Every field has a tendency to chase what’s next.
Healthcare races toward the newest treatment. Education regularly rediscovers ideas that were documented decades earlier and repackages them with new terminology. Even Applied Behavior Analysis (ABA), a discipline built upon careful observation, replication, and evidence, isn’t immune to those same tendencies.
Ironically, one of the easiest ways to become a better practitioner isn’t simply reading the newest journal article. Rather, it’s understanding where today’s ideas came from.
Never before has it been easier to consume information. Artificial intelligence can summarize hundreds of pages in seconds. Search engines can answer nearly any technical question within moments. Research is more accessible than at any point in history. But I sometimes wonder if we’re becoming historically shallow.
As our ability to retrieve information continues to improve, our opportunity to understand how ideas evolved may actually be shrinking. We often learn what works without ever learning why someone thought to ask the question in the first place.
I think that’s a loss. Because every ABA intervention has a history, every assessment has a lineage, and every graph has a backstory.
Better ABA Practice Begins with Better Historical Literacy
One of the things I’ve always appreciated about behavior analysis is that it asks us to stay humble. We follow the data. We test our assumptions. We change course when the evidence tells us we should. Historical literacy asks us to bring that same humility to the history of our science.
It’s easy to assume that the assessments we administer, the interventions we implement, and the teaching strategies we recommend simply appeared because someone had a good idea. The reality is much messier and much more interesting.
Nearly everything we use today represents years, and often decades, of experimentation, disagreement, refinement, replication, and collaboration. Researchers challenged assumptions. Teachers tested ideas in classrooms. Clinicians discovered what generalized and what didn’t. Families advocated for better options. Each generation contributed another piece to a much larger puzzle.
I don’t think history is valuable simply because it tells us where we’ve been. I think it’s valuable because it changes how we interpret where we are today. When you understand the questions researchers were trying to answer, today’s assessments, interventions, and teaching models begin to make a lot more sense.
It reminds us that many of today’s “new” ideas are often refinements of questions someone else began asking years ago. It gives us context for why certain practices have endured while others quietly disappeared. Perhaps most importantly, it helps us distinguish genuine innovation from familiar concepts wrapped in modern language. In an era where new technologies and products emerge almost weekly, I think that’s becoming an increasingly valuable skill.
Every ABA Tool We Use Has a Backstory
Most practitioners don’t spend much time thinking about where their favorite assessments or teaching models came from. That’s understandable. Our days are filled with supporting learners, collaborating with families, supervising staff, writing reports, and making clinical decisions. Each tool is often viewed as exactly that: a tool.
But every one of those tools represents years of scientific thinking.
Take the VB-MAPP, for example. Thousands of BCBAs® have administered it as part of their assessment process. It’s become a familiar part of clinical practice throughout autism services, yet it’s much more than a developmental checklist. Its foundation traces back to B. F. Skinner’s analysis of verbal behavior, which fundamentally shifted how many behavior analysts think about language. Rather than viewing language as a collection of words to memorize, verbal behavior asks us to consider the different functions language serves and the environmental variables that shape it. Understanding those origins often changes how clinicians interpret assessment results and design interventions.
The same idea applies to PEAK.
Many clinicians recognize PEAK as an assessment and curriculum designed to evaluate increasingly complex learning and language skills. What often receives less attention is the decades of research on stimulus equivalence, symbolic behavior, and relational learning that helped make those applications possible. Those discoveries expanded our understanding of how people learn relationships among stimuli without direct teaching, opening new possibilities for assessment and instruction. Appreciating that history transforms PEAK from simply another curriculum into an application of a much broader scientific conversation that has been evolving for decades.
One of the most fascinating examples comes from the work surrounding fluency-based instruction and the Morningside Model of Generative Instruction.
Most educators want remarkably similar outcomes. They want students who can retain what they learn, apply it in new situations, solve novel problems, and continue learning independently long after instruction has ended. The disagreement has rarely been about the goal. It’s been about the path to getting there.
Behavior analysis approached that challenge differently.
Rather than beginning with theories about how learning should occur, researchers asked measurable questions:
What instructional arrangements consistently produce durable learning? What happens when foundational skills become fluent rather than merely accurate?
Under what conditions do learners begin solving problems they were never explicitly taught to solve?
Those questions led researchers like Ogden Lindsley to develop Precision Teaching, fundamentally changing how many educators thought about mastery. Instead of asking whether a learner could perform a skill, the emphasis shifted toward whether that skill had become fluent—accurate, efficient, retained over time, and flexible enough to support future learning.
Kent Johnson and his colleagues extended that work even further through the Morningside Model of Generative Instruction. Their central question wasn’t simply, “How do we teach today’s lesson more effectively?” It was, “How do we build repertoires that allow learners to generate entirely new performances tomorrow?”
That’s a subtle difference, and a profound one.
When foundational skills become fluent, they stop competing for cognitive resources. Learners are then free to recognize patterns, combine previously learned skills, and solve problems they have never encountered before. In other words, the goal isn’t simply successful instruction. It’s generative responding—creating conditions where new learning emerges because the underlying repertoire has been carefully built.
What I find especially compelling is that this isn’t simply an elegant theory. Morningside Academy has spent decades testing these ideas in practice. The school became well known for offering a money-back guarantee if students failed to make the promised 2-years of academic growth in their area of most need. Over roughly four decades, that guarantee reportedly resulted in refunds for fewer than 1% of enrolled students. (Johnson et al., 2021) That’s an extraordinary claim—not because of the guarantee itself, but because it reflects decades of confidence in a model that has been continuously measured, refined, and improved.
Understanding that history changes how I think about education. I no longer see Morningside simply as an effective school. I see it as the product of generations of researchers asking increasingly better questions about how human beings learn.
Science Moves Through Data. People Often Move Through Stories.
For many practitioners, the entry point into Applied Behavior Analysis is a research article, a university course, or supervised fieldwork. For many families, it has been something entirely different. A story.
One of the clearest examples is Catherine Maurice’s Let Me Hear Your Voice. Long before social media became a primary source of information, Maurice shared a deeply personal account of searching for effective intervention for her children with autism. It wasn’t written as a textbook or a literature review. It was written as a parent’s experience navigating uncertainty, hope, and difficult decisions. (Detrich, 2018)
Regardless of where someone stands on every detail within the book today, its historical impact is difficult to overstate. It introduced countless families (and many future practitioners) to Applied Behavior Analysis at a time when relatively few people outside the profession had ever encountered it. More importantly, it demonstrated something our field occasionally overlooks: research changes science, but stories often change whether people ever discover the science in the first place.
Standing on the Shoulders of Giants
Ogden Lindsley often reflected on the privilege of standing on the shoulders of B. F. Skinner, recognizing that his own contributions were possible because someone before him had fundamentally changed how we understand behavior. I think that’s a perspective worth carrying forward.
“Stand on my shoulders as I stood on Fred Skinner’s shoulders. You see more big things from up here and you see further.”
–Ogden Lindsley (w/Nancy Hughes), 2004
Our field has always advanced this way. Rarely is there a novel breakthrough attributable to one individual. Rather, it’s almost always through one generation building thoughtfully upon the work of another.
The more I’ve learned about the history of Applied Behavior Analysis, the more I’ve realized that those giants aren’t simply names in textbooks or authors of journal articles. They were teachers, mentors, collaborators, and people who spent years wrestling with difficult questions long before many of us entered the profession.
One of the unexpected gifts of becoming interested in our field’s history is that the history eventually becomes personal.
If you’re genuinely curious, ask thoughtful questions, and take an interest in the work that came before you. Then, something remarkable begins to happen. The researchers whose papers you once highlighted become people you meet at conferences. The authors whose books shaped your thinking become generous conversation partners. You begin hearing the stories that never appeared in journal articles: the failed experiments, the unexpected discoveries, the debates that changed someone’s mind, and the moments when an entirely new direction emerged from what initially looked like failure.
Those conversations have become some of the most meaningful learning experiences of my career.
Preserving More Than Research
One of those opportunities came while producing The Morningside Model of Generative Instruction documentary. Like many educators and behavior analysts, I had admired the work coming from Morningside Academy for years. Sitting down with Kent Johnson wasn’t simply an opportunity to ask questions about instructional methods. It was an opportunity to hear the story behind them. How did these ideas evolve? Which assumptions turned out to be wrong? What discoveries surprised the researchers themselves?
How did decades of work in Direct Instruction, Precision Teaching, generative learning, and instructional design ultimately converge into an educational model that continues to influence classrooms today?
Those are questions that research papers rarely answer. They’re stories. And stories preserve something scientific journals often cannot.
That’s one reason I was so grateful to contribute to the newly released ABAI series Personal Narratives on the Behavior Analysis of Human Language and Cognition: Stories from Around the World. Rather than simply documenting research findings, the editors assembled a collection of personal histories from many of the individuals who helped shape modern behavior analysis, language, cognition, and education over the past seventy years.
My own contribution was modest, an interview with Kent Johnson that grew out of the documentary project, but seeing that conversation included alongside the reflections of so many people whose work has influenced our field was both humbling and deeply meaningful. (Johnson & O’Donnell, 2026)
To me, that’s what makes the book special.
Scientific journals preserve the findings. Personal narratives preserve the people. In a profession that’s constantly searching for what’s next, both matter. One tells us what we know today. The other reminds us how we came to know it in the first place.
Looking Back to Move Forward
We often say that better decisions begin with better data. I wholeheartedly believe that’s true. But good data becomes even more valuable when we remember how we learned what was worth measuring in the first place.
Every assessment we administer represents decades of scientific thinking. Every intervention carries the influence of researchers, teachers, clinicians, and families who asked difficult questions before us. Every graph has a backstory.
The more we understand those stories, the better equipped we’ll be to contribute our own chapter to the science—and to leave something meaningful for the generation that follows.
If any of this has you curious about where an idea in ABA started, or how it's held up in practice since, Motivity's Learning Tools page offers ongoing webinars, CEUs, and other helpful resources. And if you're already using Motivity, our Customer Learning Hub has more waiting for you there too.
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References:
Detrich, R. Perspect Behav Sci (2018) 41: 541. https://doi.org/10.1007/s40614-018-0160-y
Johnson, K., Street, E. M., Kieta, A. R., & Robbins, J. (2021). The Morningside model of generative instruction: Bridging the gap between skills and inquiry teaching. Sloan Publishing.
Johnson, K., O’Donnell, R. (2026). In pursuit of a comprehensive technology of education. In C. Harte, D. Barnes-Holmes, M. Sivaraman, J. de Rose, & J. Leslie (Eds.), Personal narratives on the behavior analysis of human language and cognition: Stories from around the world (pp. 61–77). Routledge.
Maurice, C. (1993). Let me hear your voice: A family's triumph over autism. New York: Knopf.