The Case for Behavior Analysis in the Study of Home Education
PERSPECTIVES – News and Comments1
Home School Researcher Volume 40, No. 3, 2026, p. 9-15
(Volume 40 was originally scheduled to be published in 2024.)
Note 1. The “Perspectives – News and Comments” section of this journal consists of articles that have not undergone normal blind peer review.
Danielle R. Bratton
Assistant Professor, Department of Special Education, Ball State University, Muncie, Indiana, danielle.bratton@bsu.edu
Abigail L. Johnson
Graduate Assistant, Department of Educational Psychology, Ball State University, Muncie, Indiana, abi.johnson@bsu.edu
Nichole M. Weakley
Associate Professor, Department of Special Education, Ball State University, Muncie, Indiana, nmweakley@bsu.edu
Abstract
Home education research has often been treated as adjacent to, rather than part of, the broader science of learning and leans on descriptive accounts of autonomy, motivation, and family practice without specifying mechanisms or measurement. Many features common in home education, including individualized pacing, timely feedback, natural reinforcement, and practice embedded in daily routines, already align with well-established principles of human learning. This paper illustrates how using a behavior-analytic framework can extend the reach of home-education inquiry by linking familiar practices to measurable outcomes, experimental tests, and findings that generalize across learners and settings. We compare descriptive and behavior-analytic perspectives across ontology, epistemology, axiology, and methodology to clarify what counts as learning, how evidence is justified, which outcomes matter, and how these commitments shape study and practice. Using a behavior-analytic framework strengthens rigor and comparability while preserving the flexibility of family-led learning, allowing findings from home education to contribute directly to the broader science of learning.
Keywords: home education; behavior analysis; science of learning; single-subject design
For millennia, much of education occurred not in institutions, but in places like homes, fields, and workshops through things like modeling, shaping, and reinforcement long before such processes were formally defined as principles of learning (Gidley, 2016). Today, the home education movement is simultaneously a return to that deeply human mode of learning as well as a forward-facing opportunity to examine it through a lens of behavioral science. Because, despite historical legitimacy and growing prevalence, this way of schooling is often dismissed by formal education systems in part due to a lack of robust empirical evidence in modern literature (Lubienski et al., 2013; Wilhelm & Firmin, 2009). Applied behavior analysis (ABA), as a science of human learning, offers a framework that can describe, measure, and refine what effective home educators already do intuitively: individualize instruction, shape mastery, and reinforce progress.
To bridge this divide, we first define home education as parent-directed learning in which families hold primary responsibility for instructional decisions distinct from institution-directed virtual instruction, hybrid arrangements, or publicly administered online programs where instructional authority remains with a school system (Ray, 2021b). Further, we recognize it as a legitimate, evidence-consistent practice and offer a pragmatic research framework to strengthen its study. Overlaying the analytic precision of behavioral science on the long-standing pedagogy of homeschooling not only extends and strengthens the credibility of both, but also honors the natural ways that humans learn. Ultimately, home education not only aligns with the science of learning as outlined by the principles of behavior analysis, but exemplifies it, and begs for rigorous study to advance both practice and understanding. This article outlines how a functional-analytic framework can strengthen homeschool research by specifying what counts as learning and evidence.
Human Learning and the Industrialization of Education
Home education, once the dominant model of learning, has been steadily regaining popularity in recent years (Ray, 2021; Watson, 2024). Following a roughly 50-year span where homeschooling was either explicitly prohibited or practically impossible under compulsory attendance laws in America, the right to home education became protected by law in all 50 states in 1993 (Fuller, 1997). Since, there had been a steady increase in the numbers of home educated children, estimated around 1.7% of students in 1999 growing to approximately 4% of K-12 students prior to the pandemic (Ray, 2018). COVID-19 school closures were associated with a rapid, sustained increase of home educated students (Watson, 2024). According to the US Census Bureau, the number of home educating families increased to around 3.1 million following the outbreak of the COVID-19 pandemic, accounting for nearly 6% of all K-12 students (Duvall, 2021; Ray, 2021). Though the current census data is not complete, it is estimated that this number has remained stable (Watson, 2024). Given that home education is shaping the experience of a growing share of students in the American education system, it is crucial that educators, academics, and policy makers work to understand the pedagogical, social, and structural factors that influence the growth and outcomes of these students.
Motivations for home education are diverse but often align with one of two overarching themes: reactive responses to external circumstances or proactive pursuits of specific educational values (Eldeeb et al., 2024; Green-Hennessey & Mariotti, 2023; Harding & Couper, 2025). Reactive factors are issues that are undesirable and drive parents away from traditional schooling due to dissatisfaction. Things like curriculum choice, child well-being (Chinazzi & Fensham-Smith, 2025; Green-Hennessy & Mariotti, 2023; Mitchell, 2022; Ray, 2021; Slater et al., 2022), safety concerns within the school environment, and bullying (Connolly-Sporing et al., 2024; O’Hagan et al., 2021; Sakarski, 2022; Valiente et al., 2022) fall into this category. Proactive factors, in contrast, focus more on what is desirable about home education (Green-Hennessy & Mariotti, 2023). Things like flexibility and strength of curriculum, lifestyle influences, religious preferences, and individualized educational experiences often play a significant role in the choice to home educate (Chinazzi & Fensham-Smith, 2025; Harding & Couper, 2025; Lee, 2024; Ray, 2021; Slater et al., 2022; Valiente et al., 2022).
For many families, the decision to choose home education reflects a combination of proactive goals and reactive responses to challenges faced within a traditional school environment. Parents have reported that the individualized curriculum, familiar surroundings, and sustained 1:1 educational support found in home education was beneficial for students with disabilities and other special needs (Ray et al., 2021). Home education can offer a level of flexibility and responsiveness that traditional systems cannot, allowing families to adapt learning environments and routines to their child’s unique needs rather than waiting for institutional policy to evolve.
Education policy, in response to theoretical and philosophical concerns, is often implemented with the expectation that it will address particular societal problems (Eden et al., 2024). Compulsory attendance laws, for example, were designed to address issues with literacy, promote civic engagement, reduce societal inequality, and increase safety (Bandiera et al., 2019). Following their implementation in all 50 states by 1920, these laws were found to increase attendance and reduce earning inequality in the first cohort of students (Clay et al., 2021). It was also found that increasing compulsory education by one year reduced the likelihood of reporting poor health conditions and chronic illnesses by 6.85 and 4.4 percentage points, respectively (Fonseca et al., 2020).
Yet, as with many policies, focusing on first-line objectives can overlook secondary and tertiary effects that are less visible but equally important. While increases in attendance, earnings, and health outcomes demonstrate clear benefits, other consequences highlight the complexity in development and implementation of education policy and law. DeAngelis et al. (2020) found that following the implementation of compulsory education laws, rates of patents and output per worker decreased. They interpreted this to mean that compulsory laws led to a reduction in innovation and productivity, having a direct economic and societal impact (DeAngelis et al., 2020).
In the current landscape of politicized education, it is clear that we must evaluate second and third order effects of education policy, reform efforts, and modes of academic delivery (Douglass et al., 2024). The growing entanglement of politics and pedagogy has created an environment where ideological differences can overshadow student needs, leaving schools to navigate shifting mandates and inconsistent priorities (Proweller & Monkman, 2024; Woo et al., 2022). As national data continue to reveal rising pressure surrounding academic achievement and increasing concerns about student mental health, the urgency to assess how policy decisions ripple through classrooms and into learners’ lives cannot be overstated. (Bas, 2021; Benton et al., 2021; Högberg, 2021; Turner et al., 2024). No longer can we discuss as fringe, the generally positive outcomes reported among home-educated students, nor the fact that they now account for approximately 6% of the K-12 population (Ray, 2021; Valiente et al., 2022). This growing sector of learners provides valuable insight into alternative models of instruction and engagement, and challenges long-held assumptions about what effective learning must look like.
As education shifted from its origins in the home to more formalized systems of compulsory schooling, it has invited deeper reflection on not only how children are taught, but why. The moral role of education has long been debated, touching on questions of autonomy, authority, and the responsibilities of society toward its youth (Christman, 2020). Early classical thinkers like Socrates and Plato emphasized questioning, dialogue, and critical thinking to help cultivate virtue and wisdom, shaping moral and civic character (Leigh, 2007). Aristotle believed that education should develop both reason and moral virtue, while St. Thomas Aquinas integrated those thoughts with Christian theology believing that education should cultivate both reason and faith (Hancock, 2015). As education evolved with time, arguments have grown from these philosophies on the value of education on physical, mental, and moral development (Sharma & Aswal, 2021) demanding conversation on the distinction between education as a right and as an obligation (Gaviria, 2022). Evaluating both these broader conversations as well as the effects of education policy is critical, as it underscores the need to examine not only whether a law achieves its intended goal, but also how it interacts with other aspects of learning, development, and societal progress. However, much of the literature on compulsory education remains theoretical or philosophical, lacking empirical evidence (Schouten & Brighouse, 2014).
Beyond broad theories about the aims of education, research on applied practices in education remains largely descriptive, drawing primarily on qualitative accounts and descriptive statistics rather than experimental designs. Researchers have focused their efforts on educational form, studying techniques such as child-led learning, enriched environments, and multisensory activities (Kutluca et al., 2020; Yilmazlar & Görgen, 2023). Additionally, outcomes often emphasize descriptive data focused on student attitudes, participation, knowledge, and comprehension (O’Regan et al., 2023). While valuable, this reliance on descriptive data presents a significant gap in the applied literature within education as it overlooks observational aspects of learning. This is particularly true as it relates to home education. While many home educators adhere to the educational philosophies presented in the literature, results have not been generalized outside of standard classroom settings and statistical educational data. To these ends, home education research has been siloed from the larger body of education research. To date, most existing research on home education has been more descriptive than analytic, contributing data on parental motivations and the social and academic outcomes of homeschooled students (Lubienski et al., 2013). This focus gives limited attention to the underlying process of learning that occurs in this environment which would have great potential to systematically extend the depth of understanding of human learning. Extending this body of research would not only advance our scientific understanding but could also illuminate innovative approaches to the persistent challenges facing industrialized education systems.
Further, despite the similarities in philosophy and theory behind education in both home and school, the theoretical literature focuses on the educational structures and rights but is limited in addressing the applied mechanisms of learning. Operationalizing terms like autonomy or motivation presents an opportunity to build a stronger body of literature.
Behavior analysis offers that opportunity for home education researchers to align and extend their work into a much broader evidence base, connecting the science of learning theory, philosophy, and application. By framing home education research through a behavioral lens, researchers can pull from existing foundations that inherently support practices home educators already employ. Further, behavior analysis uses experimental methodology to demonstrate efficacy, allowing home education researchers to extend and strengthen their work with greater empirical value.
This paper aims to provide an argument for using behavior analysis as a foundation for home education research. Through its robust body of evidence, behavior analysis would allow researchers to measure the efficacy of certain educational practices in alignment with the principles of behavior. By conceptualizing home education from a behavioral framework, home education researchers can leverage this science to evaluate best practices in home education, model the experimental design for future research, and extend the literature in novel ways. This would expand research on home education in two ways. First, by studying it in the context of understanding the fundamental processes of human learning. Second, by connecting it to the larger evidence base in the science of learning. This paper proposes a conceptual framework positioning behavior analysis as both the theoretical foundation and practical methodology through which home education can be systematically studied and understood.
Behavior Analysis as the Science of Learning
Rising in contrast to the dominant psychological thought of the early 20th century, behaviorism took shape during a time of growing scientific discovery, as society increasingly sought tangible explanations for what had long seemed beyond understanding (Guercio, 2020). New technology that allowed for greater exploration of physiology prompted a rise in inductive studies of animal behavior (Boakes, 2003). From here, science entered the study of human behavior. While there are many iterations of behaviorism, the most recognized type is radical behaviorism as defined by B. F. Skinner.
Radical behaviorism asserts that both public behaviors (such as speaking or writing) and private behaviors (such as thinking or remembering) fall within the realm of scientific study (Cooper et al., 2020). According to this view, both types of behaviors are governed by environmental variables. From radical behaviorism came the application of behavior analysis to the human population to promote socially significant behavior change. Operant conditioning methods led to the discovery of the basic principles of human learning (Miltenberger, 2016). From here, applied behavior analysis (ABA) was established (Cooper et al., 2020).
Behavior analysis provides a systematic, empirical understanding of human behavior grounded in experimental observation and inductive reasoning (Carr et al., 2020). The field’s methods have been applied to a wide range of socially significant problems including education, developmental disabilities, gerontology, sustainability, and public health (Cooper et al., 2020). Within psychology, behavior analytic research is notable for its consistent use of experimental analysis to establish functional relations between behavior and environment (Guercio, 2020), helping to drive advancements in intervention in education, aligning this scientific perspective with descriptive theories helps to clearly define what constitutes learning, how evidence is evaluated, and which outcomes are prioritized. This illustrates the value of a behavior-analytic framework for research in home education.
Educational Approaches
In the context of education, behavior analysis presents a functional approach that differs from descriptive educational theories. Descriptive theories offer a broad philosophical and psychological perspective on how and why learning occurs (Yilmaz, 2008). They emphasize concepts, tradition, and observation, providing frameworks for interpretation rather than testable conditions. Examples include Montessori philosophy, constructivism, and Piaget’s stages of development. In contrast, behavior analysis adopts a functional analytic approach that examines relations between behavior and environment to draw empirical conclusions about learning (Stewart, 2017). While descriptive measures hold value and often spark initial inquiry, behavior analysis extends beyond description by emphasizing prediction and control in the evaluation of instruction, resulting in more precise and adaptive interventions (Cooper et al., 2020).
Both descriptive and behavioral perspectives inform educational practice, yet they differ in level of analysis, purpose, and method. These differences are clearest when examined through the philosophical foundations that shape an educational approach: what counts as learning (ontology), how learning is known (epistemology), and which outcomes are valued (axiology) with further analysis of these related to research and practice (methodology) (Creswell & Poth, 2018; Guba & Lincoln, 1994; Scotland, 2012).
Ontology
To understand the philosophical distinctions between educational approaches, it is useful to begin with ontology, or the question of what learning is and what counts as evidence that learning has occurred (Creswell & Poth, 2018; Guba & Lincoln, 1994; Packer & Goicoechea, 2000; Scotland, 2012). In descriptive traditions, interpretivist and phenomenological commitments foreground meaning and lived experience, so evidence is primarily interpretive. Behavior analysis instead adopts a pragmatic, natural science perspective, treating public and private events as behavior within organism–environment relations and warranting claims through observable change, experimental control, and generality (Moore, 2003). For homeschool research, these ontological starting points yield different research questions, methods, and inferences.
For example, as a descriptive approach if we consider Piaget’s stages of development one might interpret learning to be relative to an internal process that shapes understanding (Yilmaz, 2008). Per this theory an individual in a preoperational stage of development would lack an ability to conserve quantity. So, when shown the same fluid ounces poured into two different containers they would erroneously believe that the tall, skinny container contains more fluid compared to the fluid in the wider container. When that same individual over the course of time is able to recognize that the amount of fluid is the same between containers, Piaget would attribute this as a sign of transition from the preoperational to operational stage of development. Conversely, the constructivist view on this scenario would maintain that the individual’s internal reasoning structures have changed through their interactions with the environment; they have developed a new learning schema through pouring liquids (Yilmaz, 2008). Both examples of descriptive theories offer insight into what learning has occurred by observing changes in behavior and knowledge, but they do not provide a means to measure how that change took place. The progression from preoperational to operational stages, or the construction of a new learning schema, relies on interpretations of hypothetical constructs rather than observable processes.
The behavior analytic approach to ontology relies on observable behavior and functional, measurable outcomes to quantify learning (Lattal & Laipple, 2003; Moore, 2003). Behavior analysts recognize that some behaviors, like thinking or remembering, are private and observable only to the individual (Baum, 2011; Cooper et al., 2020). Similarly, private events such as pain or excitement occur internally. While these are not directly observable, they can still be studied through their functional relations with the environment (Cooper et al., 2020). Theorists in this approach focus on functional relationships for the purpose of replication and demonstration of learning. Rather than attributing the cause of behavior to hypothetical constructs or explanatory fictions, behavior analysts seek to identify the contingencies that lead to learning (Cooper et al., 2020). In this example, a behavior analyst would view the individual’s development of the concept of conservation by identifying how the discrimination between fluid amounts were reinforced within the environment and then utilize those same strategies to teach new discriminations.
Epistemology
How can we know when learning has occurred? Epistemological considerations in education have often relied on things like philosophical reasoning, historical precedent, and interpretative frameworks when developing descriptive theories related to how learning takes place (Creswell & Poth, 2018; Guba & Lincoln, 1994; Scotland, 2012). These approaches rely heavily on theoretical coherence, interviews, and narrative descriptions to draw conclusions. For instance, a humanistic perspective might determine from case studies that individuals learn best when provided autonomy and are intrinsically motivated (Rogers, 1994). If a student were to submit a paper that received a failing grade, a humanist might contribute the outcome to a lack of intrinsic motivation; a factor that by its very nature is outside of the instructor’s direct influence.
Through a behavioral framework, knowledge itself is considered to be mentalistic (Cooper et al., 2020). However, learning and remembering are behaviors that can be measured and shaped (Cooper et al., 2020). Learning is measured using experimental methods that reveal cause-and-effect relationships between variables (Cooper et al., 2020). Evidence is built through data collection, replication, and systematic manipulation (Miltenberger, 2022). For instance, a behavior analyst might test whether feedback given before or after a writing task produces greater improvement. This analysis would demonstrate which feedback method results in the greatest improvement in writing.
Axiology
Axiology examines the values that should guide educational goals and priorities (Creswell & Poth, 2018; Guba & Lincoln, 1994; Scotland, 2012). Historically, there has been a large overlap between descriptive and behavior theories in this arena. Things like learner autonomy, competence, meaningful participation, and learning that endures and transfers are central values that learning practice should aim to achieve. The distinction lies, however, in how those values are articulated, selected as goals, and evaluated in practice.
Descriptive approaches often frame values as ideals. Things like curiosity, reflective understanding, and independent thought may be assessed using learner reflections and narratives, success determined by the student alignment with those ideals (Eisner, 1976). For example, in a writing course, instructors may value metacognition and flexible application of concepts, using reflective journals and portfolio reviews to judge whether students internalize strategies.
While behavior analysis shares these aims, it requires that values be operationalized and linked to outcomes that are observable, measurable, socially significant, and sustainable (Cooper et al., 2020). Goals are selected with stakeholders for their practical importance, and procedures are evaluated for effectiveness, efficiency, acceptability, generalization, and maintenance (Baer et al., 1968; Wolf, 1978). In the same writing course, the valued outcomes might include independent task initiation, revision behaviors that reliably improve rubric scores, and maintenance of those skills across assignments and instructors. Evidence would include direct measures of performance, follow-up probes for maintenance, and checks for generalization.
These approaches are complementary in this regard, as both perspectives prioritize autonomy and meaningful learning. Descriptive theories articulate these values as ideals that guide interpretation and behavior analysis treats them as outcomes to be defined, taught, and verified. In short, the values that matter are identified, and measured change demonstrates that those values were realized.
Methodology
Methodology translates an educational philosophy into practical expressions through concrete practices, procedures, and research strategies (Creswell & Poth, 2018; Guba & Lincoln, 1994; Scotland, 2012). It reflects the belief about what learning is, how it can be known, and how the ways of instruction and research are conducted based on identified values (Creswell & Poth, 2018; Guba & Lincoln, 1994; Scotland, 2012). Descriptive educational theories often rely on qualitative or interpretive methods such as case studies, interviews, or reflective analysis in the study of their theories. These approaches seek to capture the learner’s experience and meaning-making process, emphasizing description and interpretation over prediction (Creswell & Poth, 2018). A study informed by cognitive or constructivist theory, for instance, might use think-aloud protocols or narrative reflections to understand how learners internalize strategies or reorganize their understanding of a topic. The goal is often to describe how thinking and understanding appear to change, often overlooking cause-and-effect variables that can be directly studied.
In contrast, behavior analysis employs systematic observation and experimental methods to identify functional relations between teaching procedures and learning outcomes (Cooper et al., 2020). Through the use of single-subject design, researchers and practitioners systematically engage in experimentation that allows for the control necessary for rigorous scientific analysis (Byiers et al., 2012). In this design, participants can serve as their own control and data are collected repeatedly over time to document behavior before, during, and after an intervention (Cooper et al., 2020). Changes in level, trend, and stability of behavior are analyzed to determine whether the intervention produced a meaningful effect (Cooper et al., 2020). This allows researchers to demonstrate cause-and-effect relationships within individual learners rather than relying on group averages and dismissing outliers. Multiple baseline designs can also allow for comparison between individuals, settings, and interventions (Cooper et al., 2020). This methodological approach prioritizes precision and replication. Instructional strategies are evaluated using direct measures of behavior, generalization across settings, and maintenance over time (Cooper et al., 2020). These strategies aim to ensure that results are both effective and socially meaningful.
Understanding education through ontology, epistemology, axiology, and methodology clarifies why a behavior-analytic framework offers particular value for home education research. While descriptive traditions have helped articulate the meaning and purpose of learning, they often stop short of showing how learning occurs or how to measure change in ways that can be tested and replicated. Behavior analysis extends this work by grounding those same philosophical concerns in observable outcomes, systematic study, and practical application. Its emphasis on functional relations between behavior and environment provides tools for evaluating effectiveness while preserving the values of autonomy, curiosity, and meaningful learning.
Implications and Call to Action
Overlaying behavior analytic theory and methodologies over existing home education research is not merely an academic exercise. It is strategic and imperative. By applying the tools of a systematic science, researchers can more fully uncover the processes that drive learning in real-world environments. The impact of this extends beyond the homeschooling environment, allowing identification of instructional strategies that serve to maximizing mastery, build creativity, and support retention. For home educators, this perspective offers a roadmap for precision in teaching, assessment, and feedback that helps to ensure that the valued outcomes of autonomy, competence, meaningful engagement, and independence are not just aspirational but measurable. For researchers, this provides a replicable and scalable methodology that can integrate home education into the broader science of learning, strengthening the empirical foundation. The stakes of this research extend beyond the home. Rigorous, behavior-analytic study of home education could directly challenge outdated assumptions, inform policy, and offer innovative strategies that could enhance educational outcomes across all learning environments.
Conclusion
While often marginalized in contemporary discussions, homeschooling is part of the educational canon, grounded in centuries of theory, philosophy, and practice (Wilhelm & Firmin, 2009; Valiente et al., 2022). Today, it represents both a historical constant and an innovative landscape of human learning (Watson, 2024). Long predating institutionalized schooling, home education exemplifies the natural, individualized process of education while offering a unique context in which to empirically examine learning using single-case logic and direct measurement (Baer et al., 1968; Byiers et al., 2012). While descriptive traditions have helped to articulate much of the richness of home education, they often fall short in explaining how learning occurs or in providing tools for precise measurement (Yilmaz, 2008; Packer & Goicoechea, 2000; Creswell & Poth, 2018; Lubienski et al., 2013). Behavior analysis helps fill that gap by specifying operationalized goals, observable and measurable outcomes, and systematic experimental methods that make the mechanics of learning both transparent and actionable (Baer et al., 1968; Cooper et al., 2020; Miltenberger, 2022; Moore, 2003; Lattal & Laipple, 2003).
Positioning home education within this scientific framework does more than extend the scientific understanding of education; it can transform conversations around evidence-based instruction, strengthen the credibility of research in this area, and illuminate strategies with relevance for broader educational contexts (Schouten & Brighouse, 2014; Baer et al., 1968; Cooper et al., 2020). The growing population of home-educated learners is not a fringe phenomenon but a critical resource for understanding innovation, creativity, and the impact of individualization in human learning (Duvall, 2021; Ray, 2021; Watson, 2024). Through rigorous application of the science of behavior to this enduring mode of education, we can honor time-tested traditions in human learning while advancing a future in which education is effective and grounded in evidence (Baer et al., 1968; Byiers et al., 2012).
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1. The “Perspectives – News and Comments” section of this journal consists of articles that have not undergone peer review. ¯