⭐ Learn & research a topic
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TL;DR
The purpose of visualizing notes is to gain a deep understanding of what you've learned. If all of your notes are very long and you don't break down the knowledge into smaller parts, the understanding you can gain from visualization will be very limited. Real deep understanding doesn't come from the "relationship between two books" but from the "relationship between all the concepts in these two books."
You can only gain a deep understanding of the topics you care about through visual note-taking when you atomize your notes. Atomic note-taking does not mean you cannot have long notes. It means that each concept card should only contain one concept and be supported by its content. To ensure clarity, you should always describe the concept in one sentence and use that sentence as the title of the concept card.
Foreword
I read a lot. For me, the most frustrating issue with reading is that great books often contain a high volume of content that is not easy to fully digest and integrate with my existing knowledge. Even when I fully digest the content, I often find it difficult to recall knowledge that I learned in the past purely from memory, which makes it hard to apply what I've learned to my current work.
I have met many people who face the same problem in learning, and this issue is what many note-taking (a.k.a. knowledge management) tools are trying to solve. Unfortunately, most of these tools put too much focus on how you store your notes (e.g., folders, graphs, relational databases, etc.) and neglect important aspects of learning such as acquisition (making sense of knowledge), retention (recalling past knowledge), and application (applying knowledge in a real-world scenario).
In this article, I will share a real-world example of how I developed an effective method for acquiring, retaining, and applying knowledge using Heptabase, a tool my team and I created for learning and research. While this is not the only workflow for learning, it has worked extremely well for me, and I believe almost anyone can apply it to their learning.
Method Overview
The famous Feynman learning technique suggests that the best way to develop a deep understanding of a topic is to teach it to a child. I would say that whenever you want to teach something, you need to first figure out the structure of the knowledge and be able to articulate that structure clearly. The method that I developed can help you achieve that with five steps:
- Highlight all important paragraphs while reading.
- Dissect the content of a book into granular concepts.
- Map the relationships between these concepts.
- Group similar concepts together.
- Integrate these newly learned concepts with previously known concepts.
Here's a screencast of how I conduct this process. This screencast is not staged. It's a real example of how I develop an understanding of a book I read called Mindstorms: Children, Computers, and Powerful Ideas. You don't need to watch it fully (it's 4 hours long!), but quickly skimming through different parts of the video will give you a clear sense of how I extract core concepts from the book and develop my understanding of it. If you want to explore and play with the whiteboard I created in the video, here’s the link to it.
[2024/01/03 Update] I have created a tutorial showing and explaning how I conducted the five-step process in action using Heptabase. I highly recommend you check it out!
Step 1: Highlight all important paragraphs while reading.
The first step in the process is to highlight important paragraphs from the book you have read and organize them by chapter.
Depending on the reader you use, the highlighting process may vary. If you are using a desktop reader, you can simply copy and paste the text into a Heptabase card. If you are using a Kindle or iPad reader, you can export all the highlights of the book into a Markdown file and then import it into Heptabase as a card. If you are reading a physical book, you can take notes in Heptabase whenever you finish reading a chapter.
It doesn't matter which tool you use to create highlights, as long as your output is one large card for the book that includes your highlights from different chapters.

Step 2: Dissect the content of a book into granular concepts.
Once you have the book card ready, you can create a whiteboard and add that card through the import panel of the card library. In my example, I created a sub-whiteboard named Mindstorm under the parent whiteboard Reading Notes, and dragged my Mindstorms book card onto this sub-whiteboard.

Once I have the card ready, I open it on the right split panel so I can better see its content. I usually start by skimming through all the content to identify key concepts. When I decide that there's a concept I want to extract, I select the related blocks and drag them out onto the whiteboard to create a new card.

Simply creating a concept card is not enough. To ensure clarity, I always describe the concept in one sentence and use that sentence as the title of the concept card. Then, I reorganize the content of the card into a structure that makes sense to me, and perhaps even drag other related blocks from the original book card into this concept card.

Step 3: Map the relationships between these concepts.
As I extract more concept cards from the original book card, I gradually add connections between them, or place similar concept cards next to each other. If I notice two concept cards are about the same idea, I merge them into one. At other times, I might break down a large concept card into several smaller ones to ensure granularity.

Step 4: Group similar concepts together.
After extracting all the content from the original book cards into concept cards, I close the split panel and start working on mapping and grouping relationships. Often, I find multiple concept cards related to the same sub-topic. In such cases, I group those concept cards into a section and add a name to that section. Naming the section should be done as carefully as naming a concept card because these are the things that you recall first when you revisit this whiteboard in the future.

Completing steps two through four typically takes anywhere from an hour to a full day, depending on the length and depth of the book. Once you've produced the final whiteboard, the knowledge acquisition phase is complete. In this process, what's truly valuable is not the final whiteboard you produce, but the thought process you invest while establishing the knowledge structure and titling each concept card and section during steps two through four. Deep understanding and insights often come from the process of deconstructing, reassembling, and describing knowledge in your own words. Only after going through this process does the knowledge truly become your own.
After completing the final whiteboard layout (including all arrows and sections), I will open the original book card in the right split panel of the whiteboard and re-paste the links to all the concept cards and sections back onto this book card. In the figure below, you can see that each link in this book card displays the title of a concept card. This is why, in the second step, I summarize each concept card in one sentence and use that sentence as its title. Only by doing so can I see the core concepts of this book without having to open the links of these concept cards when reading the book card.

For example, if I name a concept card's title as "Engineers’ subculture," looking back a few months later, it would be hard for me to recall what this card is specifically about. But if I name the title of this concept card as "Engineers who find BASIC easy to learn formed a subculture that is influencing the world of education to favor students who are most like that subculture," even without reading the content, I can recall the core concept in the future just by its title.
Step 5: Integrate these newly learned concepts with previously known concepts
Up to now, I have gained a deep understanding of the core concepts of the book Mindstorms by breaking down and connect its core concepts on a whiteboard. But just understanding this book is not enough; I also want to truly integrate all the knowledge I have learned in the past, present, and future. In other words, I want to integrate the concept cards of this book with the concept cards I wrote for other books and lectures in the past.
Before doing this, I want to share an important learning mindset: You can only gain a deep understanding of the topics you care about through visual note-taking when you atomize your notes.
Many people, when first using a visual note-taking app like Heptabase, continue to use the old way of note-taking and write one note for each book or lecture, resulting in very long notes that contain many concepts. When your notes are in this format, it's hard to gain value from visualization.
For instance, in the figure below, there are two book cards, each with a lot of content. Although the content of these two books is related, connecting these two book cards on a whiteboard does not provide any new value, as it is almost the same as putting them in the same folder.

The purpose of visualizing notes is to gain a deep understanding of what you've learned. If all of your notes are very long and you don't break down the knowledge into smaller parts, the understanding you can gain from visualization will be very limited. Real deep understanding doesn't come from the "relationship between two books" but from the "relationship between all the concepts in these two books." What you want to connect are not book cards, but individual concept cards that you extract from these books using the previous four steps.
For instance, I've recently been researching how to design a computer-driven dynamic medium, and both books Mindstorms and The Early History of Smalltalk are highly relevant to this research topic. To better conduct this research, I created a whiteboard called Dynamic Medium and reused concept cards related to Dynamic Medium from these two books, organizing them using a mindmap to establish a unique understanding framework.
It's because I extracted and atomized the most important knowledge and ideas from these two books into reusable concept cards in the past when I read them, so that I can now easily apply my previous learning to new research topics. My past knowledge no longer sits uselessly in folders, but instead becomes the foundation for my newest research work!

Note: Atomic note-taking does not mean you cannot have long notes. It means that each concept card should only contain one concept and be supported by its content. If the content is long but all of it can be used to support the concept in the title, then the card is still an atomic concept card.
How to Learn and Research
After sharing how I implement the learning methodology in Heptabase, I would like to summarize the core ideas that underlie this methodology:
- I believe that the essence of learning and research is to break down and extract the important concepts from books, literature, lectures, and experiences. Then, one should connect, understand, and internalize these concepts in one's own way to build a deep understanding of what is known and unknown to humans.
- I believe all work plans and research papers are simply products of transforming this deep understanding into executable and communicable forms.
Under these core ideas, the processes of learning, research, planning, and output can be fully presented in the following diagram:

In this figure, on the left is source, which are the "literature cards" you wrote down while reading or attending lectures.
During my learning and research process, I extract useful concepts from these literature cards to create atomized "concept cards." Each concept card describes the concept in one sentence in the title and cites content from one or multiple pieces of literature to support this sentence. Every citation deepens my understanding and reflection of this concept.
As I learn and research, the original content of the literature cards will gradually be replaced by links to many concept cards. As I extract these concept cards from the literature cards step by step, I need to connect and fit them into a structure that makes sense to me. I can only truly understand and internalize a topic when I find such a structure for it.
In the future, whether I'm writing academic papers, work plans, or online articles, my process will involve linearly reassembling these concept cards into an "output card," which is an article meant for others to read. As I absorb and break down more and more "sources" during research, my "understanding" in the middle will deepen continuously, and the "output" on the right will naturally be of higher quality.
Closing thoughts
Although the topic of this article is about my method for acquiring, retaining, and applying knowledge, I do want to stress the importance of choosing the right tool to do so, because the design of a tool can radically change the way we subconsciously approach learning and form good and bad habits for it.
Seymour Papert, one of the pioneers of artificial intelligence and the constructionist movement in education, discusses his thoughts on this in Mindstorms:
For me, writing means making a rough draft and refining it over a considerable period of time. My image of myself as a writer includes the expectation of an “unacceptable” first draft that will develop with successive editing into presentable form. But I would not be able to afford this image if I were a third grader. The physical act of writing would be slow and laborious. I would have no secretary. For most children rewriting a text is so laborious that the first draft is the final copy, and the skill of rereading with a critical eye is never acquired. This changes dramatically when children have access to computers capable of manipulating text. The first draft is composed at the keyboard. Corrections are made easily. The current copy is always neat and tidy. I have seen a child move from total rejection of writing to an intense involvement (accompanied by rapid improvement of quality) within a few weeks of beginning to write with a computer. Even more dramatic changes are seen when the child has physical handicaps that make writing by hand more than usually difficult or even impossible.
Word processors can make a child’s experience of writing more like that of a real writer. But this can be undermined if the adults surrounding that child fail to appreciate what it is like to be a writer. For example, it is only too easy to imagine adults, including teachers, expressing the view that editing and re-editing a text is a waste of time (“Why don’t you get on to something new?” or “You aren’t making it any better, why don’t you fix your spelling?”).
As with writing, so with music-making, games of skill, complex graphics, whatever: The computer is not a culture unto itself, but it can serve to advance very different cultural and philosophical outlooks.
When building Heptabase, we aimed to design an environment that empowers you to externalize the process of identifying, dissecting, connecting, and grouping the concepts you have learned. That's why we built features such as the ability to dissect cards, move blocks across cards, build card relationships on a whiteboard, and reuse cards across multiple whiteboards. Together, these features form an environment that leverages the human capability of visual comprehension and visual memory with the computer's capability of data persistence and retrieval. With continued use of the tool to create understanding of your learning, you will start subconsciously adopting the habit of using the learning method described in this article. This is what ultimately matters—not just helping you take notes, but helping you become better at learning.

本文重點
將筆記視覺化的目的,是對你所學的知識建立深度理解。如果你的每一個筆記都非常長、如果你沒有把知識打碎、原子化,你能透過視覺化獲得的理解就會非常有限。真正的深度理解並不存在於「二本書之間的關聯性」裡頭,而是存在於「二本書中的所有概念之間的關聯性」裡頭。
只有當你將筆記原子化時,你才能透過筆記視覺化對你在乎的主題獲得深度理解。原子化指的並非你不能有很長的筆記,而是指每個概念筆記都只應包含一個概念,並以其內文來支撐這個概念。你必須能將每張概念卡片的核心概念用一句話總結,並以這句話當做是卡片標題以確保你一眼就能知道它在講什麼。
前言
身為一個時常閱讀的人,閱讀最讓我感到困擾的地方在於那些最好的書往往包含大量的內容,要完全地將這些內容消化、與我的既有知識整合有時並不容易。就算我將內容消化了,時間一久,當我在工作時突然想用以前所學的知識時,往往也很難單靠大腦記憶就回想起過去的所學。
這個問題不只發生在我身上,也發生在我認識的許多人身上。我想這也是大部分筆記軟體(又稱知識管理軟體)想要解決的問題。但不幸的是,我覺得大部分的筆記軟體都過度專注在教你用什麼架構去保存筆記(例:階層、網狀、資料庫),卻沒有在**吸收知識(acquisition)、留存知識(retention)和應用知識(application)**等學習過程中最關鍵的環節提出改善方案。
在這篇文章中,我會分享我自身學習的實際案例,展示我設計的一個用 Heptabase 來有效獲取、留存和應用知識的方法。這個方法雖然不是學習的唯一方法,但是一個我驗證過極為有效的方法,而且我相信大部分的人都可以很快地學會將它應用在自己的學習中。
方法簡介
著名的費曼學習法認為深度學習一個主題最好的方式,就是嘗試把你在學習的主題教給小孩。我的想法是不管你想要教別人什麼,你都必須先釐清你要教的知識架構,並且有辦法把這樣的架構清楚地陳述出來。在我提出的方法中,我們可以透過五個簡單的步驟達到這件事情:
- 將閱讀的過程中看到的所有重要段落記錄下來
- 將紀錄下來的重要段落拆解成顆粒度更小的概念
- 畫出概念之間的關聯性
- 將相似的概念群組起來
- 將這些新學到的概念與過去所學的已知概念整合
下面這支影片是我實踐前四個步驟的過程。這支影片是一個真實案例的錄影,完全沒有經過事先的規劃。在這支影片中,我示範了我怎麼拆解 Mindstorms: Children, Computers, and Powerful Ideas 這本書的概念、獲得深度的理解。你不需要把影片看完(因為它長達四小時),但快速的看過 影片中的不同段落會讓你更清楚我從書本提取想法和建立理解的方式。如果你想玩玩看我在影片裡建立的白板,可以點擊這個連結。
[2024/01/03 更新] 我錄了一支教學影片示範並講解了我使用 Heptabase 執行這五個步驟的方式,大力推薦你看一下。
第一步:將閱讀的過程中看到的所有重要段落記錄下來
在我的方法論的第一步中,我們會需要把在閱讀過程中看到的重要段落記錄下來並且按照章節整理。這個過程的實作方式可能會根據你使用的工具而有所不同。如果你用的是電腦的閱讀器,你可以直接將文字從電子書複製貼上到一張 Heptabase 的卡片裡頭。如果你使用的是 Kindle 或 iPad 閱讀器,你可以把所有 Highlight 匯出成 Markdown 檔案再匯入到 Heptabase 裡頭。如果你讀的是實體書,你可以在每一個章節讀完時做一次筆記。
不管你採用哪種方式做筆記,你只要確保最終會產出一張書籍卡片,裡頭包含書中你在不同章節所紀錄的重要段落即可。

第二步:將這些紀錄下來的重要段落拆解成顆粒度更小的概念
當你將讀書筆記整理到一張書籍卡片以後,你可以創建一個白板,並透過 Heptabase 右上角的 Import Panel 將書籍卡片從 Card Library 匯進這個白板裡頭。舉例來說,我在 Reading Notes 這個母白板下創建了 Mindstorm 這個子白板,並且將 Mindstorms 這本書的卡片筆記放到 了這個子白板上。

當我卡片放好之後,我會把它開到右側欄讓我更方便地瀏覽裡面的內容。我通常會先快速掃過一遍這張卡片的所有內容,然後將裡面所有重要的概念識別出來。當我決定要把一個概念萃取出來時,我會把與這個概念有關的區塊選取起來一口氣拖曳到白板上變成一張新的「概念卡片」。

光是創建卡片還不夠,我還會將這張卡片的核心概念用一句話總結,並以這句話當做是卡片標題以確保我一眼就能知道它在講什麼。接下來,我會將這張概念卡片裡頭的內容重新組織,讓它的結構更符合我的直覺;我也會看一下原本的書籍卡片裡頭有沒有其他與這張概念卡片相關的區塊,如果有的話,我就會把它們也拖進這張概念卡片裡頭。

第三步:畫出這些概念之間的關聯性
當我從書籍卡片中萃取出愈來愈多概念卡片後,

