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Features of presenting educational material

Intelligence (a characteristic of intellect, showing how capable a person is of changing their behavior after receiving rational arguments) is better in humans than in cats. Cats are better than ants. You can explain things to humans once, but you have to train a cat through repetitions to achieve the desired behavior. Ants can't even be trained.

But no matter how intelligent people are, life shows that you can't learn how to ride a bike or drive a car just through explanations, you can't learn how to do something complex just through explanations. For example, you can't learn math just through explanations. You need to solve problems, do exercises. Simply reading a math textbook won't help. You need to repeat actions with the material in the textbook, keep your brain thinking about the topics in the textbook.

To master a certain cultural (following the best examples in the best available style, not just any style that happens) way of thinking, you need exercises, you need to perform a large number of repetitions of mental operations. The neural network learns through a large number of repetitions.

This also applies to mental operations of focusing attention on important objects. In our course, these important objects will be various systems that you need to learn to recognize, identify their boundaries, clarify their type, find relationships between them, describe them and their behavior, recognize their states.

Since you need to keep a student's brain focused on the materials of our course for at least the minimum necessary time for any kind of effective learning, these course materials are not well-structured reference materials resulting from the work of a scientific methodologist. No, these course materials primarily result from the work of an instructional designer, i.e., the work of a specialist in how to teach agents, primarily humans. Humans learn with a "wet" neural network, and its training requires repeated exposure to the training materials, preferably in different contexts.

In our course, the main focus is on assigning tasks to the student for textual (writing posts) and tabular (filling out tables with prescribed columns) modeling. In practice, the student spends most of the time working not with the "textbook" and the accompanying "workbook," but the other way around: as a modeler (writing posts and filling out tables), with the "textbook" attached as "contextual help" for the modeler. For every hour of work in the modeler, there may be only ten minutes of reading the "textbook." So reading the "textbook" may only constitute one sixth of the "course." If you quickly skimmed through the textbook (three times faster than reading carefully), you only mastered one eighteenth of the course material. If you read it carefully without completing the tasks, you mastered one sixth of the course. Of course, hoping to understand systems thinking without completing the tasks is not realistic.

For example, let's reiterate what was just said about the need for repetitions in different contexts, with a slight rephrasing. The main aspect in the course regarding the teaching methodology:

  • Keep the "wet neural network" of the student (i.e., yours) focused enough time on the concepts of systems thinking to provide the necessary time for neural network learning. Teaching the teacher's work can be automated, while the student's work cannot, as learning a neural network requires a large number of repetitions of operations involving a set of concepts.
  • The course material should somehow be repeated in various contexts to be effectively absorbed. This means that the repeated or even sequential re-reading of a piece of text multiple times, grouping several examples on one topic (in education, this is blocking), as usually done in reference literature, is intentionally avoided! The course is not a reference book! If you need information, you can ask an AI, which will provide information on the course material. Students (and if they are children, also their parents) often assume that structured concise presentation of material on one topic is easier to comprehend and better for future recall. But this is a misconception: experiments show that interleaving and spacing, while more challenging to comprehend, significantly improve learning results[1].
  • Certain text fragments are repeated at various points in the course, sometimes after a couple of paragraphs, sometimes after a dozen pages, sometimes after a hundred pages. And not just once - some thoughts are repeated dozens of times! Repetitions are also intentional; the text considers the necessity of repetition for the student's neural network learning, because the human brain is not a classic memory that remembers everything from the first exposure. Our course usually lasts a month to a month and a half, and by the end of studying the final sections, the content of the earlier sections can begin to fade. This is described by forgetting curves[2]. We understand that not everyone will be willing to go back and retrace the course "for review," especially halfway through the first reading, so we've incorporated some repetitions into a single read. Nevertheless, we are confident that it will be extremely useful to go through this course a second time, and not just this course, but the entire chain of courses in the "Organizational Development" program at THE School of System Management (which currently includes "Modeling and Coherence," "Systems Thinking," "Methodology," "Systems Engineering," "Engineering of Personality," "System Management," "Intelligence Stack," with more courses being developed). Why go through the entire chain? Because each subsequent course in the chain will add to the understanding of the material in the previous courses. If you are having difficulty understanding a section of the material, it is useless to repeatedly reread it (of course, if you read it slowly and attentively, not "skimming"), just move on: chances are an explanation will come in a few pages, and if you reach the end of the course, the explanation may come in the next course.
  • It's not that there are few repetitions embedded in the text of our course. What matters is that understanding when going through the entire chain of courses will be completely different! Experience shows that the second time the course is taken is "as if it were the first time": material is read and understood completely differently. However, this course is not different from any other complex text in this regard. Every complex text conveys a complex network of ideas. Sequentially describing the graph inevitably leads to "forward references" to concepts that are not yet well understood. Here, the only option is a double pass: the first time to get acquainted with the concepts, and the second time to understand all the connections between the already familiar concepts. Explaining the connections between poorly understood concepts is useless: it will be ignored and forgotten.
  • Terminology for the main concepts of the course is intentionally not defined unambiguously: synonymic series/"trains" are used everywhere in the text. You won't be able to quickly skim through a phrase to understand it! Your eyes will stumble upon long strings of synonyms. Terms such as Method/practice/activity/style/culture/work type - will be encountered throughout the text. Each time you need to consciously understand not only the words written, but the concepts implied by this range. This is also intentionally done in the course. In real life, you won't encounter words from the course (you don't encounter "physical bodies" in life, although the physics textbook is about them), and the course doesn't feature words from life (the physics textbook does not describe the flight of an empty bottle into the trash, but describes the flight of a physical object somewhere unknown). Our course prepares you for this situation: mapping the types from the course to objects from life is not based on the similarity of names (words), but on the similarity of concepts (mental models behind the words used as terms)! Reading the course text becomes slower and more deliberate, but this is good: it is a continuous benefit to the neural network of your brain! The use of the slash for synonymic series is quite common in engineering and in English texts, but it is not recommended in literary Russian texts, and we are aware of this[3], but we ignore it in our case.

Learning turns out to be one of those rare cases where "spacing," "dispersion," "repetition," and unfixed terminology are beneficial for the result. Of course, they extend the learning time, but we see this as a beneficial phenomenon: "increasing the time during which the brain works with the course concepts." This beneficial extension of time is the goal! We need to keep your neural network engaged with the concepts of the course, and the results in terms of developing systems thinking will be better.

In the Systems Thinking course (which is not covered in the book, so we strongly recommend taking the course in Aisystant rather than just reading the book), you will need to:

  • Answer questions and provide explanations for these answers,
  • Engage in modeling in tables,
  • Complete tasks and record your thoughts after completing them in posts.

Do not hesitate to provide justifications in responses to questions: this will improve your fluency in using the terminology. Instead of relying on "vague feelings" of correctness or incorrectness of answers, "mumbling in your mind" (the "ummm" in your mind as a guess about the answer will remain nameless, and yet the goal of answering the questions is to master the terminology, remember the arguments), you will have to express reasoning about the correctness of an answer with some text, and the terms will stop "being on the tip of your tongue" without being remembered after completing the course. This educational training in writing justifications for answers is very helpful when you later communicate with colleagues in a work situation after a month or two. After all, you can't tell a colleague an argument in the form of "ummm, I have a feeling the answer is this, but I can't remember why." The argument must be clear and expressed in words, not just "ummm" in your mind. Most likely, you will have to look back at the textbook to recall the argument, remember the terms, and write an explanation.

Here is a typical comment from a student[4]:

Yes, it seems that the real game changer is only the exercises.

I remember reading the 2015 text semi-consciously, where about 20% (I did not understand why I needed all of this), just downloaded it with one button. It was tough to go through, of course. When I read the new version (from last year), suffering from how everything was slow, liquid, and repetitive. I assess the recall of information from both cases as equal. Only the course with exercises really cleared the brain fog.

"Only the course with exercises cleared the brain fog" - this is what everyone says after completing the exercises. But only one in ten students undertaking the course actually completes the exercises. We hope you are that one student. If you don't engage with the exercises, if you don't work on the tasks, then the brain fog will remain, and there will be no benefit from "reading the course" (and not "completing the course," which implies task completion).

We do not recommend taking notes/summarizing the course material in the textbook, nor do we recommend underlining individual phrases - these are student legends about how to study, but numerous experiments have shown that it is useless and does not improve the assimilation of the material. We recommend writing short texts on all the new ideas that come to you as you progress through the course, in the genre of "essays," not "summaries/cheat sheets." Publishing these notes can be very helpful for learning, for example, in our systemsworld club[5]. An account on some social network will also work, although it will be more challenging to receive interesting comments there, but even these comments are not as important here. Your own thoughts, your own models that come to you as you go through the course - they are important, don't lose them. Search for words for them, write them down, and not so much to share these thoughts with the world, but to keep your neural network engaged with the material of the course for a while longer. For the training of a neural network (whether it is the neural network of a human or implemented by a silicon or even a quantum computer) to a certain set of concepts, the network needs time to work with the material containing those concepts. This educational writing/modeling strategy[6] has proven to be very effective. Once again, what you write is not for an external audience, but for yourself: it is just time maintaining your neural network engaged in reflecting on the course material[7].


  1. article in which this effect is described in experiments detailed for one class of tasks, but there are references to similar effects for other classes of tasks: M. S. Birnbaum, E. L. Bjork, R. A. Bjork, Department of Psychology, University of California, Los Angeles, "Why interleaving enhances inductive learning: The roles of discrimination and retrieval", https://yadi.sk/i/UPRTP0DxRpw8Vg ↩︎

  2. https://en.wikipedia.org/wiki/Forgetting_curve ↩︎

  3. https://bureau.ru/soviet/20140629/ ↩︎

  4. https://t.me/ailev_blog_discussion/23418 ↩︎

  5. https://systemsworld.club/ ↩︎

  6. https://ailev.livejournal.com/1513051.html ↩︎

  7. https://www.youtube.com/watch?v=MnCV3sOkVVw ↩︎