Understanding Learning: Evidence-Based Theories and Debunking Myths

If someone shows up, participates, and completes every task, have they learned?

This question has shaped much of how I think about education. We often assume that visible activity equals progress, that engagement signals understanding, and that participation implies change. But experience and evidence suggest otherwise. Learning is not guaranteed by movement, preference, or effort alone. Something deeper has to happen.

This piece clarifies what learning actually is, challenges a persistent myth about how learning works, and argues for why evidence-based learning design matters, especially as educational systems and technologies scale.

Why I'm Writing This

I've spent years orbiting education from different angles. I previously worked in education and mentoring through AmeriCorps, and since then I've been building independent projects at the intersection of learning design, technology, and philosophy. Some of that work involves designing learning experiences and community-based programs. Some of it is more technical: building websites, digital tools, and, more recently, experimenting with AI agents and workflows for individuals and organizations.

Across all of it, I keep running into the same question: what actually changes when learning happens?

I've seen people complete programs, earn credentials, and stay busy without their thinking, choices, or sense of agency shifting in any meaningful way. I've also seen real learning happen far outside formal classrooms: through responsibility, failure, building things, and being placed in environments that demand adaptation. That contrast pushed me to look beyond intuition and toward learning science to better understand what supports real, lasting change.

What Learning Actually Is

At its core, learning is not the accumulation of information or the performance of tasks. Learning is a durable change in how a person understands, acts, or relates to the world as a result of experience.

I often think about learning in terms of a conscious organism interacting with its environment. If those interactions do not alter how the organism moves through the world (the decisions it makes, the strategies it uses, or the responsibilities it is willing to carry), then whatever occurred may have been activity, but it was not learning.

Research in learning science supports this view. Lovett et al. (2023) define learning as a process that leads to change as a result of experience, emphasizing that learning involves lasting change in knowledge, beliefs, behaviors, or attitudes. Critically, they note that learning is not something done to students but something students themselves do through how they interpret and respond to their experiences. This perspective recognizes learning as developmental and holistic, intersecting with students' identities, personal histories, and social and emotional experiences (Lovett et al., 2023).

Social cognitive theory (Denler, Wolters, & Benzon, 2010) adds another layer, emphasizing the role of beliefs, motivation, and self-efficacy. Learners' interpretations of their experiences (whether they see effort as worthwhile or failure as informative) directly influence whether learning persists and transfers. People have agency to influence their own behavior and learning environments in purposeful ways, and this sense of agency shapes engagement and outcomes.

From a sociocultural perspective (Scott & Palincsar, 2012), learning is not confined to individual minds. It is mediated by tools, social interaction, and cultural context. What and how people learn is shaped by the environments they inhabit and the expectations placed upon them. As Vygotsky argued, the social dimension of consciousness is primary, and individual development emerges from participation in culturally organized activities.

No single theory explains learning completely, but together they converge on a shared conclusion: learning is constrained, contextual, and fundamentally human.

The Learning Styles Myth

One of the most persistent myths in education is the belief that people learn best when instruction is tailored to their preferred learning style: visual, auditory, or kinesthetic. The appeal is understandable. The idea feels personalized, respectful, and intuitive.

The problem is that the evidence does not support it.

Research by Kirschner and van Merriënboer (2013) demonstrates that matching instruction to learning styles does not improve learning outcomes. What matters is not preference, but the structure of the material and the cognitive processes required to understand it. Visual information is effective when spatial relationships matter. Text is effective for precise definitions. Practice and feedback matter far more than modality preference.

Popular media has reinforced this conclusion. As illustrated in Veritasium's You Are Not a Visual Learner (Veritasium, 2021), learners often mistake comfort and familiarity for effectiveness. The danger of the learning styles myth is not only that it is inaccurate, but that it distracts designers and educators from strategies that actually support learning, such as structured practice, feedback, and attention to prior knowledge (Kirschner & van Merriënboer, 2013).

Designing instruction around preferences risks optimizing for ease rather than understanding, and in doing so, it quietly undermines learning itself.

Why Evidence-Based Learning Design Matters

Misunderstandings about learning do not merely lead to inefficient instruction; they lead to wasted time, misplaced confidence, and frustration for learners. When educational systems prioritize engagement metrics, surface activity, or personalization theater over learning outcomes, people sense the disconnect even if they cannot articulate it.

This matters even more as technology, and especially AI, becomes increasingly embedded in education and work. We now have the ability to scale instruction, automate feedback, and personalize experiences at unprecedented levels. Without a solid understanding of how learning actually works, we risk scaling ineffective or harmful practices more efficiently.

Evidence-based learning design is not about rigid formulas or one-size-fits-all solutions. It is about grounding decisions in research, testing assumptions against data, and remaining willing to abandon comforting myths when evidence contradicts them. Designers who understand learning science are better equipped to create environments that support real cognitive and behavioral change rather than the appearance of progress.

Designing for Change

If learning is defined by change, then educators, designers, and technologists have a responsibility to design for change, not merely for engagement, preference, or completion. That responsibility grows as educational systems become more automated and more scalable.

Learning is not a feeling. It is not an identity label. And it is not guaranteed by participation alone.

Learning happens, often slowly and unevenly, when experience reshapes how people think, act, and relate to the world. That is the standard worth designing for, and the one that evidence-based learning science helps us uphold.

What myths about learning have you encountered in your work? How do you stay current with learning science research? I'd love to continue this conversation. Connect with me on LinkedIn or explore my portfolio to see how I apply these principles in practice.

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