## Introduction Learning is a very complicated cognitive process. Not only is it complicated, it is shrouded in an endless sea of noise disguised as study tips, learning "science", and advice. Much of these ideas are contradictory, out of context, or simply ineffective, and do more harm than good. Yet, despite being complicated, we are all able to learn. Everybody learns, all the time. It is part of our biology and our condition. From the moment we are born, we begin absorbing information, developing skills, and adapting to our environment. However, we yearn to be better. We yearn to be smarter. To know more. To be able to do more. This is why learning efficiency is important, and why we care about accelerated learning. In a world where knowledge expands exponentially and skills become obsolete with increasing rapidity, the ability to learn effectively becomes not just an advantage but a necessity. You only learn something once. The time you spend learning something is time you never get back. If you could take a shortcut to learn the same thing with the same quality in less time, you would take that shortcut every time. The destination of learning is always the goal. Even the "love of learning" is really just curiosity that only gets satisfied when you have learned the answer, never while you're figuring out the question. To effectively try and learn better, we must first try to understand learning itself. What happens when we learn? How do different aspects of our psychology, environment, and behaviour interact to create lasting change in our capabilities? Learning is also very personalized, but how so? What makes one approach work brilliantly for one person yet fail completely for another? These questions highlight the need for a comprehensive framework that can accommodate both universal principles and individual variations. We need a framework to understand learning. Understanding here means having an effective way to organize knowledge, to comprehend the different parts of learning and how they connect with each other. Without such a framework, our efforts to improve learning remain ad hoc and potentially misguided. ## What is A System of Learning? A System of Learning (SoL) is a framework that helps us understand the process of learning, what parts go into it, and where and how we might improve our own learning process. It is only with understanding that we can really begin to innovate sustainably. Too often, learning interventions focus on isolated techniques without considering how they fit into the broader process of knowledge acquisition and skill development. SoL addresses this limitation by providing a holistic view that encompasses the many facets of learning. SoL is characterized by three key aspects. First, it functions as a framework, providing a structured way to think about and discuss learning. SoL creates a conceptual architecture that organizes the components of learning into a coherent whole. This structure allows us to see relationships between elements that might otherwise remain hidden. Second, SoL is descriptive, not prescriptive. It does not claim any underlying existence or make assertions about how learning "actually" works in some objective, universal sense. It describes things only so much as for it to make sense to us, helps us gain clarity, and makes the foggy more clear. Third, SoL is ongoing and evolving. It is not a finished framework. It evolves with time and prioritizes practical utility over technical consistency. Its goal is to help us understand, and if there are inconsistencies and paradoxes, that's just a feature. This flexibility allows SoL to incorporate new insights and adapt to changing contexts without becoming rigid or dogmatic. The aims of SoL are multifaceted and practical. It acts as a foundation framework to navigate the complex process of learning, helping learners and educators make sense of the bewildering array of methods, techniques, and approaches available. It provides vocabulary and helps describe certain parts of the learning process, giving us words for phenomena we experience but may struggle to articulate. Clarity is the most important aim, because solutions become easy once the problem is clear. When we can see the components of learning and their relationships clearly, we can identify leverage points for improvement. Finally, SoL bridges theory and action, as a framework should, connecting abstract understanding with concrete strategies for enhancing learning in practice. ## The Components of the System of Learning ![[A System of Learning 2025-01-18 16.33.35.excalidraw.png]] The central unit of SoL is **cognition**. At the end of the day, learning can be thought of as the change between your mental state from one moment in time to another moment in time. If your mind is different now compared to when it was before, you have learned. Any change in your mental state is done through cognition. Whether you're memorizing facts, developing intuition, or acquiring a physical skill, cognitive processes mediate the transformation from not knowing to knowing, from inability to ability. Cognition is defined as any operation you perform on information. This broad definition encompasses the myriad ways in which we process, manipulate, and interact with data from our environment and our own minds. Within the SoL framework, cognition is divided into three interconnected domains, each playing a vital role in the learning process. Conscious cognition includes every thought you are aware of. In learning, this involves active problem-solving where you deliberately work through challenges, applying logic and reasoning to find solutions. It includes focused attention, where you direct your mental resources toward specific information or tasks, filtering out distractions to enhance processing. Deliberate practice falls under conscious cognition as well, involving structured, effortful activities designed to improve specific aspects of performance. Reflection is another crucial aspect, where you consciously examine your understanding, experiences, and progress, drawing insights that deepen learning. These conscious processes form the visible part of learning—what we typically think about when considering educational activities. Unconscious cognition encompasses all processing that happens in the back of your mind, beyond your immediate awareness yet profoundly influencing learning outcomes. Pattern recognition operates largely unconsciously, allowing you to detect regularities and structures without explicit analysis. Memory consolidation happens primarily during sleep and rest periods, strengthening neural connections and integrating new information with existing knowledge. Intuition emerges from unconscious processing, providing insights that feel immediate rather than reasoned through. Even when you're not actively thinking about a problem, background processing continues, sometimes resulting in sudden realizations or solutions. These unconscious mechanisms explain why taking breaks and allowing incubation time often leads to breakthroughs in understanding. Not all information processing has to be done in your own mind. External cognition refers to the ways we extend our thinking beyond our biological brains. Computers can perform calculations with speed and accuracy that far exceed human capabilities. Writing notes can help store information, reducing the burden on working memory and creating retrievable records. Tools like spaced repetition apps can track optimal review schedules based on forgetting curves. Collaborative thinking allows us to leverage the cognitive resources of multiple minds. Environmental arrangements can offload memory requirements through strategic placement of reminders or resources. This distributed approach to cognition recognizes that learning happens not just within individual minds but through interaction with technologies, artifacts, and social systems. The rest of SoL frames the surrounding context around how and what exactly we do cognition with. These additional components provide a comprehensive picture of the learning process, addressing not just how information is processed but also what drives learning, what it builds upon, what it aims toward, and what enables it. Prior knowledge forms the starting point of any learning journey. What you already know forms the foundation upon which new knowledge will be built. This includes not just facts and information but also conceptual frameworks, mental models, skills, experiences, and even misconceptions that may need to be corrected. Learning never happens in a vacuum; it always connects to and builds upon what came before. The effectiveness of new learning largely depends on how well it integrates with this existing knowledge base. When prior knowledge is robust and relevant, new information can be assimilated more easily. When it's sparse or contains errors, learning may require more effort or preliminary work to establish appropriate foundations. Learning is goal-oriented. Our learning process must be defined by what we aim to achieve, whether that's mastering a specific skill, understanding a concept, solving a problem, or achieving broader personal or professional development. Goals provide direction, helping to focus attention and resources on what matters most. They also offer criteria for success, allowing learners to assess progress and determine when sufficient mastery has been achieved. Well-formed goals strike a balance between ambition and achievability, providing challenge without overwhelming the learner. They also evolve over time as understanding deepens and new possibilities emerge. We keep track of where we are in relation to our goal using state. State is simply a description of where we are, and it also accounts for the temporal dimension of our system. It encompasses what you currently know and can do, your level of confidence and comfort with the material, and your awareness of what remains to be learned. Monitoring state allows for metacognition—thinking about your thinking—which is essential for regulating the learning process. Effective learners regularly assess their state, identifying strengths to leverage and gaps to address. This self-awareness guides adjustments to strategies, resources, and goals, ensuring that learning efforts remain productive and aligned with intentions. To learn new information, we have to get that information from somewhere. That somewhere we call a resource. A resource is anything that we learn from, be it a teacher, a book, or even feedback from practice. Resources vary enormously in their quality, accessibility, and appropriateness for different learning needs. They include not just content sources like textbooks, articles, videos, and lectures, but also tools, environments, and people who support the learning process. The effectiveness of resources depends on their match to the learner's goals, prior knowledge, and preferred learning approaches. The best resources present information in ways that facilitate understanding and retention, provide appropriate challenges, and offer useful feedback. To make progress, we must take action. It is action that leads to cognition. Without active engagement, even the best resources and clearest goals remain unrealized potential. Actions in learning include studying, practicing, experimenting, applying knowledge in different contexts, seeking feedback, and reviewing what's been learned. The quality, consistency, and appropriateness of these actions largely determine learning outcomes. Effective actions are deliberate and aligned with goals, leveraging appropriate resources and responding to feedback. They balance challenge and achievability, pushing boundaries without creating overwhelming frustration. Finally, we need drive to take action. Drive encompasses motivation, interest, determination, and all the psychological forces that initiate and sustain learning efforts. It's influenced by both intrinsic factors like curiosity and enjoyment, and extrinsic factors like rewards, requirements, and social expectations. Drive affects not just whether learning happens but also its quality and depth. When drive is strong and positively oriented, learners engage more deeply, persist through difficulties, and find greater satisfaction in the process. When drive is weak or negatively oriented (as with avoidance or fear-based motivation), learning tends to be shallower and less durable. Nurturing positive drive is therefore essential for sustainable learning success. To summarize: Learning has occurred when there is a change in mental state between two points in time, facilitated by the interplay of cognition, prior knowledge, goals, state awareness, resources, actions, and drive. ## The Complex Nature of the System While the diagram above shows a simplified directional flow of the framework, SoL is actually a **complex system**. This means every single component is connected to every other component in intricate ways, creating a web of relationships that defies linear representation. ![[A System of Learning 2025-02-13 17.51.51.excalidraw.png]] The complexity of these relationships becomes apparent when we consider concrete examples. Your goal influences what resources you seek, but your available resources may also shape what goals seem feasible. Your drive affects what actions you take, but successful actions can enhance drive through positive feedback. Your prior knowledge determines how you process new information cognitively, but cognitive activities also continuously modify your prior knowledge. Your state influences how you engage with resources, but resources help change your state. These bidirectional and multilateral connections mean that changing any part of this system will affect every other part, sometimes in unexpected ways. This complexity has important implications for how we approach learning improvement. It suggests that isolated interventions targeting single components may have limited effectiveness if they don't account for ripple effects throughout the system. For instance, introducing a new learning technique (action) without addressing motivation (drive) or background knowledge (prior knowledge) may yield disappointing results. Conversely, small changes in key components can sometimes catalyze significant improvements throughout the system due to positive feedback loops and synergistic effects. Thus, while the original diagram is helpful in understanding the basic directional flow of the framework, ultimately, we have to apply each part individually, and from the ground up, while remaining mindful of the interconnections between components. Additionally, while I have presented concepts as whole units, each concept can be analyzed into smaller parts. These smaller parts are related to each other and also play a part in the whole. This hierarchical organization allows for multiple levels of analysis, from broad principles to specific mechanisms. ![[A System of Learning 2025-02-13 18.25.27.excalidraw.png]] Consider cognition as an example. At the highest level, we can talk about cognition as a unitary concept encompassing all information processing. At a more detailed level, we can distinguish between conscious, unconscious, and external cognition. Zooming in further, we can identify specific processes within each of these categories—within conscious cognition, for instance, we might examine attention allocation, working memory operations, and explicit reasoning strategies. This nested structure continues down to the level of neural mechanisms and beyond. This multi-level perspective offers several advantages. It allows us to choose the appropriate level of analysis for different purposes—broad frameworks for overall planning, detailed mechanisms for troubleshooting specific difficulties. It also highlights how interventions at different levels can produce similar outcomes through different pathways. For instance, improving learning might involve high-level strategies like goal setting, mid-level techniques like spaced practice, or fine-grained adjustments to attention management. Relations between concepts are also complex and span multiple layers of analysis: ![[A System of Learning 2025-02-13 18.55.41.excalidraw.png]] The cross-level relationships in SoL illustrate how components at different levels of abstraction interact with each other. For example, unconscious cognitive processes like memory consolidation (at a detailed level) influence overall state (at a higher level). Similarly, specific memory techniques (at a detailed level) may be selected based on broader goal considerations (at a higher level). These cross-level connections create a rich, three-dimensional understanding of learning that captures both the forest and the trees—the big picture and the detailed mechanisms. ## Applying the System of Learning Understanding the SoL framework allows us to analyze learning experiences and identify opportunities for improvement. By examining each component and its relationships to others, we can develop targeted strategies that leverage the system's complexity rather than being stymied by it. Consider the case of using Anki for vocabulary learning. Many learners approach vocabulary memorization by simply reading word lists repeatedly, often with limited success and high frustration. The SoL framework reveals why this approach is suboptimal and suggests more effective alternatives. From a cognition perspective, Anki utilizes external cognition by calculating optimal review times based on spaced repetition principles. This offloads the burden of scheduling from the learner's mind to the software, freeing cognitive resources for the actual learning task. Anki also works with unconscious cognition processes like memory consolidation by timing reviews to coincide with the theoretical forgetting curve, strengthening neural connections just as they begin to weaken. The conscious aspect of cognition comes into play during the active recall practice that Anki forces, which research shows is far more effective than passive review. Prior knowledge influences how effective Anki will be. Learners who already have some familiarity with the target language or related languages will find it easier to form meaningful associations with new vocabulary. They can leverage existing phonological patterns, etymological connections, or semantic networks to embed new words in their mental lexicon. Without such foundation, additional scaffolding may be needed to make the flashcards effective. The goal component becomes important in selecting what vocabulary to learn. Rather than trying to memorize an entire dictionary, effective learners identify high-frequency words, terms relevant to their specific interests or needs, or vocabulary that appears in their current reading materials. This targeted approach ensures that learning efforts align with practical outcomes. Anki excels at tracking state through its built-in analytics, which show retention rates, review history, and upcoming workload. This feedback allows learners to adjust their approach based on performance data, perhaps spending more time with challenging cards or modifying their deck structure to improve efficiency. The resource component extends beyond the Anki software itself to include the quality of the flashcards. Effective cards include context, example sentences, images, or mnemonic devices rather than mere word-translation pairs. They might also incorporate audio for pronunciation or color-coding for grammatical features. Action in this context involves not just the regular review sessions but also how the learner engages with each card. Active recall, where one tries to produce the answer before flipping the card, is far more effective than passive recognition. Elaborative encoding, where one forms rich associations with the new vocabulary, strengthens memory traces. Consistent, spaced practice over time yields better results than cramming. Finally, drive plays a crucial role in sustaining the Anki habit. Initial enthusiasm often gives way to boredom or procrastination as the novelty wears off. Successful learners find ways to maintain motivation, perhaps by tracking progress toward specific goals, celebrating milestones, integrating the vocabulary into authentic communication, or making the process more enjoyable through gamification. By understanding these components and their interactions, a learner can optimize their approach—perhaps by improving card design (resource), adjusting review frequency (action), connecting vocabulary to personal interests (drive), or setting more specific goals for how the vocabulary will be used in real-world contexts. The SoL framework helps identify that a learner struggling with programming might need to adjust their resources (finding more appropriate tutorials), actions (increasing deliberate practice), goals (setting more achievable milestones), or drive (connecting learning to personally meaningful projects). ## Limitations of the System of Learning While the SoL framework provides a valuable way to understand and improve learning, it has several limitations that should be acknowledged. Awareness of these limitations helps us use the framework appropriately and avoid overextending its applications. SoL is designed primarily from a knowledge learning perspective and has not yet fully expanded to include skill learning in all its complexity. While knowledge and skills are interrelated, skill development involves unique considerations like embodied learning, muscle memory, and performance under varying conditions that may not be fully captured in the current framework. Future iterations might more explicitly address these dimensions. The framework has no direct empirical grounding, as it is conceptual rather than declarative. It doesn't arise from specific experimental studies or claim to represent neural mechanisms accurately. Instead, it organizes observations and insights about learning into a coherent structure. This conceptual nature isn't necessarily a weakness—many useful frameworks operate at this level—but it does mean that SoL shouldn't be mistaken for a scientific theory with predictive power. SoL is focused on the learning goal itself and may not work well for understanding extended learning periods or lifelong learning dynamics. The framework assumes relatively stable goals and doesn't fully address how learning priorities evolve over longer timeframes. It may need extension to accommodate career-spanning learning journeys or the kind of open-ended exploration that characterizes much of informal adult learning. There are some overlaps between components that can sometimes create ambiguity. For instance, the line between state and prior knowledge can blur, as today's state becomes tomorrow's prior knowledge. Similarly, resources and external cognition share territory, as many tools serve both functions. These overlaps reflect the messiness of real learning but can complicate analysis in some cases. The interconnected nature of the system means that isolating variables for improvement can be challenging. When multiple components influence each other, determining cause and effect becomes difficult. A learning intervention might produce positive results through unexpected pathways or fail despite addressing what seemed to be the key limitation. This complexity doesn't invalidate the framework but does suggest humility in making predictions and interpreting outcomes. ## Conclusion A System of Learning (SoL) offers a framework to navigate the complex process of learning. By breaking learning down into interconnected components—cognition, prior knowledge, goal, state, resource, action, and drive—SoL helps us understand where improvements can be made and how different aspects of learning influence each other. Next we begin a deep exploration to each component of SoL and their sub components and interaction with other parts. TBC. # ============= 2025-03-05: [[A System of Learning 0.1]] (P) [[A System of Learning (Notes)]]