The Smoother Methodology
Smoother is the pedagogical methodology behind everything we build — a dynamic, personalized, evidence-based framework created by Carlos Miranda Levy. It treats learning not as content delivered, but as the transformation of the learner to perform effectively in their real environment. Not courses; learning experiences, designed from the learner's side.
Learning as transformation
Smoother begins from a single conviction: learning is not what is taught, it is what the learner becomes able to do. Every design starts from the Sujeto de Aprendizaje — the learner — their Entorno Real, the real environment where the learning will be applied, and their motivation. From there it works backward to results, impact, and structure. This is what we mean by learning-first, not teaching-first: teaching matters enormously, but it is in service of the learning, which is the subject.
Depth: a complete framework, not a slogan
Smoother is not a checklist or a mnemonic. It is a documented body of work — dozens of protocol documents covering the whole arc of learning design: the Learning Object, unit structures and core learning tasks, nineteen learning modalities, a rigorous evaluation model, and a multi-layer classification fabric aligned to international standards (ISCED, ISCO, the OECD Learning Compass 2030, and ESCO). Below are a few of the pillars.
The Learning Object
An eight-component structure — objectives, contents, knowledge, skills, competencies, expert capacities, prior and related knowledge — that turns a vague topic into a designed transformation.
19 learning modalities
From 15-minute nano-learning and microlearning to workshops, diplomados, bootcamps, and hackathons — a format for every context, energy level, and depth of commitment.
An honest evidence framework
Every typology is labeled for what it is — research-backed, synthesized, adapted, or original — so nothing hides behind borrowed authority.
Analytic evaluation
A rubric built from the Learning Object itself, producing a multi-component profile of what a learner can actually do — not a single reductive grade.
16 personal preferences
What used to be prescribed as "learning styles" is repositioned — per Pashler (2008) — as a menu of variety, not a diagnosis: perception, cognition, and collaboration honored without pigeonholing.
AI-in-learning patterns
A documented set of evidence-grounded design patterns — and named antipatterns — for using AI as a learning coach without letting it hollow out the thinking.
Academic and practical roots
The methodology stands on established instructional-design scholarship — Bloom's taxonomy, Gagné's conditions of learning, Kolb's experiential cycle, Merrill's first principles, ADDIE, and problem-based learning — and positions itself deliberately alongside frameworks like 4C/ID, SAM, and Understanding by Design: adopting what is proven, and naming honestly where it contributes something of its own. It is scholarship put to work, tempered by years of designing and delivering real learning, not theory for its own sake.
Evidence-based — and honest about it
Smoother's cognitive-science foundation draws on well-established principles of memory and learning: retrieval practice and spaced repetition (the Leitner system), self-explanation through the Feynman technique, deliberate and purposeful practice, and social learning through Vygotsky's zone of proximal development. Just as important is what it refuses to overclaim: where "learning styles" were once prescribed as a diagnosis, Smoother repositions its sixteen personal preferences as a menu of variety, following the evidence (Pashler et al., 2008). Techniques carry an explicit evidence label so you always know whether a practice is research-backed, synthesized, adapted, or original.
Innovation, grounded in practice
Smoother is not an idea on paper. It powers our Experience Learning Campus, where it has produced hundreds of learning programs and experiences across sectors and languages. Its original contributions — the Sujeto–Objeto–Entorno triad, the nineteen-modality catalog, nano-learning with a built-in honesty frame, a machine-readable composability graph, and a documented set of AI-in-learning patterns and antipatterns — come from extensive, hands-on experience building real learning at scale. Here, innovation is a track record, not a promise: we change education, but we change it well.
From theory to practice — throughout this site
We are not only about critical thinking and theory. These approaches are already at work in the tools, programs, and activities you can reach right now. Our live Experience Campus hosts hundreds of ready-to-run programs; the Learning Designer generates complete experiences on demand. We constantly create learning activities alongside educators, design fun video games that double as real learning experiences for students, and craft playful, personal study guides and interactive aids for exams — and much more, scattered across the site and renewed through frequent in-person and digital activities. Wherever you land here, the methodology is doing something. Go explore.
What persuades me is the labeling. Smoother tells you which of its parts are research-backed and which are synthesized or original — that intellectual honesty is rarer than it should be, and it is precisely what earns trust for the rest.
A methodology earns my confidence when it refuses to overclaim. Smoother repositions 'learning styles' as a menu rather than a diagnosis, and grounds its techniques in cognitive science instead of intuition. That restraint is how you protect learners.
The part I love: it has already built hundreds of real programs. This isn't a framework waiting for its first user — it's a working engine. And with everything from nano-learning to hackathons, there's a format for every kind of learner and every level of energy.
I created Smoother because I was tired of methodologies that centered the teacher's craft. Learning is the learner transformed to act in their real world — everything else is in service of that. Change education, yes — but change it well.
Comprehensive AI learning designed for educators, by educators. From awareness to mastery.