A Systems Approach to Formulating Knowledge

08 Jul, 2026

Translations: Traditional chinese

Introduction

Learning is an inherently personal process, yet the feedback mechanisms that guide it are often delayed or entirely absent. Exams assess mastery rather than the learning process itself, providing little insight into learning efficiency. Consequently, the ability to learn efficiently often remains a matter of personal judgment and, as such, an underappreciated skill.

Among high-achieving students, some seem to learn efficiently by instinct, while others reach the same level through exceptional effort. From the outside, both appear equally capable, making ambition, motivation, talent, and interest confounding factors in identifying effective learning. These qualities certainly influence performance, but they belong to the "art" of learning. Before refining the art, one must first master its fundamentals.

Evidence-based research on learning often focuses on individual “techniques¹” (e.g., flashcards, test-enhanced learning, the Pomodoro technique, etc.). This is hardly surprising. Learning is too complex to study holistically, making individual techniques the most practical unit of research. Yet, in my experience, even effective techniques can become detrimental when they evolve from tools into beliefs². We begin to neglect a technique's limitations, believing the obstacles we encounter reflect insufficient willpower rather than a flawed method.

A more effective approach is to develop what I will refer to throughout this article as a “learning system”. Instead of accumulating disconnected methods, a learning system provides a stepwise approach by first understanding the characteristics of the learning task, then choosing the most appropriate technique. The distinction is analogous to that between a shaman and a physician. A shaman may possess impressive or even seemingly miraculous remedies, whereas a physician works within a systematic framework that can be tested, refined, and improved through practice.

The strength of a learning system lies in its ability to evolve. By treating learning itself as a skill to master, the system can be continually refined through both scientific evidence and personal experience. The framework that follows reflects my experience as a medical student, though the underlying principles should extend well beyond medicine.

The learning system

Formulating knowledge comes in 4 steps.

• Priming
• Consuming
• Processing / Encoding
• Reinforcing

Priming

Ideally, the first step in any learning session is priming. Counterintuitively, priming occurs before the learning event itself, whether it is a lecture or a study session. It acts as a warm-up, preparing the brain to recognize incoming information as relevant and making subsequent learning more efficient.

In practice, priming can be remarkably simple. In my experience, merely skimming the material and developing a vague sense of what is to come the night before makes the actual learning process significantly smoother. Some consider priming one of the most powerful learning interventions as its effects extend throughout the entire learning process.

Consuming

Following priming comes the consumption phase: reading, listening, or otherwise acquiring information with the goal of understanding it.

A common mistake is placing too much emphasis on the volume of consumption. It is entirely possible to spend ten hours watching lectures or reading textbooks, understand everything in the moment, and yet retain very little afterward. This applies equally to conceptual information, such as algebra, probability, or topology, and evidence information (Midazolam 0.5 mg/kg and Rocuronium 0.5 mg/kg before endotracheal intubation). As one of my seniors often remarked, "Reading something once is almost the same as never having read it at all."

Processing / Encoding

The remark "Reading something once is almost the same as never having read it at all." is valuable, but it also exposes a common pitfall. The most intuitive response is simply to revisit the material, whether through repeated reading or more sophisticated strategies such as active recall and spaced repetition. What often develops instead is rote learning: information stored so rigidly that retrieval becomes recitation. True mastery begins with the ability to connect concepts and facts across disciplines. Achieving that requires the most cognitively demanding stage of learning: processing.\

First, step back and identify the big picture. At a minimum, you should understand the purpose of the current chapter and where it fits within the subject. Only then should you begin processing the information.

Not all information is learned in the same way. PACER Framework³ classifies learning material into five categories, each of which benefits from a different processing strategy:

P – Procedural Information
Information that describes how to perform a task (e.g., performing a physical examination or writing a computer program).

A – Analogous Information
Information that can be understood by relating it to knowledge you already possess (e.g., "The mitochondrion is the powerhouse of the cell.").

C – Conceptual Information
Theories, models, and principles (e.g., the physiology of respiratory sound).

E – Evidence Information
Details, data, and statistics that support conceptual information. (e.g., Concept: familiarity is different from recollection; Evidence: Hippocampal patients often exhibit more pronounced deficits on associative and source memory tests than on item recognition tests⁴.).

R – Reference Information
Specific details that are important to recall but require little conceptual understanding, such as definitions, dates, classifications, etc (e.g., Definition of sepsis: Life-threatening organ dysfunction (SOFA ≥2) due to infection).

In practice, many pieces of information belong to more than one category. The purpose of the PACER Framework is to guide the selection of the most appropriate processing strategy for a given type of information.

Procedural Information
The only way to master procedural information is through practice. Avoid spending excessive time memorizing procedures. Instead, apply what you learn as early and as often as possible.

Analogous Information & Conceptual Information
Although analogous and conceptual information are distinct, both require deep understanding, and many of the same learning strategies apply.\

Since analogous information is understood by relating it to knowledge you already possess, constructing analogies is one of the fastest ways to form meaningful connections. Then stress-test (critique) those analogies: ask where they succeed, where they fail, and whether better ones exist. The confusion that follows often marks the beginning of deeper understanding and more durable memory.

Take the classic analogy: "The mitochondrion is the powerhouse of the cell." Ask yourself: What does "powerhouse" actually mean for a cell? What kind of energy does it produce? How is that energy generated? By answering these questions, you naturally expand your understanding and uncover connections that the original analogy alone could not provide.

For conceptual information, after learning the concept itself, map how it relates to other concepts. A simple mind map is often enough. Even a crude sketch can organize isolated ideas into a coherent conceptual network.

The first draft of this article was little more than a messy tangle of ideas.

Another effective strategy for both types of information is explanation. Rewrite the material in your own words, simplify it as much as possible, and explain it as though teaching someone else. It may be mentally exhausting, but few methods reveal gaps in understanding as quickly.

Ultimately, the goal is not simply to "learn" concepts but to develop intuition⁵. Intuition, in this context, means reshaping your mental model until the concept feels self-evident rather than something that needs to be consciously recalled. This is achieved through deeper processing: examining an idea from multiple perspectives, modifying elements of the concept or problem, and so on. It is then verified by checking whether the solution can be reconstructed through reasoning rather than recall, indicating that intuition has developed.

Evidence Information & Reference Information
Evidence information requires deeper processing than reference information. When reviewing evidence information, rehearse by asking yourself how it is used, how it can be applied, and which conceptual principle it supports.\

Reference information, on the other hand, usually requires only direct fact recall. (Although periodic rehearsal is still beneficial.) After processing, I recommend storing both types of information in your own notes or flashcards for later reinforcement.

Reinforcing

For long-term mastery, knowledge can be reinforced through retrieval and interleaving.

Retrieval strengthens long-term retention and recall speed through repeated application of knowledge and space repetition (e.g., Anki flashcards). Interleaving promotes discrimination between related concepts by mixing different topics or problem types (e.g., a single mixed Anki deck), much like constructing a differential diagnosis.

A common mistake is to rely on reinforcement while neglecting the earlier stages of learning. Although it can compensate for weak foundations, it is inefficient as a primary strategy.

For readers unfamiliar with flashcards, Nicky Case's “How To Remember Anything Forever-ish” is a phenomenal introduction to spaced repetition. Dr. Piotr Wozniak's classic, “Twenty Rules of Formulating Knowledge”, is a must-read for the fundamentals of making flashcards. In my opinion, Anki is one of the best flashcard applications available, combining a robust spaced-repetition algorithm with the convenience of a digital platform. If you'd like to explore more tools that complement learning system, they are covered in a separate article⁶.

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Conclusion

The techniques presented here are only a means to effective learning. They can be adopted, adapted, or discarded as needed. I hope this article provides a framework for developing your own learning system and, more importantly, encourages us to share, challenge, and refine our learning systems together.

Reference