The best way to acquire knowledge from reading.

Repost Instructions

This article is authorized for reposting, and the author is Alan Chan, the founder of Heptabase. The original article can be found at The Best Way to Acquire Knowledge from Readings.

During the reposting process, some typos were corrected, and the expressions in Taiwanese Chinese were replaced with Mainland Chinese, such as "软体 → 软件" and "实作 → 实现".



As someone who frequently reads, the most challenging aspect of reading for me is that the best books often contain a large amount of content, and it is not always easy to fully digest this content. Even if I do digest the content, over time, it is often difficult for me to recall what I have learned solely from memory when I suddenly want to apply the knowledge in my work.

This problem is not unique to me; it also happens to many people I know. I believe this is the problem that most note-taking software (also known as knowledge management software) aims to solve. Unfortunately, I feel that most note-taking software focuses too much on teaching you how to organize notes using different structures (e.g., hierarchy, network, database) and lacks improvement solutions for the most critical aspects of the learning process, such as knowledge acquisition, retention, and application.

In this article, I will share practical examples of my own learning and demonstrate a method I have designed using Heptabase to effectively acquire, retain, and apply knowledge. Although this method is not the only way to learn, it is a method that I have verified to be highly effective, and I believe most people can quickly learn to apply it to their own learning.

Method Overview

The well-known Feynman learning technique suggests that the best way to deeply learn a topic is to try teaching it to a child. My idea is that no matter what you want to teach others, you must first clarify the knowledge structure you want to teach and find a way to express this structure clearly. In the method I propose, we can achieve this through five simple steps:

  1. Record all important paragraphs seen during the reading process.
  2. Break down the recorded paragraphs into smaller concepts.
  3. Draw connections between the concepts.
  4. Group similar concepts together.
  5. Recall and use the concepts.

The following video shows the process of practicing these five steps. The video is a recording of a real case study and was not planned in advance. In this video, I demonstrate how I break down the concepts in the book Mindstorms: Children, Computers, and Powerful Ideas and gain a deep understanding. You do not need to watch the entire video (as it is four hours long), but quickly skimming through different sections of the video will give you a clearer understanding of how I extract ideas from books and build understanding. If you want to play around with the whiteboard I created in the video, you can click on this link.

Step 1: Record all important paragraphs seen during the reading process

In the first step of my methodology, we need to record the important paragraphs seen during the reading process and organize them by chapter. The implementation of this process may vary depending on the tool you use. If you are using a computer e-reader, you can directly copy and paste the text from the e-book into a Heptabase card. If you are using a Kindle or iPad e-reader, you can export all highlights as a Markdown document and then import it into Heptabase. If you are reading a physical book, you can take notes after finishing each chapter.

Regardless of the method you use for note-taking, make sure that you eventually produce a book card that includes the important paragraphs you recorded from different chapters of the book.


Step 2: Break down these recorded important paragraphs into smaller concepts

Once you have organized your reading notes into a book card, you can create a whiteboard and import the book card from the Card Library into this whiteboard using the Import Panel in the top right corner of Heptabase. For example, I created a sub-whiteboard called Mindstorm under the Reading Notes parent whiteboard and placed the card notes from the book Mindstorms on this sub-whiteboard.


After placing the card, I will open it in the right sidebar for easier browsing of its content. I usually quickly scan through all the content on this card and identify several concepts that I consider important. When I decide to extract a concept, I will select the blocks related to this concept and drag them onto the whiteboard to create a new card.


Creating the card is not enough; I will also summarize the core concept of the card in one sentence and use this sentence as the card title to ensure that it is clear what the card is about at a glance. Next, I will reorganize the content within this card to make its structure more intuitive. I will also check if there are any blocks in the original book card that are relevant to this concept card, and if so, I will drag them into this concept card.


Step 3: Draw connections between these concepts

As I extract more and more concept cards from the book card, I will gradually start drawing arrows between these cards or grouping together cards with similar content. If I find that two concept cards discuss the same idea, I will merge them. If I find that a card contains too many concepts, I will break it down into smaller cards to maintain granularity.


Step 4: Group similar concepts together

After converting all the content from the book cards into concept cards, I will close the right sidebar and focus on establishing the connections and grouping relationships between these concept cards. When I find multiple cards related to a subtopic, I will group them together using a section and give the section a name. When naming a section, I am as cautious as when giving a title to a card, as these names will be the first thing you see when reviewing the whiteboard in the future.


After completing the final layout of the whiteboard (including all arrows and sections), I will paste the links to all the sections back into the original book card, and Step 4 is complete. Completing Steps 2 to 4 usually takes one to several hours, depending on the length and depth of the book.

In this process, the real value lies not in the final whiteboard you produce, but in the thought process you put into establishing the knowledge structure and giving titles to each card and section during Steps 2 to 4. True understanding and insight often come from the process of breaking down and reorganizing knowledge. Only after going through this process will this knowledge truly become your own.


Step 5: Recall and use these concepts

Once you have produced the final whiteboard, the stage of knowledge acquisition is complete. If you want to retain this knowledge, I would recommend using the theory of spaced repetition to schedule reviews of the whiteboard.

Based on my experience, even if I do not use spaced repetition, I am still able to know which knowledge should be in which whiteboard and directly find the concept cards I need in that whiteboard while working. Therefore, while reviews are beneficial, you do not need to be too strict with yourself and strictly follow a schedule.

In the long run, saving knowledge in the form of concept cards on a whiteboard will bring great benefits.

For example, suppose you are researching how to improve children's memory, and you have read five books in the past that mention ideas related to this topic to some extent. In this case, you can create a whiteboard called "Improving Children's Memory" and reuse the concept cards related to this topic from the whiteboards of those five books to establish a new understanding structure in this new whiteboard. This way, your past learning is no longer just lying quietly in a folder but can become the foundation of your new research. You can even combine these concept cards to quickly and directly produce a thematic article.


Although this article discusses the methodology of knowledge acquisition, retention, and application, I want to emphasize the importance of tool selection because the design of the tool often subconsciously changes our perception of learning and develops good and bad learning habits.

Seymour Papert, one of the pioneers of artificial intelligence and the constructionist movement in education, explores the idea of how tools influence thinking in his book Mindstorms:

For me, writing means drafting a first version and then working on it for a long time to revise and improve it. My image of myself as a writer includes a "rejected" first draft that is polished into the final presentation through continuous editing. But if I were a third-grade student, I could not imagine doing this because the physical act of writing is slow and laborious, and I do not have a secretary to help me write. For most children, rewriting an article is so laborious that the first draft becomes the final version, making it impossible for them to develop the ability to critically review their own writing. However, when children have a word processor, this situation changes dramatically. The first draft becomes something created on the keyboard, and correcting errors becomes easy. The current version is always clean and tidy. I have seen a child go from refusing to write to actively participating (with rapid improvement in quality) after using a computer for writing for a few weeks. This situation becomes even more dramatic when children have difficulty or even impossibility in handwriting due to physical disabilities.

Word processors can make children's writing experience more like that of a real writer. However, this point can be weakened if the adults around them, including teachers, cannot appreciate the writer's experience. For example, it is easy to imagine that adults would express the following views: modifying and re-editing text is a waste of time ("Why not do something new?" or "You didn't make it better, why not correct your spelling?").

Writing, music composition, skill games, complex graphics, and so on can all be viewed in the same way: the computer is not an independent culture, but it can be used to promote very different cultures and philosophies.

When building Heptabase, our goal was to design an environment that allows you to externalize the process of learning knowledge in your brain, enabling you to use your eyes and hands to recognize, break down, connect, and group concepts. This is why we developed features such as breaking down cards, moving blocks between cards, establishing card relationships on a whiteboard, and reusing cards across multiple whiteboards. These features together create an environment that allows you to better utilize human visual understanding and visual memory abilities, as well as the computer's data persistence and retrieval capabilities for learning. As you use this tool for a longer time to establish structures for your learning, you will subconsciously turn the learning method described in this article into your own habit, and this is the most important thing—tools not only allow you to take notes but also make you a person skilled in learning.

Ownership of this post data is guaranteed by blockchain and smart contracts to the creator alone.