Using Incremental Science to Improve Inclusive Educational Psychology Research
Saved in:
| Title: | Using Incremental Science to Improve Inclusive Educational Psychology Research |
|---|---|
| Language: | English |
| Authors: | Jason C. Chow (ORCID |
| Source: | Educational Psychologist. 2025 60(3):172-188. |
| Availability: | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Descriptive |
| Descriptors: | Scientific Research, Sequential Approach, Special Education, Educational Research, Educational Psychology, Students with Disabilities, Research Design, Research Administration, Research Methodology, Individual Differences |
| DOI: | 10.1080/00461520.2025.2486140 |
| ISSN: | 0046-1520 1532-6985 |
| Abstract: | In the article, we use an incremental science approach to propose opportunities for researchers in educational psychology and special education to design and implement studies that are inclusive of theory development and students with disabilities. We describe the goals and purpose of incremental science in special education and how the incremental science framework is aligned with research methodologies and funding mechanisms. We provide examples of research that have advanced knowledge in special education and discuss the importance of individual differences and disability as diversity, intersectionality, and opportunities to advance and deepen the understanding of special education and students with disabilities' experiences by expanding the methodological approaches used across the incremental frameworks, highlighting methods and procedures used in special education. We conclude by emphasizing the importance of studying phenomena in real-world, complex contexts and provide additional examples and avenues for researchers to use incremental science to address both individual differences and structural challenges in education. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1506152 |
| Database: | ERIC |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwESjB0SFKcKg5LOZ0-wlkx1AAAA4jCB3wYJKoZIhvcNAQcGoIHRMIHOAgEAMIHIBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDOwQOwzll2LKLqigYAIBEICBmm-nVLpy-fXJcko9gwxku3xo8mOhRTe1FOplN_YxUFknQ_nM75EPMuUn5pEMpVpgAxIi2b0dYpsl_8gkvRY4uF4ySxDA-Wh-2XcuTxOhrCpgemlYJM7v02Ao50sSDZOIpu0TlPpCxWgTF5d__4P5C7aS2fJ7c93M2sPhwXIi_Ww1dQUGHQN-l7hUs1_Vt13Nb_ZBMUyXLp4iYxQ= Text: Availability: 1 Value: <anid>AN0186160233;epy01jul.25;2025Jun27.03:18;v2.2.500</anid> <title id="AN0186160233-1">Using incremental science to improve inclusive educational psychology research </title> <p>In the article, we use an incremental science approach to propose opportunities for researchers in educational psychology and special education to design and implement studies that are inclusive of theory development and students with disabilities. We describe the goals and purpose of incremental science in special education and how the incremental science framework is aligned with research methodologies and funding mechanisms. We provide examples of research that have advanced knowledge in special education and discuss the importance of individual differences and disability as diversity, intersectionality, and opportunities to advance and deepen the understanding of special education and students with disabilities' experiences by expanding the methodological approaches used across the incremental frameworks, highlighting methods and procedures used in special education. We conclude by emphasizing the importance of studying phenomena in real-world, complex contexts and provide additional examples and avenues for researchers to use incremental science to address both individual differences and structural challenges in education.</p> <p>Educational psychology and special education, as research fields, have many things in common. Both fields use theoretical rationales and rigorous research methods to address important and timely questions and problems in a concerted effort to identify and develop solutions that support the outcomes of a wide range of learners. There are also several key distinctions in the ways researchers have gone about enacting this process, including differences in the focus of the research relative to students with disabilities (SWD) and the educators and systems that support them in learning environments. Special education research, at its core, is focused on understanding the complexities of <emph>what works</emph>, <emph>for whom</emph>, and <emph>under what conditions</emph> (Glass, [<reflink idref="bib50" id="ref1">50</reflink>]; Ledford et al., [<reflink idref="bib74" id="ref2">74</reflink>]; Speece, [<reflink idref="bib111" id="ref3">111</reflink>]; Toste et al., [<reflink idref="bib119" id="ref4">119</reflink>]; What Works Clearinghouse [U. S. Department of Education, n.d.]). As such, special education researchers are often interested in the study of different developmental trajectories or pathways, as well as the characteristics, contexts, settings, and systems that influence individual outcomes.</p> <p>From its inception, the field of special education has prioritized ongoing research and generation of scientific evidence to guide decision-making. Despite the prevalence of disability, individuals with disabilities have been historically excluded and marginalized within social systems; as such, services were often delivered in residential facilities and hospital programs (Scheerenberger, [<reflink idref="bib101" id="ref5">101</reflink>]; Wehmeyer, [<reflink idref="bib128" id="ref6">128</reflink>]). This was also true for groups of children who experienced severe difficulties with acquisition of academic skills—for example, students with learning disabilities were provided remedial services in clinical settings even though they were enrolled in public schools (Wiederholt, [<reflink idref="bib131" id="ref7">131</reflink>]). Consequently, early instructional methods in the field of special education were primarily derived from medical and clinical fields.</p> <p>The purpose of this article is to describe how the priorities of special education have contributed to the use of an incremental science approach to research in this field. We believe there is potential for interdisciplinary growth between special education and educational psychology, with the goal of designing and implementing studies that are inclusive of a wide range of learners and address disability as an essential dimension of human diversity. Herein, we aim to make the case that incremental science increases interdisciplinarity, which can further enable innovative solutions to complex, contemporary challenges in education and enhance the applicability of findings to real-world contexts (National Academy of Sciences, [<reflink idref="bib91" id="ref8">91</reflink>]; Wang et al., [<reflink idref="bib127" id="ref9">127</reflink>]).</p> <p>In this article, we introduce an incremental science framework within special education research and demonstrate how to use a range of research designs that leverage individual differences to maximize the potential of pedagogy, instruction, and intervention. The use of strategic planning to generate a progression of research designs from exploratory studies to full-scale efficacy and effectiveness trials can improve efficiency of intervention development and design. Further, for this work to meet the needs of a diverse range of learners, it must include theory-driven research questions related to individual differences. The next section details a range of research designs and methods that are well-suited to allow researchers to answer research questions at different stages of an incremental research program. This includes the importance of the study of implementation when the goal is real world use and sustainment in practice and highlight the importance of this focus for students who learn in and teachers who work in diverse, inclusive settings. Finally, the <emph><sups>article</sups></emph> concludes with a discussion of the importance of studying phenomena in real-world, complex contexts and providing additional examples and avenues for researchers to be more inclusive in their research, which ultimately will advance the theoretical and practical understanding of what it means to be truly inclusive. Though this article focuses on advancing special education and disability representation in educational psychology research, it is important to note that there is, has been, and should be an ongoing synergistic relationship between special education research and educational psychology research. We posit that more efforts to actively and intentionally integrate fields of study have the potential to systematically increase the inclusivity, generalizability, and applicability of educational psychology research in real world settings.</p> <hd id="AN0186160233-2">Incremental science approach in special education research</hd> <p></p> <hd id="AN0186160233-3">What is incremental science?</hd> <p>Special education researchers have long emphasized the importance of individual differences and, through formal avenues, an incremental approach to knowledge generation. Herein we use the term <emph>incremental science</emph> in reference to the broader concept of the cumulative or incremental process of knowledge generation. We draw from the concepts of programmatic research, including transparency, replication, reliability, and reproducibility, and the notion that incremental, programmatic research is rigorous, planful, but takes time (Bradley, [<reflink idref="bib12" id="ref10">12</reflink>]; Klette, [<reflink idref="bib66" id="ref11">66</reflink>]; Lombardi et al., [<reflink idref="bib78" id="ref12">78</reflink>]; Strowig &amp; Farwell, [<reflink idref="bib113" id="ref13">113</reflink>]). Across fields, scientific progress is often seen as an ongoing and cumulative endeavor, where researchers build upon existing knowledge through a series of incremental steps, research questions, and studies. This can involve establishing sufficient evidence from smaller, pilot studies that constitutes the necessary data to proceed to larger-scale studies (Beets et al., [<reflink idref="bib8" id="ref14">8</reflink>]). We argue that special education has a somewhat unique orientation toward incremental science in that special education research is typically centered around the goal of improving outcomes for individuals with disabilities, families, service providers, and systems, and this focus remains a touchstone as ideas and knowledge progress. This approach involves building on existing knowledge, refining methodologies, and making gradual improvements to theories and interventions. In special education, where the needs of diverse learners are intricate and varied, incremental science plays a crucial role in advancing the understanding of effective methods, intervention strategies or programs, and service delivery systems. Researchers can systematically test and refine interventions, educational practices, and assessment tools, leading to the development of more targeted and individualized approaches. This iterative process not only contributes to the scientific knowledge base but also directly informs educators, practitioners, and policymakers, enhancing the quality of support and education provided to individuals with disabilities.</p> <p>We focus on three broad stages of incremental science: (<reflink idref="bib1" id="ref15">1</reflink>) exploration or hypothesis generation; (<reflink idref="bib2" id="ref16">2</reflink>) development, adaptation, and testing; and (<reflink idref="bib3" id="ref17">3</reflink>) efficacy, effectiveness, and replication (see Table 1 for definitions). These stages are not strictly sequential and can often occur in parallel. Further, an incremental science approach fosters a culture of continuous improvement and work across these stages, and is often cyclical, as researchers seek to address questions that address individual-, contextual-, and systems-level issues. For example, researchers may conduct exploration research that focuses on student-level factors (e.g., characteristics within a certain population) that informs the development and testing of an intervention program that targets key areas of need for these learners. Then, researchers may pursue further testing of the effectiveness of the program or determine that it is necessary to generate knowledge about factors that influence the strength and/or implementation of this program at the contextual-level (e.g., teacher interactions or delivery methods) or the school-level (e.g., current curricula being used, school scheduling, policy issues). Figure 1 provides a visual representation of the incremental science process, highlighting the importance of the recursive nature of this process when aiming to develop solutions for real-world settings. This further encourages collaboration among researchers, educators, and other stakeholders—and ensures that research in special education remains relevant, responsive, and effective, achieving more equitable educational access for all learners.</p> <p>Graph: Figure 1. Visual representation of the incremental science process.</p> <p>Table 1. Definitions of stages of the incremental science continuum.</p> <p> <ephtml> &lt;table&gt;&lt;thead&gt;&lt;tr&gt;&lt;td&gt;Terms&lt;/td&gt;&lt;td&gt;Definition&lt;/td&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody valign="top"&gt;&lt;tr&gt;&lt;td&gt;Exploration or hypothesis generation&lt;/td&gt;&lt;td&gt;Research that develops, clarifies, or expands theories of action and conceptual frameworks. This includes the examination of relations between malleable factors and outcomes of importance.&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Development, adaptation, and testing&lt;/td&gt;&lt;td&gt;Research that develops, adapts, modifies, or augments innovative programs, practices, or policies to ensure alignment to the needs of the individuals and communities that the research aims to benefit. This research should lead to pilot projects that can be scaled up.&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Efficacy, effectiveness, and replication&lt;/td&gt;&lt;td&gt;Efficacy research tests programs, practices, or policies to determine beneficial impacts on the outcomes of interest for the population(s) of interest. Effectiveness research evaluates a fully developed intervention or program with prior evidence of efficacy to determine whether it produces a beneficial impact on the outcomes of choice for the population(s) of choice under routine conditions in authentic settings. Replication research tests programs, practices, or policies that have previously been deemed efficacious or effective to better understand whom they work for and under what conditions.&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <hd id="AN0186160233-4">Individual differences in special education</hd> <p>The understanding of individual differences is a crucial aspect of various disciplines, including psychology and education (Deno, [<reflink idref="bib38" id="ref18">38</reflink>]; Underwood, [<reflink idref="bib123" id="ref19">123</reflink>]). The purpose of examining individual differences lies in understanding the variability among people across a range of traits, characteristics, and behaviors. Research that addresses diversity, equity, and inclusion related to individual differences in race, ethnicity, gender, age, or language often fails to capture the unique perspectives and experiences related to disability (Annamma et al., [<reflink idref="bib4" id="ref20">4</reflink>]). Such failure to recognize and elevate these unique perspectives and experiences is particularly concerning given that individuals with disabilities are the nation's largest minority group, comprising over 13% of the U.S. population or approximately 44 million people (U.S. Census Bureau, [<reflink idref="bib120" id="ref21">120</reflink>]). In K-12 education, 15% of all public-school students or 7.3 million students receive special education services under the Individuals with Disabilities Education Act (National Center for Education Statistics, [<reflink idref="bib92" id="ref22">92</reflink>]).</p> <p>Students with disabilities consistently underperform their nondisabled peers in academic content areas (Gilmour et al., [<reflink idref="bib49" id="ref23">49</reflink>]). For example, national data have indicated that the majority of fourth grade students with disabilities perform at what is considered a "below basic" level in mathematics (53%) and reading (70%), as compared to only 20% and 32%, respectively, of students without disabilities (National Center for Educational Statistics [NCES], [<reflink idref="bib93" id="ref24">93</reflink>]). This gap and level of poor performance persists through the eight and twelfth grades. Further, the performance of students with disabilities has not significantly changed over the past 20 years (NCES, [<reflink idref="bib93" id="ref25">93</reflink>]). More needs to be done to ensure that schools and education systems are meeting the needs of students with disabilities, and active consideration of disability as an important aspect of diversity across the array of educational programming and the broader system is essential. Given these outcomes, it is essential to continue building the knowledge base on how to support individuals with disabilities across the lifespan, and specifically in school settings where high quality instruction and supportive learning environment is foundational to later success. Fortunately, there is a strong evidence base for studying individual differences in special education.</p> <p>The study of individual differences suggests that optimal learning or performance results from instruction that is matched to the aptitudes of the learner (Preacher &amp; Sterba, [<reflink idref="bib97" id="ref26">97</reflink>]; Snow, [<reflink idref="bib109" id="ref27">109</reflink>], [<reflink idref="bib110" id="ref28">110</reflink>]). Key to this ongoing discussion are the dimensions of diversity and variability within and across participants in studies, including intervention studies, that may be masked by focusing on average effects alone (Chow, [<reflink idref="bib22" id="ref29">22</reflink>]; Speece, [<reflink idref="bib111" id="ref30">111</reflink>]). There is evidence to suggest that individual differences among students play independent and interactive roles in explaining academic, social, and behavioral developmental trajectories (e.g., Connor et al., [<reflink idref="bib19" id="ref31">19</reflink>]; Garon-Carrier et al., [<reflink idref="bib47" id="ref32">47</reflink>]; Letcher et al., [<reflink idref="bib76" id="ref33">76</reflink>]; Westrupp et al., [<reflink idref="bib129" id="ref34">129</reflink>]) and individuals' response to intervention (e.g., Bierman et al., [<reflink idref="bib9" id="ref35">9</reflink>]; Chow &amp; Wehby, [<reflink idref="bib28" id="ref36">28</reflink>]; Fuchs et al., [<reflink idref="bib45" id="ref37">45</reflink>]). These studies provide developmental and experimental evidence that individual differences, their characteristics, can determine their pathways through life and their responsiveness to learning environments, instruction, and intervention. Put differently, there is ample justification for researchers to plan for and embrace individual variation in the context of correlational, developmental, and experimental research in educational psychology and learning contexts (Anderson et al., [<reflink idref="bib2" id="ref38">2</reflink>]; Chow &amp; Lindström, [<reflink idref="bib27" id="ref39">27</reflink>]; Hopwood, [<reflink idref="bib61" id="ref40">61</reflink>]; Larson, [<reflink idref="bib70" id="ref41">70</reflink>]; Pellegrino &amp; Glaser, [<reflink idref="bib94" id="ref42">94</reflink>]). Though much of the research on individual differences has been the focus of developmental and descriptive analyses, there is important information and lessons the field can learn from studying individual differences in an intervention context.</p> <p>In a collection of intervention studies supported by the National Center for Special Education Research (NCSER), the journal <emph>Exceptional Children</emph> published a special issue highlighting the importance of moderator analysis in intervention research (see Fuchs &amp; Fuchs, [<reflink idref="bib43" id="ref43">43</reflink>] for the introduction). Here, moderator analysis is both a theoretical and statistical approach to help explain why an intervention or a program may have worked better (or worse) for some children versus others—and these analysis are based on individual differences. We highlight two complementary studies of mathematics interventions for children at risk for mathematics learning disabilities. Clarke et al. ([<reflink idref="bib17" id="ref44">17</reflink>]) examined the role of incoming mathematics skills in moderating the effects of a Tier 2 kindergarten mathematics intervention program aimed at improving kindergarten students' whole number concepts and skills. The study demonstrated that across all children in the intervention, initial math skill predicted response to intervention, on two specific outcomes, where children who were lower performing in mathematics at the beginning of the intervention benefited more than those with higher initial skill. In contrast, Fuchs et al. ([<reflink idref="bib44" id="ref45">44</reflink>]) tested a theoretically similar question on whether the severity of first-grade students' pre-intervention math skills predicted response to two variants of a 16-week tutoring intervention. The authors reported that incoming math skills moderated interventions effects, where children with lower pre-intervention math skills showed greater gains in the more intensive intervention variant, whereas children with higher pre-intervention math skills benefited more from the less intensive version. These studies suggest that there are likely multiple factors that influence how, why, and for whom individual differences in math performance, such as having math difficulty, may or may not maximize the utility of instructional environments.</p> <hd id="AN0186160233-5">Why individual differences are important in educational psychology</hd> <p>Though researchers in the social sciences have long discussed the importance and use of individual differences analyses, representation and diversity has been a key issue in educational psychology research. DeCuir-Gunby and Schutz (2014) presented a historical discussion of the importance of race and the state of race-focused explorations in the field of educational psychology, notably reporting that only 1.3% of articles published in top journals were considered race-focused or race-reimaged research. A special issue in <emph>Educational Psychologist</emph> on race, culture, and motivation centered on understanding the educational experiences of racial and ethnic minority youth and culturally grounded research methods (Zusho &amp; Kumar, [<reflink idref="bib138" id="ref46">138</reflink>]). Relatedly, a special issue in <emph>Contemporary Educational Psychology</emph> sought to increase representation of racial and cultural minorities in educational psychology and promote the integrity in how theories and methods represent racial and cultural constructs (Matthews &amp; López, [<reflink idref="bib81" id="ref47">81</reflink>]). Consistent through the arguments of these works was the changing demographic of the United States and increasing racial and ethnic diversity in schools. Seemingly absent in much of the conversation centered on diversity in educational psychology were topics on disability and special education. This theme is also present in a special issue on "revisiting" theories of motivation (Koenka, [<reflink idref="bib65" id="ref48">65</reflink>]); even though much of the discussion and dialogue specifically focused on underexplored issues in academic motivation, students with disabilities and special education were also noticeably absent.</p> <p>Given the trends seen with race-based research, it is not surprising that similar patterns exist with regards to special education and SWDs. To illustrate, in the context of a 10-year span in six educational psychology journals (2010–2020), students with disabilities were specifically included in only 11.4% of studies; these studies were primarily focused on mathematics and reading interventions (Emery et al., [<reflink idref="bib39" id="ref49">39</reflink>]). Many of the broader and more central topics to educational psychology were absent (e.g., identity development, motivation, engagement). Further, in a recent update of the effects of school-based social emotional learning interventions (Cipriano et al., [<reflink idref="bib30" id="ref50">30</reflink>]), an analysis of the representation of student disability in the intervention studies revealed that 11 studies explicitly excluded students with disabilities, and the representation within the studies varied in terms of their descriptions of the samples, including lack of race representation (Cipriano et al., [<reflink idref="bib30" id="ref51">30</reflink>]). This can prevent meaningful analyses, including explorations of intersectionality, to determine factors that may be associated with stronger effects for students with disabilities. This has led to underrepresentation of students with disabilities in educational research and overgeneralization of theories and empirical findings related to schools, classrooms, and students. As a part of this special issue and following the mission of identifying "what works and for whom," we argue that educational psychology has an opportunity to leverage individual differences analyses and incremental science to prospectively study psychological theories and processes for students with and without disabilities.</p> <p>Taking an incremental science approach may also improve the efficiency and rigor of research. The use of pilot or preliminary studies to inform larger, more costly studies is widespread across the fields of medicine, psychiatry, psychology, sociology, and education (Leon et al., [<reflink idref="bib75" id="ref52">75</reflink>]; Moore et al., [<reflink idref="bib88" id="ref53">88</reflink>]; Pfledderer et al., [<reflink idref="bib96" id="ref54">96</reflink>]; Smith, [<reflink idref="bib108" id="ref55">108</reflink>]; Thabane et al., [<reflink idref="bib118" id="ref56">118</reflink>]). This logic aligns with incremental science, highlighting the need for adaptation, refinement, and testing to ensure that studies are measuring the outcomes as intended, are proposing and developing feasible, implementable strategies and practices, and that the preliminary work is demonstrating acceptable levels of promise prior to moving to a large-scale study.</p> <p>There is evidence from clinical fields that suggest full-scale trials that included a pilot trial were published nearly a year earlier, on average, than full-scale trials without pilot trials, and in peer-reviewed journals with significantly higher impact factors (Ying &amp; Ehrhardt, [<reflink idref="bib133" id="ref57">133</reflink>]). Presence of a pilot trial, which is an important part of an incremental science approach, was associated with meaningfully lower risk of bias in the corresponding full-scale trial in elements of study design (Ying &amp; Ehrhardt, [<reflink idref="bib133" id="ref58">133</reflink>]). This suggests that the inclusion of a pilot study prior to conducting a full-scale trial may contribute to the temporality of dissemination efforts as well as the study quality. The pilot study serves as a small-scale, preliminary investigation that gathers initial data about the promise of the program, as well as information about the feasibility of study procedures, recruitment strategies, and data collection methods. This allows for the identification of issues, refinement of procedures and research questions prior to investing the time and costs associated with a large-scale trial. Next, we discuss important factors that contribute to building a program of research that centers on incremental science process.</p> <hd id="AN0186160233-6">Building a program of research through incremental science</hd> <p>In this section, we highlight opportunities to support a program of research that takes an incremental science approach. The purpose here is to illustrate the alignment between funding structures and incremental science, not to prioritize any specific funding institute, foundation, or mechanism. We also discuss inclusive theory development and include examples of three existing theories that illustrate the use of incremental science approaches. To provide a framework for progressive research designs aimed at having an ultimate impact on the lives of children and families, we detail theoretical and conceptual advancements aligned with Institute of Education Sciences (IES; https://ies.ed.gov/) funding structure (e.g., measurement; exploration; development and innovation; efficacy, effectiveness, and replication) and provide implications for theory development and research. The structure of the project types addresses the multifaceted nature of challenges in education and to promote a comprehensive and evidence-based approach to solving these challenges. By supporting a range of projects, IES aims to foster innovation, generate high-quality research, and build a strong foundation of evidence to guide education policy and practice. The structure allows IES to fund projects at various stages of development, from initial exploration of ideas to large-scale, long-term research initiatives, ensuring a holistic and dynamic approach to improving education outcomes.</p> <p>Our aim is to encourage the possibilities of engaging and federally funded opportunities to support an iterative, incremental approach to knowledge development and inclusive evidence-based practice, also recognizing that this work can, and sometimes must, be done absent of funding. Although the scope of studies may change as a function of funding available and obtainable, the goals of incremental science remain the same.</p> <p>The IES framework is useful because it centers the importance of individual differences and has long supported both general and special education intervention research. Further, IES has had a specific center for supporting outcomes of students with disabilities, the National Center for Special Education Research (NCSER), for over two decades. The Center requires researchers to include an intentional focus on the role of individual differences in trajectories of development and response (and nonresponse) to instruction and intervention, posing the broad question: <emph>What works, for whom, and under what conditions?</emph></p> <p>The National Science Foundation (NSF) and relevant institutes of the National Institutes of Health (e.g., National Institute of Child Health and Human Development [NICHD], National Institute of Mental Health [NIMH], National Institute on Minority Health and Health Disparities [NIMHD]) also have funding structures aligned with levels of research, though not as directly related to exploration, development, and testing of effective programming in educational contexts. To prospectively leverage understanding of individual differences in the design and development of a research program aimed at ultimately impacting educators and students in authentic settings, we focus on promoting an incremental science approach to interventions.</p> <hd id="AN0186160233-7">Alignment with current federal mechanisms</hd> <p>The structure of federal funding agencies encourage research to develop over a sequenced, intentional roadmap through phases of knowledge generation. Though recent recommendations (see National Academies of Sciences, Engineering, and Medicine [NASEM], [<reflink idref="bib90" id="ref59">90</reflink>]) have added additional priorities, the goal of this research development process to identify "what works for whom" remains. To this end, we provide examples of research that use an incremental science framework and then demonstrate how to use a range of research designs that align with different stages of the framework (e.g., developmental, longitudinal designs, single-case research designs, adaptive intervention designs, and quasi-experiments and randomized trials). We argue that strategic planning that uses a progression of research designs from pilot studies that demonstrate early promise to full-scale efficacy and effectiveness research can improve efficiency of intervention development and design, as well as their use and sustainment in practice.</p> <p>Key to the successful application of an incremental science approach is the prospective planning that engages a series of studies that simultaneously answer important research questions in a developmental progression from exploration to effectiveness and iterate and adapt in response to the knowledge being generated. If individual difference hypotheses, analyses, and data collection are included in studies at each phase, research gains more specific knowledge about how, why, and for whom interventions are most effective. Leveraging the expertise of multiple fields of study, different dimensions of child and human development, and building collaborative teams to support longer-term successful research partnerships may provide the scope of expertise and knowledge needed to move the needle on outcomes and ultimate success for students with disabilities.</p> <p>The success of incremental science is reliant on the continuity of funding and opportunities to support smaller-scale research studies that contributes to programmatic thinking. To be able to sustain an incremental science line of research from its inception through the testing and efficacy stages, researchers have traditionally needed to apply for separate research grants to continue the progression from exploration to development to efficacy to effectiveness. More assurances that the investment early can be highly supportive of high-quality research that is likely to see its way through the process—whether it be by one or multiple research teams that rely on other projects, developed interventions, and knowledge to advance the field. The latter has been more likely and can be seen through the examples in the next section.</p> <hd id="AN0186160233-8">Inclusive theory through the application of incremental science</hd> <p>In this section, we summarize three examples of theories that have proven helpful for advancing theory and knowledge of SWDs via an incremental science approach[<reflink idref="bib1" id="ref60">1</reflink>]. We provide these differing but aligned examples to illustrate the ways that current theories have been adapted, refined, or adjusted with the purposes of supporting students with disabilities and their educators and families. This section is not meant to be exhaustive, but to highlight programs of research that demonstrate inclusive incremental science.</p> <hd id="AN0186160233-9">Self-regulation theory</hd> <p>Self-regulation theory is rooted in the idea that individuals have the capacity to manage their thoughts, emotions, and behaviors in order to achieve desired goals. In its early understanding, this theory focused on how individuals monitor, control, and adjust their actions in response to internal and external stimuli (e.g., Zimmerman, [<reflink idref="bib136" id="ref61">136</reflink>]). The application of self-regulation theory to special education and academic interventions has been particularly impactful. In these contexts, self-regulation is viewed as a crucial skill for students with diverse learning needs, including those with learning disabilities or attention difficulties. By teaching students strategies to regulate their cognition, emotions, and behaviors, educators aim to enhance academic performance and foster independence (see Geldhof et al., [<reflink idref="bib48" id="ref62">48</reflink>] for review).</p> <p>Over time, researchers have considered the application of self-regulation theory to the development of instruction and intervention approaches that meet the needs of a wide range of learners. For example, the Self-Regulated Strategy Development (SRSD; Harris, [<reflink idref="bib56" id="ref63">56</reflink>]; Harris &amp; Graham, [<reflink idref="bib57" id="ref64">57</reflink>]; Harris et al., [<reflink idref="bib58" id="ref65">58</reflink>]) model is an evidence-based instructional framework that combines cognitive strategy instruction with self-regulatory components, designed to teach students strategies for planning, drafting, revising, and editing their writing. Developed by Harris and Graham in the 1980s, the SRSD framework emphasizes explicit instruction, strategy instruction, self-monitoring, goal setting, and self-evaluation. Through systematic instruction and scaffolding, students learn to integrate and apply self-regulation strategies to their writing tasks, leading to enhanced writing quality and fluency. SRSD has been widely used in both special education and general education settings and has shown effectiveness in improving writing outcomes for students, including those with disabilities (Graham et al., [<reflink idref="bib53" id="ref66">53</reflink>], [<reflink idref="bib52" id="ref67">52</reflink>]). Overall, the evidence that has been derived from the application self-regulation theory to special education and academic interventions underscores its importance for improving student outcomes. By empowering students with self-regulatory skills, educators can support their academic success and foster greater independence and autonomy in their learning journey.</p> <hd id="AN0186160233-10">Self-determination theory</hd> <p>As another example, Self-Determination Theory (SDT; Deci &amp; Ryan, [<reflink idref="bib36" id="ref68">36</reflink>]; Ryan &amp; Deci, [<reflink idref="bib100" id="ref69">100</reflink>]) highlights social context as it relates to motivating human action to meet three basic psychological needs: the need for autonomy, competence, and relatedness. Meeting these needs is described as an "energizer of behavior" (Deci &amp; Ryan, [<reflink idref="bib36" id="ref70">36</reflink>], p. 101) that, when satisfied, contribute to individual motivation. Within the field of special education, self-determination, defined by Causal Agency Theory, is a "dispositional characteristic manifested as acting as the causal agent in one's life" (Shogren et al., [<reflink idref="bib104" id="ref71">104</reflink>], p. 258). This theory is the latest iteration of a model that has driven research on interventions to support the development of self-determination in people with disabilities since the 1990s (Shogren et al., [<reflink idref="bib104" id="ref72">104</reflink>]). Causal Agency Theory further emphasizes the role of instruction that enhances motivation processes. Explicit instruction can teach skills associated with causal action (i.e., self-regulated goal setting and attainment) and these skills lead to enhanced action-control beliefs and the use of volitional and agentic actions in one's environment (Shogren &amp; Raley, [<reflink idref="bib105" id="ref73">105</reflink>]). Research in this field has evolved to integrate research and theory from multiple perspectives (e.g., social cognitive theory, disability advocacy), and this has been informed by research conducted across the stages of incremental science. Table 1 highlights areas of focus across these stages and includes some potential research methods that can be used to address similar questions across the stages of incremental science. The inclusive-focused evolution of this theory to meet the real-world needs of individuals with disabilities has helped advance theoretical application, but also the targeted focus on outcomes for individuals with disabilities.</p> <hd id="AN0186160233-11">Behavioral theory</hd> <p>Behavioral theory has been used to better understand teacher self-efficacy and motivation of students with and without disabilities. Student behavioral motivation increases as students access reinforcement for engaging in explicitly defined behavioral expectations. Behavioral theory has been successfully applied to classroom management strategies to increase the likelihood of positive student outcomes via reinforcement (e.g., Simonsen et al., [<reflink idref="bib107" id="ref74">107</reflink>]). Academic performance improves as student engagement increases and mediates the relation between instruction and learning via the performance-based model of instruction (PBMI; Greenwood, [<reflink idref="bib54" id="ref75">54</reflink>]). PBMIs posit that change in students' classroom behavior and academic achievement are a function of changes in instruction and teacher behavior. Behavioral theory and PBMI, when applied together, can improve the motivation, engagement, and academic performance of students with and without disabilities while simultaneously improving teacher self-efficacy as students acquire new skills and in turn, reinforce teachers' behavior for engaging in high quality instruction. Student extrinsic motivation can be enhanced by incorporating classroom interventions designed using behavioral theory to enhance student performance and in turn, increase teacher intrinsic motivation as their instruction results in improved student outcomes (Chow et al., [<reflink idref="bib24" id="ref76">24</reflink>]; Hollo &amp; Chow, [<reflink idref="bib60" id="ref77">60</reflink>]; Sutherland et al., [<reflink idref="bib115" id="ref78">115</reflink>]; Zimmerman et al., [<reflink idref="bib137" id="ref79">137</reflink>]). In turn, these interventions and practices can facilitate the dynamic link between teachers' self-efficacy, instruction, motivation, and improved outcomes for students with and without disabilities. For example, the BEST-in-CLASS program was developed as a value-added intervention to enhance and support teachers' use of effective instructional practices through increasing teacher self-efficacy and improving their relationships with their students with or at risk for emotional and behavioral disorders (Conroy et al., [<reflink idref="bib20" id="ref80">20</reflink>]; Sutherland et al., [<reflink idref="bib115" id="ref81">115</reflink>]). Special education has a long history of using behavioral theory to improve student outcomes and can be combined with motivational theory to improve outcomes for students with disabilities, families, and teachers. Next, we discuss the stages of incremental science and corresponding research questions and methods.</p> <hd id="AN0186160233-12">Research questions and methodologies across stages of the incremental process</hd> <p>In this section, we provide examples of research questions that might be addressed within different stages of the incremental process—keeping in mind that these questions can represent parallel and cyclical work that aims to understand optimal outcomes for SWDs. We also discuss relevant research methods that support these lines of inquiry. Though not intended to be an exhaustive list of methods, we share commonly used methods related to the three broad stages: (<reflink idref="bib1" id="ref82">1</reflink>) exploration or hypothesis generation; (<reflink idref="bib2" id="ref83">2</reflink>) development, adaptation, and testing; and (<reflink idref="bib3" id="ref84">3</reflink>) efficacy, effectiveness, and replication. Proactive integration of these methods over a series of studies, a research program, or within the scope of a funded research grant is useful in the intersecting fields of educational psychology and special education because it provides theoretical, conceptual, and empirical continuity. This approach ensures that SWDs are consistently and proactively included in the development of educational theories and programs, rather than being retrofitted into frameworks that did not include SWDs in their development.</p> <hd id="AN0186160233-13">Exploration or hypothesis generation</hd> <p>The purpose of work in this stage is well-aligned with much of educational psychology research, which is to develop, clarify, or expand theories, models, and frameworks by studying relations or influences between individuals, settings, and systems (Alexander &amp; Winne, [<reflink idref="bib1" id="ref85">1</reflink>]; McInerney, [<reflink idref="bib83" id="ref86">83</reflink>]; Schutz &amp; Muis, [<reflink idref="bib106" id="ref87">106</reflink>]). Relative to hypothesis generating research, these studies help generate or inform hypotheses about how interventions, programs, or policies can best support key outcomes of interest, such as student learning, behavioral, or social outcomes, or teacher's self-efficacy or pedagogical practices. This work can directly and meaningfully inform future development and testing research by unveiling potential active ingredients of intervention efficacy and providing important qualitative and substantive contextual knowledge about the systems that education and inclusive teaching practices take place.</p> <p>Questions that researchers might pose in this stage of research include, but are not limited to: What are important predictors of student outcomes? What are the developmental trajectories of students that come from different backgrounds and what factors are associated with more positive trajectories? What are the features of instructional practices or programs that distinguish them from each other? Why do you think it will work? Why do implementers think it will work? What are the barriers to access to specific programs, practices, or resources? What does existing theory say about how existing practices are "supposed" to work? Does previous evidence account for differences across groups of learners or contexts? Do we know which contextual factors may be influencing outcomes? Do we know which contextual factors may be influencing delivery of the practice? Are outcomes consistent across different groups of learners and different contexts?</p> <p>In research that focuses on exploration or hypothesis generation, researchers can use a wide range of research methods that are well-suited for nuanced, rich descriptions of phenomena and understanding processes. These include descriptive, correlational, and longitudinal research designs, observation research that rely on observational methods, qualitative and mixed-methods research, interviews and focus groups, survey designs, and secondary data analysis that include the use of existing secondary data sets and conducting rigorous systematic reviews. These methods are foundational to understanding the <emph>how</emph> and <emph>why</emph> of human behavior as well as particularly influences on the use of practices.</p> <p>One body of methodological research that is common in special education research methods that aligns with exploration and hypothesis generation research comes from the field of observational measurement (Bakeman &amp; Quera, [<reflink idref="bib6" id="ref88">6</reflink>]; Yoder &amp; Symons, [<reflink idref="bib134" id="ref89">134</reflink>]). These methods include tools for systematic, direct observation that can reliability characterize moment-to-moment social and behavioral interactions between individuals, such as students and their peers and teachers (see Landrum et al., [<reflink idref="bib69" id="ref90">69</reflink>]). Importantly, these methods can be used to provide the sensitivity necessary to provide content-valid outcome measures of assessing behavior as well as the fidelity of behavioral interventions in classroom context, especially for improving outcomes for students with emotional and behavioral disorders (Lloyd &amp; Wehby, [<reflink idref="bib77" id="ref91">77</reflink>]). Observational measurement procedures can also be adaptable for use in classroom settings my practitioners. For example, complex procedures like contingency space analysis (i.e., identifying contingent relations observational data from conditional probabilities; Martens et al., [<reflink idref="bib80" id="ref92">80</reflink>]) can be used in classrooms to measure behavioral contingencies to best inform behavioral interventions for students who present challenging behavior in school settings (Staubitz &amp; Lloyd, [<reflink idref="bib112" id="ref93">112</reflink>]). For an excellent overview of observational measurement and the larger family of these methods, see Yoder et al., [<reflink idref="bib135" id="ref94">135</reflink>].</p> <hd id="AN0186160233-14">Development, adaptation, and testing</hd> <p>The purpose of work in this stage is to develop, adapt, and pilot innovative, theory and/or data-driven programs, practices, interventions, or policies that have promising benefits on key outcomes. After rigorous, iterative development and piloting, these promising programs, interventions, or policies can then be evaluated at scale. A key feature of development projects is the goals are to optimize—in that an iterative development process with feedback from key constituents can inform the best, most usable and feasible end product. Within this process, researchers should consider what the core elements or components of the program, practice, or policy are, factors related to implementation and usability support, and relevant financial implications and cost factors directly related to successful implementation.</p> <p>In research that aims to develop, adapt, and test interventions, programs, and other instructional practices, useful methods that allow for both the testing of efficacy and data collection that provides a nuanced understanding of the features that are important to the development and adaptation process include single case design research, mixed-methods research, pilot (or underpowered) randomized experiments, and adaptive intervention designs. In this stage of work, it is important to balance the goals of obtaining promising evidence of the efficacy of an intervention or program with the need for understanding (and collecting) descriptive and qualitative data to understand why things worked, why they did not work, and for whom they may have worked better for. Built into these designs is the recognition that smaller-scale, and perhaps more rapid iterations of testing are needed to determine and design a promising intervention or program.</p> <p>From its inception, special education research has used experimental methods to test the efficacy of individualized interventions on individual students using single-case designs. Not to be confused with case studies, single-case design experimental research uses rigorous methods to reduce or eliminate threats to internal validity that allow for researchers to determine whether or not there was a causal, functional relation between the intervention and observed behavior change (Kazdin, [<reflink idref="bib64" id="ref95">64</reflink>]; Ledford &amp; Gast, [<reflink idref="bib73" id="ref96">73</reflink>]). Within the context of an incremental science framework, single-case designs are well-suited to experimentally test the effects of interventions on individuals or groups of individuals (e.g., classrooms, school-level outcomes, communities) while simultaneously allowing for detailed and repeated observations of the intervention in progress and outcomes being assessed. Here, researchers can observe, adapt, and refine specific and detailed procedures within interventions, and re-test and reevaluate if needed, prior to a potential randomized trial to ensure that the components of the intervention are well-aligned with the intervention goals, implementer needs, and student/individual outcomes.</p> <p>Using single-case design, Roberts et al. ([<reflink idref="bib99" id="ref97">99</reflink>]) tested the efficacy of the Teach-Model-Coach-Review (TMCR) instructional approach in improving caregivers use of evidence-based language strategies with children with language impairment. Authors reported that TMCR was effective in improving language strategy use after instruction, but generalization and maintenance were limited. Results and lessons learned from this study informed a larger randomized control trial that tested the effects of the intervention on caregiver and child language outcomes (Roberts et al., [<reflink idref="bib98" id="ref98">98</reflink>]). Using an RCT, researchers were able to test the effects of intervention compared to a control group on caregiver outcomes as well as detect meaningful improvements in child language outcomes. Importantly, single-case designs are flexible and not limited to individual children, dyads, or classrooms. Similarly, Peredo et al. ([<reflink idref="bib95" id="ref99">95</reflink>]) used single-case design to test the promise using TMCR for improving Spanish speaking care-giver's implementation of an evidence-based language intervention and outcomes for their young children with language impairment in Spanish. Results and lessons learned from the single-case study informed a pilot randomized control trial which tested the effects of the intervention in a group design, randomized context. These are just two examples of many research programs that use single case design in to develop and adapt intervention programs.</p> <p>Single case designs can also be use to test the effects of larger, school-wide or community-based interventions. In terms of community-based, violence prevention research, Mehari et al. ([<reflink idref="bib84" id="ref100">84</reflink>]) propose using single-case designs to address factors that contribute to the root cause of youth violence in community settings. They propose that single case designs—multiple baseline designs, specifically—have the potential to address the numerous methodological challenges that come with implementing and evaluating community-level interventions. In an impact evaluation study, Farrell et al., ([<reflink idref="bib41" id="ref101">41</reflink>]) and Sullivan et al. ([<reflink idref="bib114" id="ref102">114</reflink>]) used a single-case design to test the causal effects of the Olweus Bullying Prevention Program (OBPP) over an eight-year period in urban middle schools. Their research team used a multiple baseline design (across schools) and examined the effects of OBPP on bullying behaviors, aggression, victimization, and school climate. This study is an example of the use of a single-case design where the unit of analysis were schools that were randomly assigned to receive the intervention beginning in a specific year. Given these examples, single-case design can be used to study a broad range of interventions and programs, including intensive, complex interventions at the individual child level and broader, comprehensive programming at the school or community level.</p> <hd id="AN0186160233-15">Efficacy, effectiveness, and replication</hd> <p>The purpose of work in this stage is to assess the immediate and/or longer-term impacts of programs, practices, interventions, or policies on meaningful, relevant outcomes (Hunsley &amp; Lee, [<reflink idref="bib62" id="ref103">62</reflink>]). Studies in this category may also aim to document how and why the interventions work, or did not work at scale, and focus on implementation, support needs, and cost. Efficacy studies test programs, practices, interventions, or policies that have demonstrated previous promising effects, through a development and innovation project, as an example. Replication studies test programs, practices, interventions, or policies that have already been rigorously evaluated and aim to ensure the effects replicate, and often focus on varying conditions, contexts, and populations to better understand the scope of efficacy that provide information on what works for whom and under what conditions.</p> <p>For the scope of work, researchers can rely on traditional experimental designs such as randomized control trials and cluster randomized trials to leverage the strength of randomization to provide confidence in causal estimates. For programs or policies for which randomization is not possible or unethical, researchers can use quasi-experimental designs like regression discontinuity designs and fixed-effect regression models (Chow &amp; Lindström, [<reflink idref="bib27" id="ref104">27</reflink>]; Murnane &amp; Willett, [<reflink idref="bib89" id="ref105">89</reflink>]). To illustrate, a school district may adopt a policy that will roll out across the district at the same time such as a multitiered systems of support (MTSS) model to support all students from a tiered, responsive, progress-monitoring framework. In this case, randomizing schools within a district, or classrooms/teachers within a school, to such a policy is not possible (and could be unethical if it is a policy about equity or access, such as inclusion policies or teacher salary policies). For an example, see Coyne et al. ([<reflink idref="bib33" id="ref106">33</reflink>]) who studied the effects of a supplemental reading intervention for students at risk for reading disabilities in the context of district-implemented multitiered systems of support. Using a regression discontinuity design, they reported statistically significant effects of the tutoring intervention on students' phonemic awareness and word decoding skill. Because the school district was implementing MTSS, all students who qualified for supplemental reading instruction needed to receive the additional tutoring. In this case, randomization of students to receive intervention was not possible. Using a regression discontinuity design to understand the impact of the supplemental reading intervention on reading outcomes, the research team was able to provide a causal estimate of the effect of the reading intervention on student outcomes absent of a pure randomized experimental design.</p> <hd id="AN0186160233-16">Illustration of an incremental science approach</hd> <p>The design of the pilot, efficacy, and effectiveness studies should include the measurement of malleable factors to help discern for whom the larger intervention was more or less effective. Doing so can help researchers tweak, iterate, and tailor specific, potentially adaptive components of the intervention to best meet the needs of a broader range of students, teachers, and families. To illustrate the incremental science approach and the corresponding connections to knowledge generation and research design and quality, we provide an example of using these methods to advance a line of research in the context of ecological systems theory (Bronfenbrenner, [<reflink idref="bib14" id="ref107">14</reflink>], [<reflink idref="bib15" id="ref108">15</reflink>]). Ecological systems theory has been applied in educational psychology, special education, and in numerous other fields, traditions, and contexts. The primary argument of this theory is that to understand human development, it is important to consider the larger ecological system in which that development occurs. We use this theory to provide an example of how to apply and extend existing psychological theory to be inclusive of SWDs and their context</p> <p>To illustrate using the end goal of supporting teachers' ability to effectively support children's language, social, and behavioral development in early learning contexts, a research program using ecological systems theory can focus on factors associated with inclusion, SWDs, and teacher preparation, skills, and self-efficacy across the series of studies (Cunningham et al., [<reflink idref="bib35" id="ref109">35</reflink>]). Following the incremental science pathway that is inclusive of SWDs, researchers might begin with a measurement study that focuses on understanding how to measure, capture, and account for variation in classroom contexts, and the numerous contributing factors that act as resources and limiters to inclusive classroom environments. These factors could involve observable, malleable classroom level factors (e.g., supplies, teacher pedagogical skills, peer relationships), affective variables (e.g., teacher self-efficacy, perceptions of inclusion and disability), system-level factors (e.g., administrative support, professional development opportunities, educator community and collective efficacy), and external factors (e.g., political climate and sociopolitical factors, neighborhood characteristics, weather) (Granger &amp; Chow, [<reflink idref="bib51" id="ref110">51</reflink>]). In one recent example for external factors, Chung and Liu ([<reflink idref="bib29" id="ref111">29</reflink>]) use an instrumental variable approach to show that ambient air pollution influences student and teacher outcomes such as absenteeism and office discipline referrals. Using wind direction as an instrument for pollution exposure, the authors show that increases in daily air pollution causes a 5.7% increase in full-day student absences and a 28% increase in office referrals within a three-day window. The study also demonstrates that increases in daily air pollution cause a 13.1% increase in teacher absences due to illness. Furthermore, individual differences within this analysis shows that effects were primarily driven by low-income, Black, Hispanic, and younger students. This quasi-experimental approach provides causal estimates that environmental factors can have a causal impact on student and teacher outcomes highly germane to school success and achievement. As demonstrated in this example for external factors, ecological approaches would align with the importance of identifying key factors in the broader ecology of a student's experiences to enable the characterization of the contribution of these factors to student outcomes. This includes classroom factors that have a direct impact on students' educational environments such as resources and limiters to successful teaching and daily school functioning (Granger &amp; Chow, [<reflink idref="bib51" id="ref112">51</reflink>]).</p> <p>This points to another important step which is the development and validation of a measure that produces reliable scores across groups and contexts that will increase the rigor of subsequent research by relying on a well-developed, theoretically aligned, reliable and valid system of measurement. The ability to capture contructs that are important to student outcomes but also reflect the dynamic nature and nuance of the classroom environment is complex. Once this is achieved, an exploration study can study the longitudinal role of these ecological factors on student, teacher, administrator, and family outcomes; a study inclusive of SWDs could focus on specific outcomes of students with disabilities and special education teacher outcomes.</p> <p>After developing the reliable measure and, through an exploration study, identifying ecological predictors (e.g., resource or limiting factors) of important student, teacher, administrator, and family outcomes, the next step is to design, iteratively develop, and test an intervention that isolates key predictors of later outcomes, aiming to enact change to reduce the impact of a limiting factor or promote the use of or access to a resource factor. For example, the measurement and exploration study may identify effective, ongoing professional development (PD) and active home-school partnerships to be strong predictors of student achievement; the study may also have revealed that home-school partnerships are particularly important for studies with disabilities given the integral role families are designed to play in the special education and individualized education program development and implementation. The development study would use these factors as more components to develop an intervention that focused on improving aspects of these factors, using an iterative process with feedback from stakeholders, and test the promise of the intervention. Upon a successful pilot study (e.g., using single-case experimental designs or a pilot RCT), then the research team would be ready to test the effects of the intervention at scale using an efficacy trial that was designed to be implemented at high fidelity in a relatively controlled setting. This efficacy trial is also likely to be better informed and more efficiently developed than other trials not based on the pilot trial findings, improving progress and alignment to the outcomes of interest for the populations of interest especially when including intention adaptation and refinement (Hampton &amp; Chow, [<reflink idref="bib55" id="ref113">55</reflink>]; Ying &amp; Ehrhardt, [<reflink idref="bib133" id="ref114">133</reflink>]). Then, an efficacious, fully powered RCT would move into the effectiveness stage where the design would ensure that the intervention on increasing access to relevant and ongoing PD and home-school communication could be implemented in real-world, authentic education settings by the stakeholders. Following the real-world study, the research would then transition to a focus on consistent, end-user implementation and sustainment in routine practice. This can include a specific focus on implementation processes and sustainment outcomes, or measurement of different aspects of the durability of an intervention or program.</p> <hd id="AN0186160233-17">Future directions and addressing diversity to ensure inclusive research</hd> <p>Aligned with the purpose of this special issue, we highlight several avenues that can lead to the next generation of inclusive research (see Figure 2). We summarize several broad areas for future development and collaboration. Linking to previous sections of this <emph><sups>article</sups></emph>, researchers could identify constructs that may serve as malleable developmental or intervention factors and measure those potential active ingredients in the context of an existing longitudinal study or randomized trial. Linked to the theoretical and conceptual advancements, educational psychology researchers can collaborate to integrate areas of interest into existing or new grant-funded projects, which can provide direction and/or a roadmap to the integration of educational psychology research and students with disabilities and their families. Research communities can work together toward the intentional integration of SWDs, special education teachers, and disability policy factors from the onset of educational psychology theories, theory development initiatives, and promising or efficacious core interventions for SWD.</p> <p>PHOTO (COLOR): Figure 2. Opportunities for diverse, inclusive research leveraging individual differences and structural change.</p> <p>In line with this special issue, a primary way to broaden the reach as well as the inclusion of theory, perspectives, and experiences (including lived experiences of individuals with disabilities) within the context of the presented incremental science framework is to design integrative studies to use multiple methods that draw on unique and complementary epistemologies, research methodologies, and positionalities (Cumming et al., [<reflink idref="bib34" id="ref115">34</reflink>]; Fielding, [<reflink idref="bib42" id="ref116">42</reflink>]; Mertens, [<reflink idref="bib86" id="ref117">86</reflink>]; Sells et al., [<reflink idref="bib102" id="ref118">102</reflink>]; Wallis, [<reflink idref="bib126" id="ref119">126</reflink>]). In this article, we promote the use of incremental science and align it with current funding institutions. We acknowledge this alignment, and while doing so, see an opportunity for educational psychologists to bring differing perspectives to collaborations and professional discourse, some of which may manifest as research proposals for funding. As presented in the first section of this <emph><sups>article</sups></emph>, educational psychology as a community is really pushing back on the past, including the traditional research questions, foci, methods, and measures, that have been the majority to date (Cipriano et al., [<reflink idref="bib30" id="ref120">30</reflink>]; Emery et al., [<reflink idref="bib39" id="ref121">39</reflink>]; Koenka, [<reflink idref="bib65" id="ref122">65</reflink>]; Matthews &amp; López, [<reflink idref="bib81" id="ref123">81</reflink>]; Zusho &amp; Kumar, [<reflink idref="bib138" id="ref124">138</reflink>]). Intentionally leveraging critical methodologies by infusing these methods into the descriptive stages of research early on that identify, describe, and synthesis key issues and priorities for development and change can be instrumental in ensuring priorities are represented (during exploration or hypothesis generation) and also responded to (during development, adaptation, and testing). This early collaboration, co-creation, and knowledge generation may also help bridge gaps in the field that often lie between research methods and epistemologies. We acknowledge that this author team does not have expertise in critical lenses or methodologies, but we submit that generating discussion (and consensus when possible) and intentional collaboration in the early stages of research may be specifically fruitful in addressing inequities in special education. Robust methodologies or lenses like disability critical race theory/Disability Critical Race Studies (DisCrit) and DefectCraft (Artiles, [<reflink idref="bib5" id="ref125">5</reflink>]; Tefera et al. [<reflink idref="bib116" id="ref126">116</reflink>]) are poised to influence every aspect of the incremental science approach including but not limited to the focus of research, the measures selected, data interpretation and integration, and the value of outcomes. Further, the reach of DisCrit research lends itself well to the study of nearly all aspects of life and the systems that influence it. We recommend Annamma et al. ([<reflink idref="bib4" id="ref127">4</reflink>]) for a comprehensive and critical review.</p> <p>On intersectionality (i.e., how different and multiple social identifies combine to create unique experiences of discrimination and privilege) in special education, many scholars have identified intersectional perspectives as complex and essential to fully understanding the educational experiences of children and youth with disabilities (Boveda &amp; Aronson, [<reflink idref="bib10" id="ref128">10</reflink>]; García &amp; Ortiz, [<reflink idref="bib46" id="ref129">46</reflink>]; Hernández-Saca et al., [<reflink idref="bib59" id="ref130">59</reflink>]). Previous reviews and collections in educational psychology have focused on highlighting specific intersections and dimensions of individuality and identity that should be included and elevated, and disability (and special education) should be a part of the larger goal and development toward a consolidated, comprehensive framework of intersectionality. Though intersectionality is not a primary focus of this <emph><sups>article</sups></emph>, there are opportunities to use intersectional frameworks and perspectives to include disability and special education as important identities that influence educational experiences of students with disabilities. For example, a critical disability intersectional qualitative approach (Tefera &amp; Fischman, [<reflink idref="bib117" id="ref131">117</reflink>]) focuses on using data to contribute to and transform special education policy research and is a framework that relies on active engagement with the many processes of marginalization and centering the intersections of students with disabilities in education research and policy research (Annamma et al., [<reflink idref="bib3" id="ref132">3</reflink>]; Bal &amp; Trainor, [<reflink idref="bib7" id="ref133">7</reflink>]; Erevelles &amp; Minear, [<reflink idref="bib40" id="ref134">40</reflink>]). Critical scholars in education, sociology, educational psychology, and special education can bring this expertise to pressing problems in society as well as help shape the discourse on the multidimensionality of disability in society.</p> <p>Through the interdisciplinarity of the incremental science approach, educational psychologists and their teams and collaborators can be well-poised to address complex, structural issues in education systems. Individuals, including those with disabilities, learn and develop within environments, structures, and systems. It may be that taking an interdisciplinary approach to examining and developing effective and sustainable solutions to differing belief systems in special education service delivery requires incremental science. To illustrate, many children with autism receive services from speech language pathologists (SLPs) and board-certified behavior analysts (BCBAs). Given the different theoretical underpinnings and instructional approaches of applied behavior analysis and speech therapy, sectors of these fields have long been at odds (Isaacson, [<reflink idref="bib63" id="ref135">63</reflink>]; Volkers, [<reflink idref="bib125" id="ref136">125</reflink>]). This has led to issues in successful collaboration and lack of professional agreement, which is a challenge given the overlap between SLPs and BCBAs in school-based special education service delivery (Bowman et al., [<reflink idref="bib11" id="ref137">11</reflink>]). Using a purposeful, interdisciplinary approach to converge on theoretical and practical alliance is possible through incremental science and can provide proactive and needed unification of theory and purpose (Lane &amp; Brown, [<reflink idref="bib68" id="ref138">68</reflink>]). Starting by exploring why conflict exists with a team that represents multiple perspectives before co-developing solutions is an important, incremental step. This can ultimately help align practitioners and service delivery models, as well as training and certification programs, to support SWDs who receive special education services from multiple practitioners and ensure that they are receiving the educational services they deserve (Chow, [<reflink idref="bib23" id="ref139">23</reflink>]). Further, the mechanisms for successful interprofessional practice and collaboration may be well-aligned with educational psychology theories and adult behavior, including collective and self-efficacy and motivation (Ly &amp; Boll, [<reflink idref="bib79" id="ref140">79</reflink>]; Meirink et al., [<reflink idref="bib85" id="ref141">85</reflink>]; Wexler et al., [<reflink idref="bib130" id="ref142">130</reflink>]; Zimmerman et al., [<reflink idref="bib137" id="ref143">137</reflink>]). The study of self-efficacy and motivation to collaborate can addresses individual differences of professionals within layers and systems that predicate the quality of services children access. The <emph>individual differences</emph> are the SWDs, the professional training, attitudes, and perceptions of SLPs, BCBAs, and their special and general education teachers. The <emph>structures and systems</emph> are the training and certification programs each practitioner came from, including the accrediting body of each profession. This has layers of complexity given that speech pathologist licensure in the United States is overseen by the American Speech Language Hearing Association, and behavior analysts are overseen by the Behavior Analyst Certification Board, both of which operate at the national level. However, general and special education teachers are licensed and accredited at the state level, which leads to potential issues in experience and perceptions because education and service delivery is facilitated by multiple practitioners that are trained and certified through completely different organizations and pathways. Joining together through genuine interprofessional practice is likely a more effective pathway to effective interdisciplinarity and better support outcomes for SWDs who have individualized education programs.</p> <p>Another arena of inclusive theory-building and improving work will be to interrogate existing, well-accepted theories in educational psychology by collecting data and testing the theory with appropriate and multiple measures. Each field of study has histories for measurement of constructs and "gold-standard" approaches, but there is more to be gained from learning new methods that may advance or improve construct measurement. For example, both qualitative and qualitative data can be collected through observational measurement procedures that capture observable, probably, and contingent relationships (Yoder et al., [<reflink idref="bib135" id="ref144">135</reflink>]), ecological momentary assessment procedures that allow for repeated sampling in real time to study microprocesses in real world contexts (Shiffman et al., [<reflink idref="bib103" id="ref145">103</reflink>]), network analysis methods that provide a more nuanced understanding of connections between variables, individuals, and the flow of information and knowledge (Broda et al., [<reflink idref="bib13" id="ref146">13</reflink>]), and more recently widespread, the use of machine learning methods, such as natural language processing, with numerous applications to advancing scientific knowledge and improving efficiency in education research (Kim &amp; Kwon, [<reflink idref="bib67" id="ref147">67</reflink>]). Learning from different measurement paradigms can expand the assessment repertoire of a research team and, in turn, extend the reach, efficiency, impact, and implications of research findings. '</p> <p>Ensuring that the sample populations in empirical research represent those that the theories are intending to support is essential for alignment, relevance, and generalizability. This is particularly important if researchers apply a theory to a specific developmental or experimental study with the goal of making decisions for SWDs and their teachers and other classroom and school support staff. Given the purpose of this special issue, leveraging the collaborative synergy of interdisciplinary work can support the uptake and important planning these types of inclusive projects require. There are several professional fields that overlap in both research and practice like school psychology, clinical psychology, special education, and speech and hearing sciences. All these fields have a strong and important presence in meeting the needs of children and youth with disabilities and other clinical disorders, some which include educational service provision under IDEA and some that do not. Intentional collaboration from the exploratory research through development and testing of interventions can benefit from understanding the within- and between-discipline similarities and differences in research methods, measurement, and design.</p> <p>Single-case designs can, by design, often be highly adaptive to a participant's response to an intervention or a component of an intervention. The logic behind these designs is directly aligned with one of the major tenets of special education, which recognizes and values that children and youth with disabilities have unique strengths and differences, and have a right to an inclusive, effective education. There is a strong body of evidence in special education indicating that the effectiveness of a particular instructional practice will depend on the individual skills and characteristics of the student. Adaptive intervention designs that fall within the group experimental design paradigm are conceptually aligned with single-case research designs, that are commonly used in special education research and other fields like school psychology, in that they adapt, change, and are responsive to how an individual or group responds to an intervention (Brown et al., [<reflink idref="bib16" id="ref148">16</reflink>]; Chow &amp; Hampton, [<reflink idref="bib25" id="ref149">25</reflink>]; Hampton &amp; Chow, [<reflink idref="bib55" id="ref150">55</reflink>]). Designing adaptive interventions that have the capacity to include general education classrooms while also attending to the individual needs of students could be an impactful opportunity to integrate SWDs and variation in student populations into classroom-based research in educational psychology. Incorporating mechanisms that are inclusive, and are designed and prepared to address the needs of students who do not respond to an initial, general (e.g., Tier 1, class wide) intervention or program through proactively planned intervention intensification can provide additional supports for SWDs and other nonresponders (or individuals for whom a prescribed intervention is not effective) within the parameters of a larger randomized experiment or adaptive intervention trial. Researchers have recently argued for adaptive designs like sequential multiple-assignment randomized trials that aim to develop causal evidence for the best combination and sequence of intervention components as a promising area of continued research in educational psychology (Chow &amp; Hampton, [<reflink idref="bib26" id="ref151">26</reflink>]). There are also ample opportunities for a stronger focus on cultural adaptation given the increasing cultural and linguistic diversity in public schools. For example, focusing on adaptive interventions to improve implementation for interventions for historically marginalized groups can improve the mobilization and implementation of evidence-based strategies across a variety of practices, settings, and populations (Lau et al., [<reflink idref="bib71" id="ref152">71</reflink>]; Yeh et al., [<reflink idref="bib132" id="ref153">132</reflink>]). Tailoring professional development in school settings to focus on or include components of cultural and linguistic diversity also is associated with improve outcomes (Larson et al., [<reflink idref="bib72" id="ref154">72</reflink>]).</p> <p>Integrating and learning from the multiple adaptive intervention frameworks theories, models, and frameworks may help improve the efficiency and effectiveness of development and testing at scale—fields are likely to learn from each other in the process. Adaptive interventions and incremental science approaches align with other intervention development and testing frameworks originating in other friends, such as the multiphase optimization strategy (MOST; see Collins et al., [<reflink idref="bib18" id="ref155">18</reflink>]). The MOST framework begins with a screening phase to identify effective components of intervention to be included in the intervention based on performance and early promise; a refining phase where components identified in the screening phase are fine-tuned and any potential issues to implementation and success are addressed; and it concludes with a confirmation phase where the identified and refined components are evaluated at scale. Within or alongside this process, drawing from clinical psychology and the mental health literature by applying a common elements approach to identifying, selecting, and matching effective practices to clinician and client needs (Chorpita et al., [<reflink idref="bib21" id="ref156">21</reflink>]) could help improve the precision of the screening phase of MOST and tailor the model to include specific practices that are effective for SWDs. Conference grant proposals and other generative efforts to bring together health, clinical, educational, and implementation researchers could be a way to integrate federal agencies into the conversation as well. For example, the National Science Foundation, Spencer Foundation, various institutes of the National Institutes of Health, and American Educational Research Association have conference grant proposals in their portfolios.</p> <p>Often, researchers drive research topics, agendas, and ultimately, outcomes. Inclusivity should span the range of research processes, including giving voice and autonomy to important constituents, invested parties and partners, including SWD themselves and parents/families of SWDs, when developing instructional practices and/or preventative/remedial interventions and drawing on multiple methodologies. In recent years, educational psychology has been a leader in the promotion and use of mixed methods research to use multiple data sources and methods to understand complex phenomena (Clark, [<reflink idref="bib32" id="ref157">32</reflink>]; McCrudden et al., [<reflink idref="bib82" id="ref158">82</reflink>]; Meyer &amp; Schutz, [<reflink idref="bib87" id="ref159">87</reflink>]; Urdan, [<reflink idref="bib124" id="ref160">124</reflink>]). Ensuring that the voices are heard, highlighted, and celebrated in the context of educational psychology and special education research at each stage of the incremental science process (and not simply at the efficacy or testing phase) can ensure better fit, more directly alignment to priorities, needs, and goals, and potentially have more impact improving longer-term outcomes for SWDs, their families, and communities.</p> <p>The number of "successful" interventions, whether at the pilot or promise stage, to the larger scale efficacy and effectiveness trials, can only be realized if the outcomes of the experimental, controlled contexts can deliver impacts to real-world contexts. There is a necessary focus on implementation and sustainment in ensuring equity and access to effective interventions for all students, educators, and families. This is important broadly but may be particularly important in the context of diverse populations, including SWDs, to ensure equitable access to instruction and opportunities in school settings and beyond. More research that includes measurement and careful monitoring of variables and mechanisms associated with the uptake, implementation, and sustainment of effective practices is needed, and can provide early indicators, including early warning signs of lack of adoption of lack of effects, that can help improve the efficiency of intervention development. This may be particularly important in the context of supporting SWDs in inclusive educational environments, where several policies and structures overlap to ensure education and access such as the general education curriculum, school structure (programming structure and physical building structure), special education service delivery including individualized education program (IEP) development, monitoring, and implementation, and the healthcare system that provides important services and therapies in and outside of school contexts. As such, research should prioritize measures of use, feasibility, implementation, and sustainment of programs, practices, and policies within the community and other real-world settings as key indicator of success.</p> <p>One final comment is that we recognize the scale of some of the successful examples of using the incremental science approach, not only in terms of the scale and cost of the research activities, but also the time it takes to develop, test, refine, and evaluate interventions and programs over the course of careers and teams of motivated individuals. This should encourage interdisciplinary collaboration and also be viewed as a framework for researchers and groups that may not have the required resources to implement all stages can focus on specific stages within a larger, collaborative program of research. We view these examples as helpful illustrations of how researchers can place themselves and their work within a framework that has the overarching goal of inclusive, individual differences research that can also address complex, structural issues in education.</p> <hd id="AN0186160233-18">Conclusions</hd> <p>Our goal for this contribution to the special issue was to overview an incremental science approach and shed light on ways that special education research is aligned with psychological science through the history of individual differences and the opportunity to address complex, structural challenges in education. A focus on developing and engaging in an incremental science approach, through the lens of inclusivity, can advance theory development and research methods in educational psychology while also improving the scope, reach, and depth of special education research. By design, special education as a field emerged to address aspects of human diversity that were not yet being met by society. Through interdisciplinarity, leveraging the strengths and experiences of multiple research communities, epistemologies, and methodologies may be a key factor in improving and maintaining successful outcomes for students with disabilities, their educators, and their families and communities.</p> <hd id="AN0186160233-19">Disclosure statement</hd> <p>No potential conflict of interest was reported by the author(s).</p> <ref id="AN0186160233-20"> <title> References </title> <blist> <bibl id="bib1" idref="ref15" type="bt">1</bibl> <bibtext> Alexander, P. A., &amp; Winne, P. H. (2012). Handbook of educational psychology. Routledge.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref16" type="bt">2</bibl> <bibtext> Anderson, A., Hattie, J., &amp; Hamilton, R. J. (2005). Locus of control, self-efficacy, and motivation in different schools: Is moderation the key to success? Educational Psychology, 25 (5), 517 – 535. https://doi.org/10.1080/01443410500046754</bibtext> </blist> <blist> <bibl id="bib3" idref="ref17" type="bt">3</bibl> <bibtext> Annamma, S. A., Connor, D., &amp; Ferri, B. (2013). Dis/ability critical race studies (DisCrit): Theorizing at the intersections of race and dis/ability. Race Ethnicity and Education, 16 (1), 1 – 31. https://doi.org/10.1080/13613324.2012.730511</bibtext> </blist> <blist> <bibl id="bib4" idref="ref20" type="bt">4</bibl> <bibtext> Annamma, S. A., Ferri, B. A., &amp; Connor, D. J. (2018). Disability critical race theory: Exploring the intersectional lineage, emergence, and potential futures of DisCrit in education. Review of Research in Education, 42 (1), 46 – 71. https://doi.org/10.3102/0091732X18759041</bibtext> </blist> <blist> <bibl id="bib5" idref="ref125" type="bt">5</bibl> <bibtext> Artiles, A. J. (2011). Toward an interdisciplinary understanding of educational equity and difference: The case of the racialization of ability. Educational Researcher, 40 (9), 431 – 445. https://doi.org/10.3102/0013189X11429391</bibtext> </blist> <blist> <bibl id="bib6" idref="ref88" type="bt">6</bibl> <bibtext> Bakeman, R., &amp; Quera, V. (2011). Sequential analysis and observational methods for the behavioral sciences. Cambridge University Press.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref133" type="bt">7</bibl> <bibtext> Bal, A., &amp; Trainor, A. A. (2016). Culturally responsive experimental intervention studies: The development of a rubric for paradigm expansion. World Yearbook of Education, 237 – 277.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref14" type="bt">8</bibl> <bibtext> Beets, M. W., von Klinggraeff, L., Weaver, R. G., Armstrong, B., &amp; Burkart, S. (2021). Small studies, big decisions: The role of pilot/feasibility studies in incremental science and premature scale-up of behavioral interventions. Pilot and Feasibility Studies, 7 (1), 173. https://doi.org/10.1186/s40814-021-00909-w</bibtext> </blist> <blist> <bibl id="bib9" idref="ref35" type="bt">9</bibl> <bibtext> Bierman, K. L., Nix, R. L., Greenberg, M. T., Blair, C., &amp; Domitrovich, C. E. (2008). Executive functions and school readiness intervention: Impact, moderation, and mediation in the Head Start REDI program. Development and Psychopathology, 20 (3), 821 – 843. https://doi.org/10.1017/S0954579408000394</bibtext> </blist> <blist> <bibtext> Boveda, M., &amp; Aronson, B. A. (2019). Special education preservice teachers, intersectional diversity, and the privileging of emerging professional identities. Remedial and Special Education, 40 (4), 248 – 260. https://doi.org/10.1177/0741932519838621</bibtext> </blist> <blist> <bibtext> Bowman, K. S., Tereshko, L., Marshall, K. B., Weiss, M. J., &amp; Rose, K. (2024). The Perceptions and Experiences of Professionals Collaborating with Behavior Analysts. Journal of Behavioral Education, 2024, 1 – 26. https://doi.org/10.1007/s10864-023-09542-4</bibtext> </blist> <blist> <bibtext> Bradley, M. M. (2017). The science pendulum: From programmatic to incremental—and back? Psychophysiology, 54 (1), 6 – 11. https://doi.org/10.1111/psyp.12608</bibtext> </blist> <blist> <bibtext> Broda, M. D., Granger, K., Chow, J., &amp; Ross, E. (2023). Using social network analysis in applied psychological research: A tutorial. Psychological Methods, 28 (4), 791 – 805. https://doi.org/10.1037/met0000451</bibtext> </blist> <blist> <bibtext> Bronfenbrenner, U. (1986). Recent advances in research on the ecology of human development. In R. K. Silbereisen, K. Eyferth, &amp; G. Rudinger (Eds.), Development as action in context. Springer. https://doi.org/10.1007/978-3-662-02475-1_15</bibtext> </blist> <blist> <bibtext> Bronfenbrenner, U. (2000). Ecological systems theory. Oxford University Press.</bibtext> </blist> <blist> <bibtext> Brown, C. H., Ten Have, T. R., Jo, B., Dagne, G., Wyman, P. A., Muthén, B., &amp; Gibbons, R. D. (2009). Adaptive designs for randomized trials in public health. Annual Review of Public Health, 30 (1), 1 – 25. https://doi.org/10.1146/annurev.publhealth.031308.100223</bibtext> </blist> <blist> <bibtext> Clarke, B., Doabler, C. T., Smolkowski, K., Turtura, J., Kosty, D., Kurtz-Nelson, E., Fien, H., &amp; Baker, S. K. (2019). Exploring the Relationship Between Initial Mathematics Skill and a Kindergarten Mathematics Intervention. Exceptional Children, 85 (2), 129 – 146. https://doi.org/10.1177/0014402918799503</bibtext> </blist> <blist> <bibtext> Collins, L. M., Murphy, S. A., &amp; Strecher, V. (2007). The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): New methods for more potent eHealth interventions. American Journal of Preventive Medicine, 32 (5 Suppl), S112 – S118. https://doi.org/10.1016/j.amepre.2007.01.022</bibtext> </blist> <blist> <bibtext> Connor, C. M., Morrison, F. J., &amp; Underwood, P. S. (2007). A second chance in second grade: The independent and cumulative impact of first-and second-grade reading instruction and students' letter-word reading skill growth. Scientific Studies of Reading, 11 (3), 199 – 233. https://doi.org/10.1080/10888430701344314</bibtext> </blist> <blist> <bibtext> Conroy, M. A., Sutherland, K. S., Algina, J. J., Wilson, R. E., Martinez, J. R., &amp; Whalon, K. J. (2015). Measuring teacher implementation of the BEST in CLASS intervention program and corollary child outcomes. Journal of Emotional and Behavioral Disorders, 23 (3), 144 – 155. https://doi.org/10.1177/1063426614532949</bibtext> </blist> <blist> <bibtext> Chorpita, B. F., Daleiden, E. L., &amp; Weisz, J. R. (2005). Identifying and selecting the common elements of evidence based interventions: A distillation and matching model. Mental Health Services Research, 7 (1), 5 – 20. https://doi.org/10.1007/s11020-005-1962-6</bibtext> </blist> <blist> <bibtext> Chow, J. C. (2020). Commentary–Classroom motivation and learning disabilities: Consensus points and recommendations. Learning Disabilities: A Multidisciplinary Journal, 25 (2), 54 – 60.</bibtext> </blist> <blist> <bibtext> Chow, J. C. (2023). Collaboration to support language and learning outcomes for students with disabilities. Intervention in School and Clinic, 58 (3), 143 – 145. https://doi.org/10.1177/10534512221081263</bibtext> </blist> <blist> <bibtext> Chow, J. C., Cunningham, J. E., &amp; Wallace, E. S. (2020). Interaction-centered model of language and behavioral development. In Handbook of research on emotional and behavioral disorders. (pp. 83 – 95). Routledge.</bibtext> </blist> <blist> <bibtext> Chow, J. C., &amp; Hampton, L. H. (2019). Sequential multiple-assignment randomized trials: Developing and evaluating adaptive interventions in special education. Remedial and Special Education, 40 (5), 267 – 276. https://doi.org/10.1177/0741932518759422</bibtext> </blist> <blist> <bibtext> Chow, J. C., &amp; Hampton, L. H. (2022). A systematic review of sequential multiple-assignment randomized trials in educational research. Educational Psychology Review, 34 (3), 1343 – 1369. https://doi.org/10.1007/s10648-022-09660-x</bibtext> </blist> <blist> <bibtext> Chow, J. C., &amp; Lindström, E. R. (2022). Leveraging Moderation and Mediation to Examine Individual Differences in Special Education Research. In Handbook of Special Education Research, Volume I. (pp. 158 – 170). Routledge.</bibtext> </blist> <blist> <bibtext> Chow, J. C., &amp; Wehby, J. H. (2019). Effects of symbolic and nonsymbolic equal-sign intervention in second-grade classrooms. The Elementary School Journal, 119 (4), 677 – 702. https://doi.org/10.1086/703086</bibtext> </blist> <blist> <bibtext> Chung, P. &amp; Liu. (2025). The effects of daily air pollution on students and teachers. NBER Working Paper Series. Working Paper No. 33549. <ulink href="http://www.nber.org/papers/w33549">http://www.nber.org/papers/w33549</ulink></bibtext> </blist> <blist> <bibtext> Cipriano, C., Naples, L. H., Eveleigh, A., Cook, A., Funaro, M., Cassidy, C., McCarthy, M. F., &amp; Rappolt-Schlichtmann, G. (2023). A systematic review of student disability and race representation in universal school-based social and emotional learning interventions for elementary school students. Review of Educational Research, 93 (1), 73 – 102. https://doi.org/10.3102/00346543221094079</bibtext> </blist> <blist> <bibtext> Cipriano, C., Strambler, M. J., Naples, L. H., Ha, C., Kirk, M., Wood, M., Sehgal, K., Zieher, A. K., Eveleigh, A., McCarthy, M., Funaro, M., Ponnock, A., Chow, J. C., &amp; Durlak, J. (2023). The state of evidence for social and emotional learning: A contemporary meta-analysis of universal school-based SEL interventions. Child Development, 94 (5), 1181 – 1204. https://doi.org/10.1111/cdev.13968</bibtext> </blist> <blist> <bibtext> Clark, V. L. P. (2019). Meaningful integration within mixed methods studies: Identifying why, what, when, and how. Contemporary Educational Psychology, 57, 106 – 111.</bibtext> </blist> <blist> <bibtext> Coyne, M. D., Oldham, A., Dougherty, S. M., Leonard, K., Koriakin, T., Gage, N. A., Burns, D., &amp; Gillis, M. (2018). Evaluating the effects of supplemental reading intervention within an MTSS or RTI reading reform initiative using a regression discontinuity design. Exceptional Children, 84 (4), 350 – 367. https://doi.org/10.1177/0014402918772791</bibtext> </blist> <blist> <bibtext> Cumming, M. M., Bettini, E., &amp; Chow, J. C. (2023). High-quality systematic literature reviews in special education: Promoting coherence, contextualization, generativity, and transparency. Exceptional Children, 89 (4), 412 – 431. https://doi.org/10.1177/00144029221146576</bibtext> </blist> <blist> <bibtext> Cunningham, J. E., Chow, J. C., Meeker, K. A., Taylor, A., Hemmeter, M. L., &amp; Kaiser, A. P. (2023). A conceptual model for a blended intervention approach to support early language and social-emotional development in toddler classrooms. Infants &amp; Young Children, 36 (1), 53 – 73. https://doi.org/10.1097/IYC.0000000000000232</bibtext> </blist> <blist> <bibtext> Deci, E. L., &amp; Ryan, R. M. (2012). Self-determination theory. Handbook of Theories of Social Psychology, 1 (20), 416 – 436.</bibtext> </blist> <blist> <bibtext> DeCuir-Gunby, J. T., &amp; Schutz, P. A. (2014). Researching race within educational psychology contexts. Educational Psychologist, 49 (4), 244 – 260. https://doi.org/10.1080/00461520.2014.957828</bibtext> </blist> <blist> <bibtext> Deno, S. L. (1990). Individual differences and individual difference: The essential difference of special education. The Journal of Special Education, 24 (2), 160 – 173. https://doi.org/10.1177/002246699002400205</bibtext> </blist> <blist> <bibtext> Emery, A., Louick, R. A., &amp; Sabrowsky, J. (2022). Moving beyond the ableist roots of educational psychology: Audit of the field and a path forward. Educational Psychology Review, 34 (3), 1517 – 1540. https://doi.org/10.1007/s10648-022-09673-6</bibtext> </blist> <blist> <bibtext> Erevelles, N., &amp; Minear, A. (2010). Unspeakable offenses: Untangling race and disability in discourses of intersectionality. Journal of Literary &amp; Cultural Disability Studies, 4 (2), 127 – 145. https://doi.org/10.3828/jlcds.2010.11</bibtext> </blist> <blist> <bibtext> Farrell, A. D., Sullivan, T. N., Sutherland, K. S., Corona, R., &amp; Masho, S. (2018). Evaluation of the Olweus Bully Prevention Program in an urban school system in the USA. Prevention Science, 19 (6), 833 – 847. https://doi.org/10.1007/s11121-018-0923-4</bibtext> </blist> <blist> <bibtext> Fielding, N. G. (2012). Triangulation and mixed methods designs: Data integration with new research technologies. Journal of Mixed Methods Research, 6 (2), 124 – 136. https://doi.org/10.1177/1558689812437101</bibtext> </blist> <blist> <bibtext> Fuchs, D., &amp; Fuchs, L. S. (2019). On the Importance of Moderator Analysis in Intervention Research: An Introduction to the Special Issue. Exceptional Children, 85 (2), 126 – 128. https://doi.org/10.1177/0014402918811924</bibtext> </blist> <blist> <bibtext> Fuchs, L. S., Fuchs, D., &amp; Gilbert, J. K. (2019). Does the Severity of Students' Pre-Intervention Math Deficits Affect Responsiveness to Generally Effective First-Grade Intervention? Exceptional Children, 85 (2), 147 – 162. https://doi.org/10.1177/0014402918782628</bibtext> </blist> <blist> <bibtext> Fuchs, L. S., Schumacher, R. F., Sterba, S. K., Long, J., Namkung, J., Malone, A., Hamlett, C. L., Jordan, N. C., Gersten, R., Siegler, R. S., &amp; Changas, P. (2014). Does working memory moderate the effects of fraction intervention? An aptitude–treatment interaction. Journal of Educational Psychology, 106 (2), 499 – 514. https://doi.org/10.1037/a0034341</bibtext> </blist> <blist> <bibtext> García, S. B., &amp; Ortiz, A. A. (2013). Intersectionality as a framework for transformative research in special education. Multiple Voices for Ethnically Diverse Exceptional Learners, 13 (2), 32 – 47. https://doi.org/10.56829/muvo.13.2.yv7822w58116kw42</bibtext> </blist> <blist> <bibtext> Garon-Carrier, G., Boivin, M., Lemelin, J.-P., Kovas, Y., Parent, S., Séguin, J. R., Vitaro, F., Tremblay, R. E., &amp; Dionne, G. (2018). Early developmental trajectories of number knowledge and math achievement from 4 to 10 years: Low-persistent profile and early-life predictors. Journal of School Psychology, 68, 84 – 98. https://doi.org/10.1016/j.jsp.2018.02.004</bibtext> </blist> <blist> <bibtext> Geldhof, G. J., Fenn, M. L., &amp; Finders, J. K. (2017). A self-determination perspective on self-regulation across the life span. In M. L. Wehmeyer, K. A. Shogren, T. Little, &amp; S. Lopez (Eds.) Development of self-determination through the life-course (pp. 221 – 235). Springer.</bibtext> </blist> <blist> <bibtext> Gilmour, A. F., Fuchs, D., &amp; Wehby, J. H. (2019). Are students with disabilities accessing the curriculum? A meta-analysis of the reading achievement gap between students with and without disabilities. Exceptional Children, 85 (3), 329 – 346. https://doi.org/10.1177/0014402918795830</bibtext> </blist> <blist> <bibtext> Glass, G. V. (1983). Effectiveness of special education. Policy Studies Review, 2 (1), 65 – 78.</bibtext> </blist> <blist> <bibtext> Granger, K. L., &amp; Chow, J. C. (2025). Classroom carrying capacity: A resource and limiting factors framework. Educational Psychology Review, 37 (1), 99. https://doi.org/10.1007/s10648-025-09999-x</bibtext> </blist> <blist> <bibtext> Graham, S., Harris, K. R., &amp; McKeown, D. (2013). The effectiveness of SRSD for teaching writing to students with learning disabilities: A meta-analysis. Exceptional Children, 80 (4), 454 – 473.</bibtext> </blist> <blist> <bibtext> Graham, S., McKeown, D., Kiuhara, S., &amp; Harris, K. R. (2012). A meta-analysis of writing instruction for students in the elementary grades. Journal of Educational Psychology, 104 (4), 879 – 896. https://doi.org/10.1037/a0029185</bibtext> </blist> <blist> <bibtext> Greenwood, C. R. (1996). The case for performance-based instructional models. School Psychology Quarterly, 11 (4), 283 – 296. https://doi.org/10.1037/h0088935</bibtext> </blist> <blist> <bibtext> Hampton, L. H., &amp; Chow, J. C. (2022). Deeply tailoring adaptive interventions: Enhancing knowledge generation of SMARTs in special education. Remedial and Special Education, 43 (3), 195 – 205. https://doi.org/10.1177/07419325211030669</bibtext> </blist> <blist> <bibtext> Harris, K. R. (2024). The self-regulated strategy development instructional model: Efficacious theoretical integration, scaling up, challenges, and future research. Educational Psychology Review, 36 (4), 104. https://doi.org/10.1007/s10648-024-09921-x</bibtext> </blist> <blist> <bibtext> Harris, K. R., &amp; Graham, S. (1996). Making the writing process work: Strategies for composition and self-regulation. Brookline Books.</bibtext> </blist> <blist> <bibtext> Harris, K. R., Graham, S., Mason, L., &amp; Friedlander, B. (2008). Powerful writing strategies for all students. Brookes Publishing Co.</bibtext> </blist> <blist> <bibtext> Hernández-Saca, D. I., Gutmann Kahn, L., &amp; Cannon, M. A. (2018). Intersectionality dis/ability research: How dis/ability research in education engages intersectionality to uncover the multidimensional construction of dis/abled experiences. Review of Research in Education, 42 (1), 286 – 311. https://doi.org/10.3102/0091732X18762439</bibtext> </blist> <blist> <bibtext> Hollo, A., &amp; Chow, J. (2015). Communicative functions of problem behavior for students with high-incidence disabilities. Beyond Behavior, 24 (3), 23 – 30. https://doi.org/10.1177/107429561502400304</bibtext> </blist> <blist> <bibtext> Hopwood, C. J. (2007). Moderation and mediation in structural equation modeling: Applications for early intervention research. Journal of Early Intervention, 29 (3), 262 – 272. https://doi.org/10.1177/105381510702900305</bibtext> </blist> <blist> <bibtext> Hunsley, J., &amp; Lee, C. M. (2007). informed benchmarks for psychological treatments: Efficacy studies, effectiveness studies, and beyond. Professional Psychology: Research and Practice, 38 (1), 21 – 33. https://doi.org/10.1037/0735-7028.38.1.21</bibtext> </blist> <blist> <bibtext> Isaacson, K. L. (2022). Implications for cross-training between applied behavior analysis and speech-language pathology [Graduate studies thesis]. University of New Mexico. University of New Mexico Research Repository.</bibtext> </blist> <blist> <bibtext> Kazdin, A. E. (2011). Single-case research designs: Methods for clinical and applied settings (2nd ed.). Oxford University Press.</bibtext> </blist> <blist> <bibtext> Koenka, A. C. (2020). Academic motivation theories revisited: An interactive dialog between motivation scholars on recent contributions, underexplored issues, and future directions. Contemporary Educational Psychology, 61, 101831. https://doi.org/10.1016/j.cedpsych.2019.101831</bibtext> </blist> <blist> <bibtext> Klette, K. (2023). Towards programmatic research when studying classroom teaching and learning. In Didactics in a changing world: European perspectives on teaching, learning and the curriculum (pp. 137 – 158). Springer International Publishing.</bibtext> </blist> <blist> <bibtext> Kwon, K. (2024). A systematic review of the evaluation in K-12 artificial intelligence education from 2013 to 2022. Interactive Learning Environments, 2024, 1 – 29.</bibtext> </blist> <blist> <bibtext> Lane, J. D., &amp; Brown, J. A. (2023). Child communication research and practice: Collaborative roles for behavior analysts and speech-language pathologists. Policy Insights from the Behavioral and Brain Sciences, 10 (1), 104 – 112. https://doi.org/10.1177/23727322221144652</bibtext> </blist> <blist> <bibtext> Landrum, T. J., Cook, B. G., &amp; Tankersley, M. (Eds.) (2018). Emerging research and issues in behavioral disabilities.</bibtext> </blist> <blist> <bibtext> Larson, J. E. (2009). Educational psychology: Cognition and learning, individual differences and motivation.</bibtext> </blist> <blist> <bibtext> Lau, A. S., Huey, S. J., Jr, &amp; Baumann, A. A. (2023). Advances in the adaptation and implementation of evidence-based interventions for historically marginalized groups. Behaviour Research and Therapy, 168, 104377. https://doi.org/10.1016/j.brat.2023.104377</bibtext> </blist> <blist> <bibtext> Larson, A. L., Cycyk, L. M., Carta, J. J., Hammer, C. S., Baralt, M., Uchikoshi, Y., An, Z. G., &amp; Wood, C. (2020). A systematic review of language-focused interventions for young children from culturally and linguistically diverse backgrounds. Early Childhood Research Quarterly, 50, 157 – 178. https://doi.org/10.1016/j.ecresq.2019.06.001</bibtext> </blist> <blist> <bibtext> Ledford, J.R., &amp; Gast, D.L. (Eds.) (2024). Single case research methodology: Applications in special education and behavioral sciences (4th ed.). Routledge. https://doi.org/10.4324/9781003294726</bibtext> </blist> <blist> <bibtext> Ledford, J. R., King, S., Harbin, E. R., &amp; Zimmerman, K. N. (2018). Antecedent social skills interventions for individuals with ASD: What works, for whom, and under what conditions? Focus on Autism and Other Developmental Disabilities, 33 (1), 3 – 13. https://doi.org/10.1177/1088357616634024</bibtext> </blist> <blist> <bibtext> Leon, A. C., Davis, L. L., &amp; Kraemer, H. C. (2011). The role and interpretation of pilot studies in clinical research. Journal of Psychiatric Research, 45 (5), 626 – 629. https://doi.org/10.1016/j.jpsychires.2010.10.008</bibtext> </blist> <blist> <bibtext> Letcher, P., Smart, D., Sanson, A., &amp; Toumbourou, J. W. (2009). Psychosocial precursors and correlates of differing internalizing trajectories from 3 to 15 years 1. Social Development, 18 (3), 618 – 646. https://doi.org/10.1111/j.1467-9507.2008.00500.x</bibtext> </blist> <blist> <bibtext> Lloyd, B. P., &amp; Wehby, J. H. (2018). Developing direct observation systems to measure classroom behavior for students with behavioral disabilities. In Emerging research and issues in behavioral disabilities (Vol. 30, pp. 9 – 27). Emerald Publishing Limited.</bibtext> </blist> <blist> <bibtext> Lombardi, A., Chow, J., Cook, B. G., Scott, L., Root, J., &amp; Fleming, J. I. (2025). Prioritizing preregistration in special education research. Research in Special Education, 2, 1–15. https://doi.org/10.25894/rise.2643</bibtext> </blist> <blist> <bibtext> Ly, A., &amp; Boll, L. (2024). Navigating Special Education Relationships: Building Collective Efficacy for a Collaborative Team. Taylor &amp; Francis.</bibtext> </blist> <blist> <bibtext> Martens, B. K., DiGennaro, F. D., Reed, D. D., Szczech, F. M., &amp; Rosenthal, B. D. (2008). Contingency space analysis: An alternative method for identifying contingent relations from observational data. Journal of Applied Behavior Analysis, 41 (1), 69 – 81. https://doi.org/10.1901/jaba.2008.41-69</bibtext> </blist> <blist> <bibtext> Matthews, J. S., &amp; López, F. (2020). Race-reimaging educational psychology research: Investigating constructs through the lens of race and culture. Contemporary Educational Psychology, 61, 101878. https://doi.org/10.1016/j.cedpsych.2020.101878</bibtext> </blist> <blist> <bibtext> McCrudden, M. T., Marchand, G., &amp; Schutz, P. (2019). Mixed methods in educational psychology inquiry. Contemporary Educational Psychology, 57, 1 – 8. https://doi.org/10.1016/j.cedpsych.2019.01.008</bibtext> </blist> <blist> <bibtext> McInerney, D. M. (2005). Educational psychology – Theory, research, and teaching: A 25-year retrospective. Educational Psychology, 25 (6), 585 – 599. https://doi.org/10.1080/01443410500344670</bibtext> </blist> <blist> <bibtext> Mehari, K. R., Smith, P. N., Morton, B. C., Billingsley, J. L., Coleman, J. N., &amp; Farrell, A. D. (2024). Challenges in evaluating a community-level intervention to address root causes of youth violence. Prevention Science, 25 (5), 774 – 785. https://doi.org/10.1007/s11121-024-01678-7</bibtext> </blist> <blist> <bibtext> Meirink, J. A., Imants, J., Meijer, P. C., &amp; Verloop, N. (2010). Teacher learning and collaboration in innovative teams. Cambridge Journal of Education, 40 (2), 161 – 181. https://doi.org/10.1080/0305764X.2010.481256</bibtext> </blist> <blist> <bibtext> Mertens, D. M. (2019). Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods. Sage Publications.</bibtext> </blist> <blist> <bibtext> Meyer, D. K., &amp; Schutz, P. A. (2020). Why talk about qualitative and mixed methods in educational psychology? Introduction to special issue. Educational Psychologist, 55 (4), 193 – 196. https://doi.org/10.1080/00461520.2020.1796671</bibtext> </blist> <blist> <bibtext> Moore, C. G., Carter, R. E., Nietert, P. J., &amp; Stewart, P. W. (2011). Recommendations for planning pilot studies in clinical and translational research. Clinical and Translational Science, 4 (5), 332 – 337. https://doi.org/10.1111/j.1752-8062.2011.00347.x</bibtext> </blist> <blist> <bibtext> Murnane, R. J., &amp; Willett, J. B. (2010). Methods matter: Improving causal inference in educational and social science research. Oxford University Press.</bibtext> </blist> <blist> <bibtext> National Academies of Sciences, Engineering, and Medicine. (2022). The Future of Education Research at IES: Advancing an Equity-Oriented Science. The National Academies Press. https://doi.org/10.17226/26428</bibtext> </blist> <blist> <bibtext> National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. (2005). Facilitating interdisciplinary research. The National Academies Press. https://doi.org/10.17226/11153</bibtext> </blist> <blist> <bibtext> National Center for Education Statistics. (2023). Students With Disabilities. Condition of Education. U.S. Department of Education, Institute of Education Sciences.</bibtext> </blist> <blist> <bibtext> National Center for Education Statistics. National Assessment of Educational Progress (Project), Educational Testing Service., &amp; United States. (2022). NAEP 2020 and 2022 Long-Term Trend (LTT) Reading and Mathematics Assessments. Washington, D.C : National Center for Education Statistics, Office of Educational Research and Improvement, U.S. Dept. of Education. https://<ulink href="http://www.nationsreportcard.gov/highlights/ltt/2022/">www.nationsreportcard.gov/highlights/ltt/2022/</ulink></bibtext> </blist> <blist> <bibtext> Pellegrino, J. W., &amp; Glaser, R. (1979). Cognitive correlates and components in the analysis of individual differences. Intelligence, 3 (3), 187 – 215. https://doi.org/10.1016/0160-2896(79)90017-5</bibtext> </blist> <blist> <bibtext> Peredo, T. N., Zelaya, M. I., &amp; Kaiser, A. P. (2018). Teaching low-income Spanish-speaking caregivers to implement EMT en Español with their young children with language impairment: A pilot study. American Journal of Speech-Language Pathology, 27 (1), 136 – 153. https://doi.org/10.1044/2017_AJSLP-16-0228</bibtext> </blist> <blist> <bibtext> Pfledderer, C. D., von Klinggraeff, L., Burkart, S., da Silva Bandeira, A., Lubans, D. R., Jago, R., Okely, A. D., van Sluijs, E. M. F., Ioannidis, J. P. A., Thrasher, J. F., Li, X., &amp; Beets, M. W. (2024). Consolidated guidance for behavioral intervention pilot and feasibility studies. Pilot and Feasibility Studies, 10 (1), 57. https://doi.org/10.1186/s40814-24-01485-5</bibtext> </blist> <blist> <bibtext> Preacher, K. J., &amp; Sterba, S. K. (2019). Aptitude-by-treatment interactions in research on educational interventions. Exceptional Children, 85 (2), 248 – 264. https://doi.org/10.1177/0014402918802803</bibtext> </blist> <blist> <bibtext> Roberts, M. Y., &amp; Kaiser, A. P. (2015). Early intervention for toddlers with language delays: A randomized controlled trial. Pediatrics, 135 (4), 686 – 693. https://doi.org/10.1542/peds.2014-2134</bibtext> </blist> <blist> <bibtext> Roberts, M. Y., Kaiser, A. P., Wolfe, C. E., Bryant, J. D., &amp; Spidalieri, A. M. (2014). Effects of the teach-model-coach-review instructional approach on caregiver use of language support strategies and children's expressive language skills. Journal of Speech, Language, and Hearing Research: JSLHR, 57 (5), 1851 – 1869. https://doi.org/10.1044/2014_JSLHR-L-13-0113</bibtext> </blist> <blist> <bibtext> Ryan, R. M., &amp; Deci, E. L. (2002). Overview of self-determination theory: An organismic dialectical perspective. Handbook of Self-Determination Research, 2, 3 – 33.</bibtext> </blist> <blist> <bibtext> Scheerenberger, R. C. (1983). A history of mental retardation.</bibtext> </blist> <blist> <bibtext> Sells, S. P., Smith, T. E., &amp; Sprenkle, D. H. (1995). Integrating qualitative and quantitative research methods: A research model. Family Process, 34 (2), 199 – 218. https://doi.org/10.1111/j.1545-5300.1995.00199.x</bibtext> </blist> <blist> <bibtext> Shiffman, S., Stone, A. A., &amp; Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4 (1), 1 – 32. https://doi.org/10.1146/annurev.clinpsy.3.022806.091415</bibtext> </blist> <blist> <bibtext> Shogren, K. A., Wehmeyer, M. L., &amp; Palmer, S. B. (2017). Causal agency theory. In M. Wehmeyer, K. Shogren, T. Little, &amp; S. Lopez (Eds.), Development of self-determination through the life-course. Springer. https://doi.org/10.1007/978-94-024-1042-6_5</bibtext> </blist> <blist> <bibtext> Shogren, K. A., &amp; Raley, S. K. (2022). Causal agency theory: Defining self-determined actions. In K. A. Shogren &amp; S. K. Raley (Eds.), Self-determination and causal agency theory: Integrating research into practice. (pp. 37 – 52). Springer.</bibtext> </blist> <blist> <bibtext> Schutz, P. A., &amp; Muis, K. R. (2024). An introduction to the handbook of educational psychology. In Handbook of Educational Psychology (pp. 3 – 12). Routledge.</bibtext> </blist> <blist> <bibtext> Simonsen, B., Fairbanks, S., Briesch, A., Myers, D., &amp; Sugai, G. (2008). Evidence-based practices in classroom management: Considerations for research to practice. Education and Treatment of Children, 31 (3), 351 – 380.</bibtext> </blist> <blist> <bibtext> Smith, C. A. (2019). The uses of pilot studies in sociology: A processual understanding of preliminary research. The American Sociologist, 50 (4), 589 – 607. https://doi.org/10.1007/s12108-019-09419-y</bibtext> </blist> <blist> <bibtext> Snow, R. E. (1977). Individual differences and instructional theory. Educational Researcher, 6 (10), 11 – 15. https://doi.org/10.2307/1174235</bibtext> </blist> <blist> <bibtext> Snow, R. E. (1980). Aptitude, learner control, and adaptive instruction. Educational Psychologist, 15 (3), 151 – 158. https://doi.org/10.1080/00461528009529223</bibtext> </blist> <blist> <bibtext> Speece, D. L. (1990). Aptitude-treatment interactions: Bad rap or bad idea? The Journal of Special Education, 24 (2), 139 – 149. https://doi.org/10.1177/002246699002400203</bibtext> </blist> <blist> <bibtext> Staubitz, J. L., &amp; Lloyd, B. P. (2016). Beyond ABC data: A tutorial for measuring contingencies in the classroom. Beyond Behavior, 25 (3), 17 – 26. https://doi.org/10.1177/107429561602500304</bibtext> </blist> <blist> <bibtext> Strowig, R. W., &amp; Farwell, G. F. (1966). Programmatic research. Review of Educational Research, 36 (2), 327 – 334. Chapter X https://doi.org/10.2307/1169503</bibtext> </blist> <blist> <bibtext> Sullivan, T. N., Farrell, A. D., Sutherland, K. S., Behrhorst, K. L., Garthe, R. C., &amp; Greene, A. (2021). Evaluation of the Olweus Bullying Prevention Program in US urban middle schools using a multiple baseline experimental design. Prevention Science, 22 (8), 1134 – 1146. https://doi.org/10.1007/s11121-021-01244-5</bibtext> </blist> <blist> <bibtext> Sutherland, K. S., Conroy, M. A., Algina, J., Ladwig, C., Jessee, G., &amp; Gyure, M. (2018). Reducing child problem behaviors and improving teacher-child interactions and relationships: A randomized controlled trial of BEST in CLASS. Early Childhood Research Quarterly, 42, 31 – 43. https://doi.org/10.1016/j.ecresq.2017.08.001</bibtext> </blist> <blist> <bibtext> Tefera, A. A., Artiles, A. J., Kramarczuk Voulgarides, C., Aylward, A., &amp; Alvarado, S. (2023). The aftermath of disproportionality citations: Situating disability-race intersections in historical, spatial, and sociocultural contexts. American Educational Research Journal, 60 (2), 367 – 404. https://doi.org/10.3102/00028312221147007</bibtext> </blist> <blist> <bibtext> Tefera, A. A., &amp; Fischman, G. E. (2024). Beyond good intentions in special education policy: Engaging With critical disability intersectional research. Qualitative Inquiry, 30 (1), 48 – 58. https://doi.org/10.1177/10778004231165461</bibtext> </blist> <blist> <bibtext> Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L. P., Robson, R., Thabane, M., Giangregorio, L., &amp; Goldsmith, C. H. (2010). A tutorial on pilot studies: The what, why and how. BMC Medical Research Methodology, 10 (1), 1 – 10. https://doi.org/10.1186/1471-2288-10-1</bibtext> </blist> <blist> <bibtext> Toste, J. R., Logan, J. A., Shogren, K. A., &amp; Boyd, B. A. (2023). The next generation of quality indicators for group design research in special education. Exceptional Children, 89 (4), 359 – 378. https://doi.org/10.1177/00144029221150801</bibtext> </blist> <blist> <bibtext> U.S. Census Bureau. (n.d.). Disability characteristics. U.S. Department of Commerce.</bibtext> </blist> <blist> <bibtext> U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance (NAEP). What Works Clearinghouse.</bibtext> </blist> <blist> <bibtext> U.S. Department of Education. Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP). (2024). Reading assessment.</bibtext> </blist> <blist> <bibtext> Underwood, B. J. (1975). Individual differences as a crucible in theory construction. American Psychologist, 30 (2), 128 – 134. https://doi.org/10.1037/h0076759</bibtext> </blist> <blist> <bibtext> Urdan, T. (2022). Mixed-methods research in educational psychology: Opportunities and costs. Routledge.</bibtext> </blist> <blist> <bibtext> Volkers, N. (2018). When SLP meets ABA: A deeper understanding of the underpinnings of ABA and speech-language pathology approaches to autism may clarify tensions – and, perhaps, offer potential for reconciliation. The ASHA Leader, 23 (12), 44 – 53. https://doi.org/10.1044/leader.FTR1.23122018.44</bibtext> </blist> <blist> <bibtext> Wallis, S. E. (2014). Existing and emerging methods for integrating theories within and between disciplines. Journal of Organisational Transformation &amp; Social Change, 11 (1), 3 – 24. https://doi.org/10.1179/1477963313Z.00000000023</bibtext> </blist> <blist> <bibtext> Wang, J., Thijs, B., &amp; Glänzel, W. (2015). Interdisciplinarity and impact: Distinct effects of variety, balance, and disparity. PloS One, 10 (5), e0127298. https://doi.org/10.1371/journal.pone.0127298</bibtext> </blist> <blist> <bibtext> Wehmeyer, M. L. (2013). Beyond pathology: Positive psychology and disability. In M. L. Wehmeyer (Ed.), The Oxford handbook of positive psychology and disability (pp. 3 – 6). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195398786.001.0001</bibtext> </blist> <blist> <bibtext> Westrupp, E. M., Reilly, S., McKean, C., Law, J., Mensah, F., &amp; Nicholson, J. M. (2020). Vocabulary development and trajectories of behavioral and emotional difficulties via academic ability and peer problems. Child Development, 91 (2), e365 – e382. https://doi.org/10.1111/cdev.13219</bibtext> </blist> <blist> <bibtext> Wexler, J., Shelton, A., Stark, K., Hogan, E., Chow, J., &amp; Fisk, R. (2023). Professional Development as a Pathway For Sustaining Teachers. In Handbook of research on special education teacher preparation (pp. 319 – 340). Routledge.</bibtext> </blist> <blist> <bibtext> Wiederholt, J. L. (1974). Historical perspectives on the education of the learning disabled. In L. Mann &amp; D.A. Sabatino (Eds.), The second review of special education (pp. 103 – 152). PRO-ED.</bibtext> </blist> <blist> <bibtext> Yeh, M., Zerr, A., &amp; McCabe, K. (2022). Personalizing PCIT for culturally diverse families: Outcomes from a pilot trial utilizing the PersIn framework. Behaviour Research and Therapy, 159, 104204. https://doi.org/10.1016/j.brat.2022.104204</bibtext> </blist> <blist> <bibtext> Ying, X., &amp; Ehrhardt, S. (2023). Pilot trials may improve the quality of full-scale trials: A meta-research study. Journal of Clinical Epidemiology, 160, 117 – 125. https://doi.org/10.1016/j.jclinepi.2023.06.017</bibtext> </blist> <blist> <bibtext> Yoder, P., &amp; Symons, F. (2010). Observational measurement of behavior. Springer Publishing Company.</bibtext> </blist> <blist> <bibtext> Yoder, P., J., Symons, F., &amp; Lloyd, B. P. (2018). Observational measurement of behavior (2nd ed.). Brookes Publishing.</bibtext> </blist> <blist> <bibtext> Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25 (1), 3 – 17. https://doi.org/10.1207/s15326985ep2501_2</bibtext> </blist> <blist> <bibtext> Zimmerman, K. N., Torelli, J. N., &amp; Chow, J. C. (2022). Planning positive reinforcement cycles in behavior intervention plans. Behavior Analysis in Practice, 15 (3), 924 – 937. https://doi.org/10.1007/s40617-021-00663-8</bibtext> </blist> <blist> <bibtext> Zusho, A., &amp; Kumar, R. (2018). Introduction to the special issue: Critical reflections and future directions in the study of race, ethnicity, and motivation. Educational Psychologist, 53 (2), 61 – 63. https://doi.org/10.1080/00461520.2018.1432362</bibtext> </blist> </ref> <ref id="AN0186160233-21"> <title> Footnotes </title> <blist> <bibtext> The three examples are not meant to represent an exhaustive listing of how incremental science has advanced the field of special education, nor is the selection of these particular examples meant to imply higher quality or rigor of research compared to the many other examples in the field.</bibtext> </blist> </ref> <aug> <p>By Jason C. Chow and Jessica R. Toste</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib50" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib74" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib111" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib119" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib101" firstref="ref5"></nolink> <nolink nlid="nl6" bibid="bib128" firstref="ref6"></nolink> <nolink nlid="nl7" bibid="bib131" firstref="ref7"></nolink> <nolink nlid="nl8" bibid="bib91" firstref="ref8"></nolink> <nolink nlid="nl9" bibid="bib127" firstref="ref9"></nolink> <nolink nlid="nl10" bibid="bib12" firstref="ref10"></nolink> <nolink nlid="nl11" bibid="bib66" firstref="ref11"></nolink> <nolink nlid="nl12" bibid="bib78" firstref="ref12"></nolink> <nolink nlid="nl13" bibid="bib113" firstref="ref13"></nolink> <nolink nlid="nl14" bibid="bib38" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib123" firstref="ref19"></nolink> <nolink nlid="nl16" bibid="bib120" firstref="ref21"></nolink> <nolink nlid="nl17" bibid="bib92" firstref="ref22"></nolink> <nolink nlid="nl18" bibid="bib49" firstref="ref23"></nolink> <nolink nlid="nl19" bibid="bib93" firstref="ref24"></nolink> <nolink nlid="nl20" bibid="bib97" firstref="ref26"></nolink> <nolink nlid="nl21" bibid="bib109" firstref="ref27"></nolink> <nolink nlid="nl22" bibid="bib110" firstref="ref28"></nolink> <nolink nlid="nl23" bibid="bib22" firstref="ref29"></nolink> <nolink nlid="nl24" bibid="bib19" firstref="ref31"></nolink> <nolink nlid="nl25" bibid="bib47" firstref="ref32"></nolink> <nolink nlid="nl26" bibid="bib76" firstref="ref33"></nolink> <nolink nlid="nl27" bibid="bib129" firstref="ref34"></nolink> <nolink nlid="nl28" bibid="bib28" firstref="ref36"></nolink> <nolink nlid="nl29" bibid="bib45" firstref="ref37"></nolink> <nolink nlid="nl30" bibid="bib27" firstref="ref39"></nolink> <nolink nlid="nl31" bibid="bib61" firstref="ref40"></nolink> <nolink nlid="nl32" bibid="bib70" firstref="ref41"></nolink> <nolink nlid="nl33" bibid="bib94" firstref="ref42"></nolink> <nolink nlid="nl34" bibid="bib43" firstref="ref43"></nolink> <nolink nlid="nl35" bibid="bib17" firstref="ref44"></nolink> <nolink nlid="nl36" bibid="bib44" firstref="ref45"></nolink> <nolink nlid="nl37" bibid="bib138" firstref="ref46"></nolink> <nolink nlid="nl38" bibid="bib81" firstref="ref47"></nolink> <nolink nlid="nl39" bibid="bib65" firstref="ref48"></nolink> <nolink nlid="nl40" bibid="bib39" firstref="ref49"></nolink> <nolink nlid="nl41" bibid="bib30" firstref="ref50"></nolink> <nolink nlid="nl42" bibid="bib75" firstref="ref52"></nolink> <nolink nlid="nl43" bibid="bib88" firstref="ref53"></nolink> <nolink nlid="nl44" bibid="bib96" firstref="ref54"></nolink> <nolink nlid="nl45" bibid="bib108" firstref="ref55"></nolink> <nolink nlid="nl46" bibid="bib118" firstref="ref56"></nolink> <nolink nlid="nl47" bibid="bib133" firstref="ref57"></nolink> <nolink nlid="nl48" bibid="bib90" firstref="ref59"></nolink> <nolink nlid="nl49" bibid="bib136" firstref="ref61"></nolink> <nolink nlid="nl50" bibid="bib48" firstref="ref62"></nolink> <nolink nlid="nl51" bibid="bib56" firstref="ref63"></nolink> <nolink nlid="nl52" bibid="bib57" firstref="ref64"></nolink> <nolink nlid="nl53" bibid="bib58" firstref="ref65"></nolink> <nolink nlid="nl54" bibid="bib53" firstref="ref66"></nolink> <nolink nlid="nl55" bibid="bib52" firstref="ref67"></nolink> <nolink nlid="nl56" bibid="bib36" firstref="ref68"></nolink> <nolink nlid="nl57" bibid="bib100" firstref="ref69"></nolink> <nolink nlid="nl58" bibid="bib104" firstref="ref71"></nolink> <nolink nlid="nl59" bibid="bib105" firstref="ref73"></nolink> <nolink nlid="nl60" bibid="bib107" firstref="ref74"></nolink> <nolink nlid="nl61" bibid="bib54" firstref="ref75"></nolink> <nolink nlid="nl62" bibid="bib24" firstref="ref76"></nolink> <nolink nlid="nl63" bibid="bib60" firstref="ref77"></nolink> <nolink nlid="nl64" bibid="bib115" firstref="ref78"></nolink> <nolink nlid="nl65" bibid="bib137" firstref="ref79"></nolink> <nolink nlid="nl66" bibid="bib20" firstref="ref80"></nolink> <nolink nlid="nl67" bibid="bib83" firstref="ref86"></nolink> <nolink nlid="nl68" bibid="bib106" firstref="ref87"></nolink> <nolink nlid="nl69" bibid="bib134" firstref="ref89"></nolink> <nolink nlid="nl70" bibid="bib69" firstref="ref90"></nolink> <nolink nlid="nl71" bibid="bib77" firstref="ref91"></nolink> <nolink nlid="nl72" bibid="bib80" firstref="ref92"></nolink> <nolink nlid="nl73" bibid="bib112" firstref="ref93"></nolink> <nolink nlid="nl74" bibid="bib135" firstref="ref94"></nolink> <nolink nlid="nl75" bibid="bib64" firstref="ref95"></nolink> <nolink nlid="nl76" bibid="bib73" firstref="ref96"></nolink> <nolink nlid="nl77" bibid="bib99" firstref="ref97"></nolink> <nolink nlid="nl78" bibid="bib98" firstref="ref98"></nolink> <nolink nlid="nl79" bibid="bib95" firstref="ref99"></nolink> <nolink nlid="nl80" bibid="bib84" firstref="ref100"></nolink> <nolink nlid="nl81" bibid="bib41" firstref="ref101"></nolink> <nolink nlid="nl82" bibid="bib114" firstref="ref102"></nolink> <nolink nlid="nl83" bibid="bib62" firstref="ref103"></nolink> <nolink nlid="nl84" bibid="bib89" firstref="ref105"></nolink> <nolink nlid="nl85" bibid="bib33" firstref="ref106"></nolink> <nolink nlid="nl86" bibid="bib14" firstref="ref107"></nolink> <nolink nlid="nl87" bibid="bib15" firstref="ref108"></nolink> <nolink nlid="nl88" bibid="bib35" firstref="ref109"></nolink> <nolink nlid="nl89" bibid="bib51" firstref="ref110"></nolink> <nolink nlid="nl90" bibid="bib29" firstref="ref111"></nolink> <nolink nlid="nl91" bibid="bib55" firstref="ref113"></nolink> <nolink nlid="nl92" bibid="bib34" firstref="ref115"></nolink> <nolink nlid="nl93" bibid="bib42" firstref="ref116"></nolink> <nolink nlid="nl94" bibid="bib86" firstref="ref117"></nolink> <nolink nlid="nl95" bibid="bib102" firstref="ref118"></nolink> <nolink nlid="nl96" bibid="bib126" firstref="ref119"></nolink> <nolink nlid="nl97" bibid="bib116" firstref="ref126"></nolink> <nolink nlid="nl98" bibid="bib10" firstref="ref128"></nolink> <nolink nlid="nl99" bibid="bib46" firstref="ref129"></nolink> <nolink nlid="nl100" bibid="bib59" firstref="ref130"></nolink> <nolink nlid="nl101" bibid="bib117" firstref="ref131"></nolink> <nolink nlid="nl102" bibid="bib40" firstref="ref134"></nolink> <nolink nlid="nl103" bibid="bib63" firstref="ref135"></nolink> <nolink nlid="nl104" bibid="bib125" firstref="ref136"></nolink> <nolink nlid="nl105" bibid="bib11" firstref="ref137"></nolink> <nolink nlid="nl106" bibid="bib68" firstref="ref138"></nolink> <nolink nlid="nl107" bibid="bib23" firstref="ref139"></nolink> <nolink nlid="nl108" bibid="bib79" firstref="ref140"></nolink> <nolink nlid="nl109" bibid="bib85" firstref="ref141"></nolink> <nolink nlid="nl110" bibid="bib130" firstref="ref142"></nolink> <nolink nlid="nl111" bibid="bib103" firstref="ref145"></nolink> <nolink nlid="nl112" bibid="bib13" firstref="ref146"></nolink> <nolink nlid="nl113" bibid="bib67" firstref="ref147"></nolink> <nolink nlid="nl114" bibid="bib16" firstref="ref148"></nolink> <nolink nlid="nl115" bibid="bib25" firstref="ref149"></nolink> <nolink nlid="nl116" bibid="bib26" firstref="ref151"></nolink> <nolink nlid="nl117" bibid="bib71" firstref="ref152"></nolink> <nolink nlid="nl118" bibid="bib132" firstref="ref153"></nolink> <nolink nlid="nl119" bibid="bib72" firstref="ref154"></nolink> <nolink nlid="nl120" bibid="bib18" firstref="ref155"></nolink> <nolink nlid="nl121" bibid="bib21" firstref="ref156"></nolink> <nolink nlid="nl122" bibid="bib32" firstref="ref157"></nolink> <nolink nlid="nl123" bibid="bib82" firstref="ref158"></nolink> <nolink nlid="nl124" bibid="bib87" firstref="ref159"></nolink> <nolink nlid="nl125" bibid="bib124" firstref="ref160"></nolink> |
|---|---|
| Header | DbId: eric DbLabel: ERIC An: EJ1506152 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Using Incremental Science to Improve Inclusive Educational Psychology Research – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jason+C%2E+Chow%22">Jason C. Chow</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2878-7410">0000-0002-2878-7410</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jessica+R%2E+Toste%22">Jessica R. Toste</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6327-0054">0000-0002-6327-0054</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Educational+Psychologist%22"><i>Educational Psychologist</i></searchLink>. 2025 60(3):172-188. – Name: Avail Label: Availability Group: Avail Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 17 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Descriptive – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Scientific+Research%22">Scientific Research</searchLink><br /><searchLink fieldCode="DE" term="%22Sequential+Approach%22">Sequential Approach</searchLink><br /><searchLink fieldCode="DE" term="%22Special+Education%22">Special Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Psychology%22">Educational Psychology</searchLink><br /><searchLink fieldCode="DE" term="%22Students+with+Disabilities%22">Students with Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Design%22">Research Design</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Administration%22">Research Administration</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Methodology%22">Research Methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Individual+Differences%22">Individual Differences</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1080/00461520.2025.2486140 – Name: ISSN Label: ISSN Group: ISSN Data: 0046-1520<br />1532-6985 – Name: Abstract Label: Abstract Group: Ab Data: In the article, we use an incremental science approach to propose opportunities for researchers in educational psychology and special education to design and implement studies that are inclusive of theory development and students with disabilities. We describe the goals and purpose of incremental science in special education and how the incremental science framework is aligned with research methodologies and funding mechanisms. We provide examples of research that have advanced knowledge in special education and discuss the importance of individual differences and disability as diversity, intersectionality, and opportunities to advance and deepen the understanding of special education and students with disabilities' experiences by expanding the methodological approaches used across the incremental frameworks, highlighting methods and procedures used in special education. We conclude by emphasizing the importance of studying phenomena in real-world, complex contexts and provide additional examples and avenues for researchers to use incremental science to address both individual differences and structural challenges in education. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2026 – Name: AN Label: Accession Number Group: ID Data: EJ1506152 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1506152 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00461520.2025.2486140 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 172 Subjects: – SubjectFull: Scientific Research Type: general – SubjectFull: Sequential Approach Type: general – SubjectFull: Special Education Type: general – SubjectFull: Educational Research Type: general – SubjectFull: Educational Psychology Type: general – SubjectFull: Students with Disabilities Type: general – SubjectFull: Research Design Type: general – SubjectFull: Research Administration Type: general – SubjectFull: Research Methodology Type: general – SubjectFull: Individual Differences Type: general Titles: – TitleFull: Using Incremental Science to Improve Inclusive Educational Psychology Research Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jason C. Chow – PersonEntity: Name: NameFull: Jessica R. Toste IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0046-1520 – Type: issn-electronic Value: 1532-6985 Numbering: – Type: volume Value: 60 – Type: issue Value: 3 Titles: – TitleFull: Educational Psychologist Type: main |
| ResultId | 1 |
