading, writing, math, or spelling. Academic skills were noted as measures of (a) quality, defined as accuracy and/or fluency on an academic task, a holistic quality score, or a rating on a quality checklist; (b) productivity, defined as amount of task completed; or (c) standardized academic assessment performance. See Table 1 for detailed explanations of each academic dependent variable.
Procedures for Descriptive Review
Examination of each study included use of a researcher-developed coding form to gather information on participants' sex, age, disability, and ethnicity; settings; research designs; dependent variables; independent variables; and results. Inter-rater reliability for this information was calculated in two stages.
The first two authors read titles and abstracts of the 191 articles identified in the initial search and independently decided whether or not to include each article. They agreed on the inclusion of 91.6% of articles. All disagreements were discussed, and consensus was reached. We selected 58 studies for inclusion in the original review; however, due to the scope of the review, we decided to narrow the focus to participants with LD and/or ADHD. Therefore, we included 34 studies, described in 31 articles.
Next, descriptive information was recorded for 19% of the articles by two of the first three authors. Interrater agreement was calculated by dividing the total number of agreements by the total number of items reviewed and converted to a percentage. Number of items reviewed varied because the number of dependent variables in studies was not constant. Inter-rater reliability for this portion of the review ranged from 87.5% to 98.5% with a mean of 95.7%. Consensus was reached on disagreements before information was recorded for results.
Procedures for Evaluation of Study Quality
Quality indicators from Gersten et al. (2005) and Homer et al. (2005) were used to analyze the quality of each study. Two of the first three authors independently reviewed 22.4% of the studies. The methods used to calculate reliability were the same as those described previously. For single-subject study quality, reliability ranged from 72.0% to 96.0%, with a mean of 86.70%. Reliability ranged from 70.0% to 88.0%, with a mean of 80.7% for group studies.
Gersten et al. (2005) delineated 10 essential quality indicators for group and quasi-experimental research whereas Homer et al. (2005) identified 21 for single-subject research. Due to space limitations, we grouped some of the indicators into categories.
For example, if a study's dependent variable was described with "operational precision ... measured with a procedure that generates a quantifiable index ... measurement ... is valid and described with replicable precision ... (and) measured repeatedly over time" (Homer et al., p. 174), the study was reported to have a "dependent variable that is operationally defined." Similarly, if a study met indicators for social validity, including the "dependent variable is socially important ... magnitude of change in the dependent variable ... is socially important ... implementation ... is practical and cost effective" (Horner et al., p. 174), the study was reported to have a "socially valid intervention."
Calculation of Intervention Effects
Gersten et al. (2005) noted the importance of reporting the power of an intervention because it indicates the probability of an accurately analyzed statistically significant result. In single-subject research, systematically analyzing the effects of an intervention is critical to understanding its reliability for other participants (Scruggs, Mastropieri, & Casto, 1987). Several methods have been used to assess the strength of the results of single-subject studies (Campbell, 2003; Scruggs & Mastropieri, 2001; Scruggs et al.), and effect sizes are frequently used to calculate power in group experiments (Gersten et al.). This literature review reports the strength of the effects on the academic variables for both group and single-subject studies, when the data provided made such analysis possible.
Group studies. All the group design studies reported data that allowed for calculating the strength of effects of the self-determination intervention on the academic variables. We used the independent case pooled method (Hedges g) of calculation. Hedges pooled g is deemed to be a more sensitive measure of effect size (Cohen, 1988) than the independent-case separate statistic, which is not useful when the disparity between the standard deviations of both groups is large. An unweighted average of effect sizes was calculated across the six group intervention studies for which such data were calculated and, more important, reported for self-determination component and academic dependent variable across studies. Due to the small number of group studies, we determined that weighted calculations of various characteristics of studies (e.g., sample size, type of self-determination intervention) would not be informative.
The g effect size statistic is calculated as the mean of the control group performance subtracted from the mean of the experimental group's performance, divided by the average standard deviation of both groups. For this review, the control group mean and standard deviation represented the group whose intervention excluded any component of self-determination (e.g., Reid & Harris, 1993). Cohen (1988) cautiously referred to small (ES = .2), medium (ES = .5), and large (ES = .8) regarding the interpretation of the strength of effects.
Single-subject studies. Scruggs et al. (1987) asserted that the "only major evaluative criteria that can consistently be applied" (p. 27) to single-subject research is the method of calculating the percentage of non-overlapping data...
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