Abstract
Researchers, policy makers, practitioners, and other advocates in the field of special education remain firmly committed to further strengthening the rigor, relevance, and reach of educational services and supports aimed at improving academic, behavioral, and social outcomes for students with disabilities and their families. Indeed, improving outcomes and enhancing quality of life for students with disabilities have long been central to the purpose of special education (Individuals With Disabilities Education Improvement Act of 2004; Turnbull, Turnbull, Wehmeyer, & Park, 2003). To achieve this objective, a range of high-quality methodologies are needed to address socially significant research questions that hold promise for making a real difference in the educational lives of students and serve as the driving force for all inquiry (Odom et al., 2005).
Shavelson and Towne (2002) suggested most research questions can be categorized into one of the three domains: (a) descriptive inquiry, exploring the question of “What is happening?”; (b) causal inquiry, exploring the question of “Is there an effect, or does x cause y?”; and (c) process or mechanism inquiry, exploring the question of “Why or how is it happening?” These interrelated questions provide a framework for developing the knowledge base for improving educational outcomes of students with disabilities. Descriptive inquiry can include qualitative (e.g., case studies) and/or quantitative (e.g., correlational) approaches. Results from descriptive studies have the potential to provide initial impressions of or deeper insights into understudied and emerging areas of practice (e.g., the relationship between motivation and self-determined behaviors for students with disabilities; Zorigian, Lane, & Carter, 2012; or other moderating variables affecting self-determined behaviors; Wehmeyer et al., 2011). Information gleaned from descriptive studies can be used in conjunction with strong theoretical frameworks to inform causal inquiry. For example, if findings from descriptive studies suggest students with higher levels of achievement motivation engage in more self-determined behaviors (e.g., goal setting, decision making, and self-advocacy), interventions can be designed to examine the extent to which improving self-determined behaviors results in improved achievement motivation and academic performance. After sufficient evidence is generated to suggest this relationship is not spurious, process or mechanism studies can be conducted to explore how or why this causal relationship exists. For example, it may be improved that achievement motivation moderates academic performance.
Importance of Causal Inquiry in Identifying Evidence-Based Practices
Ideally, evidence resulting from causal studies is used to determine which practices are indeed evidence based for particular students, in particular contexts, and for particular outcomes. Shavelson and Towne (2002) suggested causal inquiry serves as “the intellectual foundation for understanding relationships” (p. 108). Causal questions can be answered via randomized control (also referred to as experimental group), single-case, quasiexperimental, and regression-discontinuity designs, each of which brings distinct methodological strengths and tactics.
Within the field of education, researchers, policy makers, and teachers rely on findings from causal questions to identify and advocate for evidence-based practice in special education. Accurate information as to which strategies and practices yield desired outcomes is essential as we seek to support students with and at risk for disabilities in a range of settings, including within the context of three-tiered models of prevention such as Response to Intervention (RtI; Fuchs & Fuchs, 2006), Positive Behavior Intervention and Supports (PBIS; Sugai & Horner, 2006), and Comprehensive, Integrated, Three-Tiered (CI3T) models of prevention (Lane, Oakes, & Menzies, 2010).
The educational community is charged with the task of implementing evidence-based practices for all learners—including those with disabilities such as emotional disturbances (Mooney, Epstein, Reid, & Nelson, 2003), severe intellectual disabilities (Spooner, Knight, Browder, & Smith, 2012), or autism (Tincani & Devis, 2011)—and at each level of prevention within tiered systems. For example, school-site leadership teams now have increasing access to research-based guidance on selecting and implementing with fidelity primary (Tier 1, for all students) programs such as universal social skills programs (e.g., Social Skills Improvement System: Classwide Intervention Program; Elliott & Gresham, 2007), secondary (Tier 2, for some students) programs such as Check-In/Check-Out (Crone, Horner, & Hawken, 2004), and tertiary (Tier 3, for a few students) supports such as functional assessment–based interventions (Umbreit, Ferro, Liaupsin, & Lane, 2007).
Respecting the need to honor and protect teachers’ and students’ instructional time, we emphasize the importance of selecting practices with a strong evidence base and implementing those practices with high fidelity to increase the likelihood of obtaining desired outcomes (e.g., high academic achievement, successful interpersonal and self-determined skills). Instructional time is simply too precious to encourage the use of strategies and practices with insufficient evidence or implement evidence-based practices with insufficient fidelity. To support practitioners in this formidable task, the research community must identify compelling and justifiable approaches for synthesizing findings from treatment outcome (causal) studies conducted to provide greater confidence about “what really works.” Yet, this particular call can be especially challenging when working to identify evidence-based interventions for students with low-incidence disabilities in particular.
Focus on Single-Case Design: A Call for Greater Clarity
Although the process of evaluating and synthesizing causal studies employing group designs (e.g., randomized trials) has benefited from considerable attention and growing consensus in some respects (e.g., Gersten et al., 2005), there is less clarity on how to rigorously, accurately, and fairly evaluate causal studies conducted using single-case designs (Horner et al., 2005). As noted within this special issue, the What Works Clearing House Standards for Evaluating Single-Subject Research have been proffered as one promising approach for evaluating a body of studies using this design. Furthermore, initial testing of these proposed criteria is already underway to determine their utility and feasibility (e.g., Kratochwill et al., 2013; Maggin, Briesch, & Chafouleas, 2013). Although some agreement exists about important elements to consider when evaluating the rigor of experimental designs using single-case methodology, there is still important work to be done when it comes to approaches for synthesizing findings across studies. This is particularly true when the conversation turns to approaches for documenting the magnitude of the effects (Campbell, 2013; Scruggs & Mastropieri, 2013), with a key challenging being the serial dependency (autocorrelation) of single-case design data.
We applaud Daniel Maggin and Sandra Chafouleas for proposing, developing, and editing this special issue dedicated to the topic of single-case design methodology. We are encouraged by the rigor, relevance, and reach of the articles and commentaries constituting this special issue. We are confident consensus has not been achieved (e.g., Wolery, Busick, Reichow, & Barton, 2010); yet, we are hopeful this collection of articles will further deepen interest among applied researchers, methodologists, and statisticians in working collaboratively to establish meaningful procedures for synthesizing areas of the literature dominated by single-case design in such a manner enabling accurate comparisons between findings of causal studies conducted using experimental group and single-case designs.
We also applaud the Institute of Education Sciences (IES) for directing resources toward projects focused on the planning, execution, and analysis of single-case design data (Campbell, 2013). As single-case designs continue to be widely used in the field of special education, it is essential that scholars continue to refine and strengthen the analytic approaches available to the field. High-quality studies using single-case designs will continue to play an essential role in identifying evidence-based strategies and practices for enhancing the academic, behavioral, and social outcomes for students with and at risk for disabilities. Findings from such studies can provide practitioners and policy makers with access to the information they need to select and implement the best of what we know works within (and beyond) three-tiered models of prevention, with an overarching goal of improving educational experiences and outcomes for all students.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.