A lot of people advocate creating atomic notes from the start. I actually think that is a waste of time and that you should only excise part of a note (making it into a new “atomic” note) when you want to reference it elsewhere, whether that be a link or an embed. Instead a note should look like an interweave between the notes content and embeds. The primary reason Luhmann used atomic notes is it allowed for the insertion of new information anywhere in the notes collection. In a digital system we do not face that issue because we can edit the text on the fly.
Yes the objective of a zettelkasten is knowledge development, which is essentially the remix of ideas or creation of new connections. Traditional note taking tools do not look to promote the development of knowledge but instead stick to just knowledge management (storing & retrieval of information).
Search functionality is not part of the feature set of a zettelkasten, but instead a more fundamental feature of information management (note taking) systems. Linear search is a nightmare so throughout time we create search tools to facilitate quicker search. In the far past this took the form of indexes, summaries, and table of contents. This is why Luhmann used an index, he needed a search tool.
Nowadays we have digital search tools that make it very easy, so we don’t necessarily need to use an index or other traditional search tools. You might ask why then do I have an index? Well I find that an index can still often be faster than using the universal search tool (the magnifying glass icon in top right corner of forum) because the universal search tool pulls up all the occurrences of a concept, when in reality I only want the first occurrence.
For example, my index takes me to the very first note on “Note Size”, whereas using the universal search tool brings up every occurrence of the word Note Size.
When you have very long notes, you aren’t engaged in knowledge management but merely in info arrangement and a tiny bit of knowledge acquisition. I am speaking from experience with one of my non-zk knowledge bases.
Atomic notes with one idea are not only meant to embed in other notes,. Their primary purpose is to get a full handle on that one idea and branch out from there to make new associations. With long notes that is a lot more cumbersome to do, and less efficient.
As for search functionality, no, it is not part of the structure. Search is to find info you are looking for, and that info itself is part of the notes structure, whereas Search, whether that be linear or more sophisticated Regex-based, is ephemeral, only relevant in that one moment that you use it, then it’s gone again. A structure is permanent, not ephemeral; a structure can change, it can even disappear, but a search is never permanent, its output can be.
183 - Creating Note Sequences with Embeds - One drawback of current digital systems is the inability to easily insert notes between each other as you would do so with a physical system. This is for the creation of note sequences (chains of notes). One work around to this, is to have the start of a sequence be a note then embed other notes within it to create a note sequence.
An example of this is the Note 79 - Cognitive Skills, which has 8 embeds in it. Here is what it looks like in my Zettelkasten. @kbrede
185 - Bloom’s Taxonomy Revised - is a set of learning objectives used by theorists and researchers. You can think of our brains as information processing machines. Your zettelkasten can be framed in the same way, except it serves as an external machine.
The key mental functions you engage in for learning are: remembering, understanding, applying, analyzing, evaluating, and creating. The goal is to be able to engage in these functions with the four different types of knowledge: factual, conceptual, procedural, and metacognitive.
186 - Understanding more broadly is the process of acquiring knowledge about a topic such that you can make predictions about it.
On a neurological level this means creating a network of memory traces (chains of neurons) such that you can pull to mind all the relevant information on an idea through spreading activation. This is done through the natural or deliberate memorization of connections in everyday learning. These connections can take the form of knowing the relationship between two concepts or how the new information relates to prior knowledge. You essentially want to create as many retrieval cues as possible, so that you can pull up the information when needed.
Conceptually understanding means forming a working model around an idea whereby you can predict the output with a given input. On the most basic level, you can think of a simple math equation. You develop an understanding of it such that If I give you a set of inputs you can tell me what the output will be. This means knowing all the different components of the model (e.g. rules & concepts) and how they relate to each other.
With a zettelkasten understanding means taking the above working model and making it explicit through a series of connected notes instead of just having it all within your head in the form of a mental model.
cognitive processes (and alternative names) in the category of Understanding
Remix to combine or edit existing material to produce something new. With knowledge work, the existing material takes the form of information and knowledge.
Elements of Creativity
Copying is how we learn, and we do that through emulation. It builds your foundation of knowledge and understanding. After establishing a foundation of understanding, then you experiment through transformation. Transformation is taking ideas and creating variations until you get a breakthrough. Most dramatic results happen when ideas are combined.
"The problem of reading theoretical texts seems to consist in the fact that they do not require just short-term memory but also long-term memory in order to be able to distinguish between what is essential and what is not essential and what is new from what is merely repeated. But one cannot remember everything. This would simply be learning by heart. In other words, one must read very selectively and must be able to extract extensively networked references. One must be able to understand recursions. But how can one learn these skills, if no instructions can be given; or perhaps only about things that are unusual like “recursion” in the previous sentences as opposed to “must”?
Perhaps the best method would be to take notes—not excerpts, but condensed reformulations of what has been read. The re-description of what has already been described leads almost automatically to a training of paying attention to “frames,” or schemata of observation, or even to noticing conditions which lead the text to offer some descriptions but not others. What is not meant, what is excluded when something is asserted? If the text speaks of “human rights,” what is excluded by the author? Non-human rights? Human duties? Or is it comparing cultures or historical times that did not know human rights and could live very well without them?
This leads to another question: what are we to do with what we have written down? Certainly, at first we will produce mostly garbage. But we have been educated to expect something useful from our activities and soon lose confidence if nothing useful seems to result. We should therefore reflect on whether and how we arrange our notes so that they are available for later access. At least this should be a consoling illusion. This requires a computer or a card file with numbered index cards and an index. The constant accommodation of notes is then a further step in our working process. It costs time, but it is also an activity that goes beyond the mere monotony of reading and incidentally trains our memory."
This section from his essay is essentially saying that to create meaningful connections with our reading material, we must make an external form of long term memory. This long term memory takes the form of networked references within a large body of notes, using condensed reformulations of information. This condensed reformulations is also highly recommended for learning writ large through the process of elaboration.
189 - Deliberate Memorization of Information - is one of they key parts of learning. This becomes important when you aren’t dealing with ideas with such frequency that they naturally get memorized. So you have to create an artificial exposure by deliberately attempting to retrieve the memories. This is what we mean by studying and rote memorization.
Often it is done through the use of flashcards or a Spaced Repetition program such as Anki and SuperMemo.
190 - Learning is the process of creating mental connections in the brain through organizing information and tying it to your prior knowledge. The connections, represented in the form of memory traces in the brain, are then accessed through retrieval cues.
n. the acquisition of novel information, behaviors, or abilities after practice, observation, or other experiences, as evidenced by change in behavior, knowledge, or brain function. Learning involves consciously or nonconsciously attending to relevant aspects of incoming information, mentally organizing the information into a coherent cognitive representation, and integrating it with relevant existing knowledge activated from long-term memory.
191 - Natural Memorization of Information is the process of creating memories through repeat exposure to information in your environment. This is our default way of learning, as it happens everyday throughout your entire life.
A simple example of this is how you learn your coworkers name through repeat engagement with them. This will happen automatically over time, without the need to deliberately remember their name.
192 - Understanding vs. Knowing - in life it is useful to understand (ba dum tish) the distinction between understanding and knowing. I learned this distinction through the writings of Richard Feynman. He uses a couple different examples to illustrate it:
His Bird Story
Student and Fulcrum Story
Other stories?
In Surely You’re Joking, Mr. Feynman! he talks about
193 - Meaning is when information has acquired significance through its utility. This happens when you’ve connected the information to other pieces of information such that it…
n. the cognitive or emotional significance of a word or sequence of words, or of a concept, sign, or symbolic act. This may include a range of implied or associated ideas (connotative meaning) as well as a literal significance (denotative meaning). The study of meaning in language is semantics, and that of meaning in symbolic systems generally is semiotics. —meanvb.—meaningfuladj.
Further Reading:
A User’s Guide to Thought and Meaning by Ray Jackendoff
A Meaning Processing Approach to Cognition - What Matters? by John Flach and Fred Voorhorst
194 - Abstraction and Utility - our inclination and ever increasing march towards mastering the art of abstraction comes from its utility in the world would be my guess. Over time we have seen an increase in IQ (Flynn Effect), with some thinking it in part has to do with our increasing amount of knowledge work that deals with manipulating abstract ideas.
I think we are inclined towards abstraction because it allows us to use new information in a wider context, therefore gaining utility. You can generalize from the specifics, then use that information as a rough estimation.
At the ground level of learning is the process of knowing (remembering), whereby you create the memory trace and pair it with a retrieval cue so that you can pull up the information when presented with the retrieval cue at a later date.
Understanding is when you connect the information (memory traces) with your wider body of knowledge, whereby it gains meaning from becoming useful. An example of knowing information without understanding would be memorizing the words of a foreign language without connecting it to the equivalent words in your native language. So if someone were to say the words to you, you’d be able to say them back, but would not be able to act on them because there is no understanding. When the words have no utility then they are meaningless. Further Reading.
The goal is to achieve a full understanding of a subject, such that you can make predictions around the subject and successfully apply the knowledge to situations in life (e.g. decision making & skills).
The purpose of knowledge in the world is for use, the utility of information is what makes it meaningful in my opinion. The mind isn’t built to randomly memorize information, instead its built for remembering information that gets a lot of utility and is meaningful. That is why it is important to acquire the memory traces on how to apply the information you learn.
Part of structure building process in learning involves analyzing a topic to understand how its organized and its various sub concepts. This is necessary step to create meaning out of information. Often times in school, this step is explicitly done for you on paper within textbooks. It is still a good skill to develop for when you leave school and have to learn on your own (I do a lot of that).
196 - Memory Trace is a connected set of neurons that get activated when you invoke a specific retrieval cue. They get strengthened on retrieval, hence why we do rote memorization, and get re-consolidated after we retrieve them.
n. the hypothetical memory trace that is stored in the brain. The nature of the engram, in terms of the exact physiological changes that occur to encode a memory, is as yet unknown. The term was introduced by German biologist Richard Semon (1859–1918) in the early 1900s and was popularized by Karl S. Lashley in his 1950 paper “In Search of the Engram.” Also called mneme; mnemonic trace; neurogram.
a neural circuit in which nerve impulses that were initially activated in response to stimuli are more or less continuously reactivated so that retrieval of information on demand is possible. A theory of reverberating circuits has been proposed to explain learning and memory processes. Although reverberating circuits have been demonstrated only in the autonomic nervous system, they are also believed to exist in the central nervous system. Also called reverberatory circuit.
a group of neurons that are repeatedly active at the same time and develop as a single functional unit, which may become active when any of its constituent neurons is stimulated. This enables, for example, a person to form a complete mental image of an object when only a portion is visible or to recall a memory from a partial cue. Cell assembly is influential in biological theories of learning and memory. [proposed in 1949 by Donald O. Hebb]
197 - Retrieval Cues are pieces of stimuli you encounter that trigger the retrieval of a memory. Many different stimuli can serve as retrieval cues. A very unique smell may take you back to a memorable episode where last encountered that smell. This can also happen if there was a very specific smell during a meaningful event in your life. Music can often do this, listening to certain songs that I haven’t heard in a very long time bring up emotions I had experienced during that period of my life.
The two most common retrieval cues that we use in everyday life are the spoken and written word. When people say someone elses name it will bring up a slew of associations if you know that person. When you read a term or concept on a page it can invoke associated concepts or the terms definition.
The word being defined serves as the retrieval cue for its actual definition. You don’t evoke a definition, instead the word that represents it
1. the activation of a memory, which involves the retrieval of a memory by a cue. A retrieval cue that matches information stored in memory results in access to that memory. Cues or conditions that were present when the memory was formed are stored with the memory; therefore, those same conditions need to be reinstated at retrieval to provoke ecphory.
2. the process in which a memory, emotion, or the like is revived in the mind by a stimulus. Also called ecphoria. [defined by German biologist Richard Semon (1859–1918)] —ecphoricadj.
the principle that retrieval of memory is optimal when the retrieval conditions (such as context or cues) duplicate the conditions that were present when the memory was formed. [proposed in 1983 by Endel Tulving]
198 - Should you include textbook structures in your notes when deconstructing them?
This is a question that I’m still trying to work out in my head. When picking apart a textbook and taking notes on it, what are the components you can take notes on?
Quotes
Excerpts
Your Own Reactions
Individual Concepts
Interconnected Concepts
Models (Set of Rules)
Summary of Book
Review of Book
Summary of each Chapter
Book’s Table of Contents
This means that your notes on a book could either be very short (say the note just includes bibliography information and links to a few quotes) or very long (include all of the above components).
I’m not entirely sure what is the right balance? If I frame it through the lens of utility, then I’d want to find what level of note taking do I get the most bang for my buck. The very long notes probably have the most utility but tend to be very time consuming to make. The short ones are quick, but you want to avoid having to reread the book down the line.
199 - Retrieval Practice is the act of repeatedly retrieving a memory from long-term storage in order to test yourself and increase the memories retrieval strength. This works by being presented with a retrieval cue (flash card) that has to pull up the right set of knowledge (memory traces) from memory.
200 - Data, Information, Knowledge are all along the same continuum in my mind.
Data - is a set of values of qualitative or quantitativevariables about one or more persons or objects, while a datum (singular of data) is a single value of a single variable.
Information is data that has been made meaningful through contextualization and understanding.
Knowledge is information that has become a memory or set of memories within an individual.
Further Reading & Integration
Respective Wikipedia Pages
Big Data: A Very Short Introduction
Information: A Very Short Introduction
Knowledge: A Very Short Introduction
The Information: A History, A Theory, A Flood
Too Big to Know: Rethinking Knowledge…
Why Information Grows: The Evolution of Order, from Atoms to Economics
The Demon in the Machine: How Hidden Webs of Information Are Finally Solving the Mystery of Life
