Tag: notetaking

Smart Connections finds note connections

Smart Connections discovers and reveals related notes in Obsidian. I started using the Obsidian plugin Smart Connections because I wanted a way to apply AI interrogation of my own notes. I wanted to request cross-note summarizations and generate a variety of sample written products (e.g., blog posts) based on my personal notes and highlights. I ignored an important capability that is claimed based on the product’s name — the identification of note connections. 

Without an AI-based method for identifying possible connections among notes, Obsidian relies on the user to establish connections via links and tags. I was aware that other services (e.g., Mem.ai) suggested that a note retention system could do better and offered tags and links, but also made the claim that AI would help surface connections. Some would argue that exploring your Obsidian content repeatedly and finding connections are important parts of the process of personal knowledge management. Constantly working with your notes is an active cognitive activity that encourages connections between what is internally retrievable at a point in time and what you are accessing in Obsidian. New connections first brain to second brain and within Obsidian may emerge. This constant interactive process is suggested by what I would describe as the Zettelkasten practitioners. I don’t think this advice must be rejected for users who want to use AI to surface new connections.

Smart Connections makes use of AI, and the AI creates a numerical representation of the content of each note and stores these as what are called embeddings. You must subscribe to an AI provider via an API, which is far less expensive than a subscription to such a service. You have the option of basing such representations on blocks within notes rather than entire notes. I make use of this option because I store lengthy notes containing book and pdf highlights, such that a representation of an entire note does not represent a level of detail that is very useful for finding something useful in such lengthy notes. In the content that follows, I will show where to turn on block embedding.

Smart Connections works by requesting connections for a note that you have selected. The following image shows Obsidian with Smart Connections active. The green rectangle in the menu bar is used to activate the Connections as opposed to the Chat capability of Smart Connections. The up/down symbol allows you to scroll through the associated notes/blocks from most related to less related. The gear symbol is used to access settings for Smart Connections. The middle panel is the active note, and the right-hand column represents a hierarchy of related notes/blocks. 

Getting back to how I think AI may supplement the more hands-on use of Obsidian, I would recommend that in examining connections to a given note that you then use tags or links if you want to create permanent connections.

The extension of Smart Connects from note to note to note to block is worth doing if you do not keep atomic notes. Start with the Gear icon (see image above). This will reveal multiple setting options. What you are searching for are the environment settings. Open these settings with the button shown below. 

Once more settings have been revealed, you are looking for Smart Blocks (see below). You turn this option on and specify a minimal length. I did not keep a careful record of the source for advice I followed and I apologize to the author, but I entered 300 characters, and that seems to work well. There are many other settings and I have mostly stayed with the defaults. 

Summary: 

Smart Connections is an Obsidian plugin (free) that allows AI capabilities to be applied to the notes stored in Obsidian. Chats allows a user to generate AI prompts that are applied to the contents of Obsidian. Connections generates a list of notes (note blocks in the setup I have described) associated with a selected note and is helpful in the identification of such relationships in a large collections of notes. 

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Disciplinary Perspectives on Taking and Using Notes

I have found myself exploring and writing about the interrelated topics of personal knowledge management, second brains, and note-taking for the past several years. As I have spent time on these interests, it became obvious that there were multiple disciplinary perspectives on these topics. In addition, the different disciplines seem mostly oblivious to each other as indicated by the lack of cross-referencing evident in their written materials. There are sometimes references to historical connections which I will identify, but for anyone interested in these topics I would suggest there are benefits for exploring more than a single point of view.

The Perspectives

Here are the descriptive labels I have decided to use for what I claim to be different perspectives. Hopefully, the labels offer some insights into the categories I have in mind.

  1. Academic studying – this perspective provided my personal background for this general topic. The focus of this perspective is learning in formal academic environments with the goals of the acquisition, understanding, and application of information to examinations and projects. While the general goal of education is focused on the long term and preparation for life, note-taking has a more immediate focus. I am of the opinion that the great majority of what I would describe as research is focused on topics within this category. Most of this research is based on a cognitive perspective on learning and application.
  2. Organizational Knowledge Management – Organizations have a need to develop, preserve, and apply knowledge. For multiple practical reasons (e.g., changeover in personnel), this knowledge should be externalized for the benefit of the organization. The generation and use of this shared knowledge originate with individuals. Personal knowledge management (PKM) can be individualized or integrated with the more general needs of a given organization. Procedures for accomplishing these goals are the subject of scholarship and training in the formal programs preparing individuals for careers in organizations (e.g., business schools), but it is my impression that scholarship is less empirical than that applied by those with an academic studying perspective and more anecdotal and based in logical argumentation.
  3. Knowledge Management Entrepreneurs – I struggled with a way to describe this perspective. It seems to me that there has been a recent and identifiable group of individuals offering self-help books and consulting expertise to those interested in Personal Knowledge Management. This category resembles the organizational knowledge management perspective but does not share the same group focus. The perspective emphasizes the collection, organization, exploration, and application of information over an extended period of time to accomplish personal goals. Of the three groups I have identified, those individuals promoting techniques and processes are the least likely engaged in what I would describe as formal scholarship.

Historical Antecedents

While not absolutely consistent, there are frequent references to similar individuals, practices, and models that can often be identified among these perspectives. Here is my own list of such sources.

  1. Vannevar Bush’s article “As we may think” describing the manner in which individuals and organizations might use a yet-to-be-developed technology (the Memex) to take on information overload and how a knowledge worker might explore, retain, organize, and apply information. 
  2. Commonplace books are journals, diaries, or notebooks maintained by individuals. A famous historical example would be the Leonardo Di Vinci notebooks still available in different formats (Amazon source).
  3. Luhmann’s Zettelkasten. A zettelkasten is a card-based note-taking and note-linking system now often adapted to digitization and computer applications. It did not originate with Nikolas Luhmann, but I have connected the approach with his name because his prodigious use of the system as a scholar seems the example so many use. 
  4. The encoding and external model of note-taking (e.g., Rickards & Friedman, 1978) is the basis for much of the empirical research from the academic studying perspective. It proposes that learners could possibly benefit from both the thinking required in taking notes (the encoding process) and/or by having an external record available for review (external storage). This basic differentiation has been applied to such topics as whether taking notes by hand is more or less effective than taking notes using a keyboard (encoding), the best ways to work with the external notes (e.g., retrieval practice), and individual differences in both what is stored and how what is stored is used. For example, the Cornell note-taking method is an example of a system for both taking and using notes. 

Examples from the different perspectives

I have written extensively about a couple of these perspectives in previous posts so rather than repeat myself and increase the length of this post I will link to some of these earlier posts.

  1. Academic Studying – History of Note-Taking Research, Note-taking as a Generative Activity, Cornell Notes and Beyond
  2. Organizational Knowledge Management – this perspective is a little more challenging as I have not written about it before. Here is a source you can explore without having journal access – Towards a Co-evolution of Organizational and Personal Knowledge Management Systems. Also see Pauleen (2009) – this is the introduction to a special issue on personal knowledge management. 
  3. Knowledge Management Entrepreneurs – Creating, Storing, and Using Smart Notes, Evaluating Tech Tools for Adults

Why consideration of the different perspectives might be useful?

Having asked you to recognize the multiple perspectives that I have identified, I owe you some explanation for why I think anyone interested in taking notes should expand their awareness of the background content available on this topic. I have found a couple of personal opportunities. First, the work from the perspective of academic studying has been far more carefully evaluated and useful in answering questions of why and if specific activities work. The knowledge management entrepreneurs offer specific “how to do it” suggestions and have strongly promoted the use of technology tools in PKM. The organizational knowledge management perspective extends the note-taking and PKM for life-long learning expanding core ideas beyond the academic classroom setting. 

The links I provide here should open to many other resources on the perspectives I have identified.

References not linked

Pauleen, David (2009), “Personal knowledge management: putting the ‘person’ back into the knowledge equation”, Online Information Review, vol. 33, no. 2, pp. 221–224, doi:10.1108/14684520910951177.

Rickards, J. P., & Friedman, F. (1978). The encoding versus the external storage hypothesis in note taking. Contemporary Educational Psychology, 3(2), 136-143.

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Could AI Replace Many of the Recommended PKM Processes?

How much of the “building” part of building a second brain is necessary? With the opportunity to direct AI at accumulated resources, how much of the linking, tagging, reviewing, and re-expressing notes is productive? Some version of this question has long bothered me. I studied classroom note-taking as an academic and became familiar with the massive research base associated with different ways to take and use notes, the cognitive and metacognitive processes associated with activities in different note-taking approaches, and individual differences in the capacity and motivation to execute specific processes effectively. While there is a great deal of speculation, multiple books, and the sharing of numerous personal processes in online posts, where is the research on PKM and Second Brains? The research on learners taking and using notes in academic settings may offer a general structure, however there would seem important differences in the use of self-directed note-taking outside of an environment that involves processes that must accomplish goals set by others to produce products or perform tasks after short time intervals (the time between exams or writing assignments).

The terminology is different. You do not find classroom-oriented research considering fleeting versus permanent notes or the ideal types of tags and links to organize notes and prepare the user for future goals and tasks that often do not exist when the notes are taken. I try to translate the proposed strategies outlined in popular books for the audience that takes notes to benefit them under these circumstances (Ahrens, Doto, and Forte). Can the research on generative cognitive processes, metacognitive comprehension monitoring, and retrieval practice serve to determine if the recommendations made by these writers are reasonable? Perhaps the strategies for creating different types of notes (fleeting vs. permanent), strategies for linking and tagging, and reviewing to find new associations are just busy work. 

Does AI provide an alternative?

MEM.AI was the first note-taking and storage tool I used that came with an embedded AI tool. The promotional material I read before investing time and money into MEM proposed that the availability of the embedded AI offered an alternative to the tags and links in a tool such as Obsidian. MEM.AI allows the manual assignment of something similar to tags and bi-directional links. The embedded AI did a couple of interesting things. As you built up a collection of notes, the AI offered suggestions based on the material you have accumulated. Similar notes were identified based on common elements of a new note and existing notes (see red box in the following image). You could link to suggested notes if you found the suggestions of value. Tags for a new note were proposed beyond any rags that were manually added (see red box in the following image) and any of these suggestions can be accepted. I have recently written about multiple ways note-taking systems can be augmented with AI, but MEM.AI is built with some of these processes assumed rather than potentially available through the creation of clever prompts. MEM.AI proposes that it creates a self-organizing workspace which seems a reasonable description.

MEM.AI has one more unique feature that seems a powerful use of the self-organizing workspace concept. There is a built-in word-processing capability called Smart Write. When you enter a forward slash / within any existing note or within an empty note, you can then enter a chat prompt. You can ask a question or make a request. With an existing note, the AI extends what already exists in what are often interesting and creative ways relying on what appears in the note you are working on and the corpus of notes you have saved. The output appears within that note and can be copied and pasted elsewhere or left as part of that note. It can be argued that this is a way to discover connections to other material more directly than what might have been manually indicated by creating a link to another specific note. 

Here is an example.

The following (Permanentnotes) is a note I created with two tags. What you can no longer see is the / and prompt that was originally inserted after the second tag. The prompt entered after the / was “Does my idea that permanent notes move more of the thinking involved in transforming notes into a final written product earlier in that writing process make sense?”  Smart Write added three paragraphs based on other stored notes.These paragraphs now appear in the original note (shown below). Not all of this content seems relevant, but connections were discovered and much of what was said could be used in writing about this concept. These additions were all based on previous content I added, but I did not have to manually find these connections.

Permanentnotes

This is a key insight. Permanent notes should be able to stand alone without reference to the original content for context. Perhaps it could be described as moving part of the writing process earlier in the transition from note-taking to a final written product.

#notetaking

#slipbox

Your thought about moving part of the writing process earlier in the transition from note-taking to a final writing product indeed makes sense and aligns with the ideas presented in the writing process model by Flower and Hayes (1981). The model emphasizes the importance of planning as a foundational step in effective writing, which involves setting goals, gathering information, and organizing ideas. By integrating permanent notes into this early stage, you essentially create a structured framework that facilitates the translation and reviewing phases of writing.

The approach of using permanent notes, akin to the slip-box system described by Ahrens, enhances this framework by allowing writers to develop a rich, interconnected repository of ideas and insights. This repository acts as an external structure that compensates for the cognitive limitations of the human brain, making it easier to retrieve and connect ideas when composing a draft. The slip-box method encourages a shift from merely capturing fleeting thoughts to actively engaging with and refining those ideas into coherent, stand-alone pieces of information.

Furthermore, this method aligns with the iterative nature of the writing process. As notes are continually reviewed and expanded, they can reveal gaps in understanding or suggest new lines of inquiry, prompting further research and reflection. This iterative engagement not only aids in the development of writing skills but also fosters deeper learning and insight generation, as noted by Ahrens. Thus, your suggestion to reposition part of the writing process earlier, in the context of note-taking and idea organization, is a strategic move that can significantly enhance both the efficiency and quality of writing.

Summary

I would argue that AI capabilities can substitute for or at least augment manual processes advocated by those arguing tags and links are an essential part of the Personal Knowledge Management process. To some extent, I have found the capabilities of the MEM self-organizing workspace to be more thorough in proposing connections than I would typically be on my own.

This brings me to an issue I consider in many applications of AI. This issue is whether the AI approach allows the user to avoid important activities that are important in and of themselves. Perhaps both the manual and AI approaches here allow a note-taker to produce comparable final written products if that was the goal. Whether the activities of exploring notes to make appropriate links and adding tags that identify key ideas encourage deeper thinking about the content seems a different issue. Again, this is difficult to know. One might make the opposite argument claiming that reviewing the text generated by the AI offers a different way to explore and find relationships within existing content and the process of considering what within this new material is relevant to the intended purpose of the prompt is a unique evaluative activity performed by the user. As I have already suggested, MEM.AI does not require that you take one approach or the other. So, explore. AI capabilities are being added to many note-taking tools and the potential is worth a look.

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Desirable Difficulty

Despite a heavy focus on cognitive psychology in the way I researched and explained classroom study tactics, I had not encountered the phrase desirable difficulty until I became interested in the handwritten vs. keyboard notetaking research. I discovered the idea when reviewing studies by Luo and colleagues and Mueller and Oppenheimer. Several studies have claimed students are better off taking notes by hand in comparison to on a laptop despite being able to record information significantly faster when using a keyboard. 

Since having a more complete set of notes would seem an advantage. The combination of more notes associated with poorer performance is counterintuitive. Researchers speculated that learners who understood they had to make decisions about what they had time to record selected information more carefully and possibly summarized rather than recorded verbatim what they heard. This focus on what could be described as deeper processing seemed like an example of desirable difficulty. The researchers also proposed that the faster keyboard recording involved shallow cognitive processing.  

Note: I am still a fan of more complete notes and the methodology used when demonstrating better performance from recording notes by hand needs to be carefully considered. I will comment on my argument more at the end of this post. 

Desirable difficulty an idea attributed to Robert Bjork has been used to explain a wider variety of retention phenomena. Bjork suggested that retrieval strength and storage strength are distinct phenomena and learners can be misled when an approach to learning is evaluated based on retrieval strength. I find these phrases to a bit confusing as applied, but I understand the logic. Students cramming for an exam make a reasonable example. Cramming results in what may seem to be successful learning (retrieval strength), but results in poorer retention over an extended period of time (storage storage strength). Students may understand and accept the disadvantages of cramming so it is not necessary that the distinction be unrecognized by learners. In a more recent book on learning for the general public, Daniel Willingham suggests that the brain is really designed to avoid rather than embrace thinking because thinking is effortful. The human tendency is to rely on memory rather than thinking. Desirable difficulty may be a way to explain why some situations that require thinking prevent something more rote. 

Increasing difficulty to improve retention

There are multiple tactics for productively increasing difficulty that I tend to group under the heading of generative learning. I describe generative activities as external tasks intended to increase the probability of productive cognitive (mental) behaviors. I suppose desirable difficulty is even more specific differentiating external tasks along a difficulty dimension. So in the following list of tasks, it is useful to imagine more and less difficult tasks. Often the less difficult task is the option learners choose to apply. In connecting these tactics with personal experience, I would recommend you consider the use of flashcards to conceptualize what would be the easier and the more challenging application. Then, move beyond flashcards to other study tactics and consider if you can identify similar contrasts. 

Retrieval Practice: Testing oneself on the material rather than passively reviewing notes is considered retrieval practice. The classic empirical demonstration of the retrieval practice or the testing effect compared reviewing content versus responding to questions. Even when controlling for study time, spending some time on questions was superior. With the flashcard applications I recommended you consider, answering multiple-choice questions would be less challenging than answering short-answer questions (recognition vs recall).

Spacing (Distributed Practice): Instead of cramming, spreading out study sessions over time is more productive. This method helps improve long-term retention and understanding. Spacing allows some retrieval challenges to develop and the learner must work harder to locate the desired information in memory. See my earlier description of Bjork’s distinction between retrieval strength and storage strength. 

Interleaving: Mixing different types of problems or subjects in one study session. For example, alternating between math problems and reading passages rather than focusing on one at a time. A simple flashcard version of this recommendation might be shuffling the deck between cycles through the deck. Breaking up the pattern of the review task increases the difficulty and requires greater cognitive effort. 

Other thoughts

First, the concept of committing to more challenging tasks is broader than the well researched examples I provide here. Writing and teaching could be considered examples in that both tasks require an externalization of knowledge that is both generative and evaluative. It is too easy to fake it and make assumptions when the actual creation of a product is not required.

Second, desirable difficulty seems to me to be a guiding principle that does not explain all of the actual cognitive mechanisms that are involved. The specific mechanisms may vary with activity – some might be motivational, some evaluative (metacomprehension), and some at the level of basic cognitive activities. For example, creating retrieval challenges probably creates an attempt to find alternate or new connections among stored elements of information. For example, in trying to put a name with a face one might attempt to remember the circumstances in which you may have met or worked with this person and this may activate a connection you do not typically use and is not automatic. For example, after being retired for 10 years and trying to remember the names of coworkers, I sometimes remember the arrangement of our offices working my way down the appropriate hallway and this sometimes helps me recall names. 

I did say I was going to return to the use of desirable difficulty as a justification for the advantage of taking notes by hand. If keyboarding allows faster data entry than handwriting, in theory keyboarding would allow more time for thinking, paraphrasing, and whatever advantage one would have when the recording method requires more time. Awareness and commitment would seem to be the issues here. However, I would think complete notes would have greater long-term value than sparse notes. One always has the opportunity to think while studying and a more complete set of notes would seem to provide the opportunity to have more external content to work with. 

References:

Bjork, R.A. (1994). Memory and metamemory considerations in the training of human beings. In J.  Metcalfe & A. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 185-205). Cambridge,  MA: MIT Press.

Luo, L., Kiewra, K. A., Flanigan, A. E., & Peteranetz, M. S. (2018). Laptop versus longhand note taking: effects on lecture notes and achievement. Instructional Science, 46(6), 947-971.

Mueller, P. A., & Oppenheimer, D. M. (2014). The pen is mightier than the keyboard: Advantages of longhand over laptop note taking. Psychological science, 25(6), 1159-1168.

Willingham, D. T. (2021). Why don’t students like school?: A cognitive scientist answers questions about how the mind works and what it means for the classroom. John Wiley & Sons.

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YouTube Annotation with Glasp

I take a lot of notes and have done so for years. I have tried many different tools over this time period. Social Annotation is a subcategory of these tools that allows users to share their highlights and notes. The idea is that the sharing of notes allows individuals to find resources they have not personally explored and offer their own discoveries to others. Glasp serves these purposes.

I have written about Glasp on several previous occasions. A unique capability allows built-in AI capabilities to “chat” not only with your own notes, but also the annotations stored by others.

Glasp is a combination of a Profile page that is the online location allowing access to the content you have collected (see above) and a browser extension that provides the means to highlight and annotate the content viewed within your browser. Kindle content is imported automatically. Glasp could provide the storage location for all of your notes, but I export notes to Obsidian to take advantage of more advanced features.

I don’t spend a lot of time collecting information from Youtube because most of writing is based on books and journal articles. There are exceptions when I review tutorials for software tools and want to keep track of specific tactics. I understand that others use YouTube extensively and I wanted to explore the capabilities of Glasp with this information source. The following video is my effort to describe how notes and highlights are generated from YouTube content.

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Potential conflicting benefits of your note-taking tool and approach

As I have explored and used several digital note-taking tools and examined the arguments that have been made regarding how such tools result in productivity benefits, I have identified a potential conflict in what produces more positive outcomes. The recognition of this conflict allows more purposeful execution on the part of the tool user and may better align activities with goals.

One way to identify note-taking goals is to use a long-standing approach differentiating generative and external storage benefits. This distinction was proposed long before PKM and was applied in the analysis of notes taken in classroom settings. The generative benefit proposes that the process of taking notes or sometimes of taking notes in a particular way engages our cognitive (mental) processes in ways that improve retention and understanding. External storage implies that our memory becomes less effective over time and having access to an external record (the notes) benefits our productivity. In practice (e.g., a student in a classroom) both benefits may apply, but one benefit depends on the other activity. Taking notes may not be beneficial, but to review notes one must have something to review. This is not always true as notes in one form or another can be provided or perhaps generated (for example AI identification of key ideas), but taking your own notes is by far the most common experience. In a PKM way of thinking, these two processes may function in different ways, but the classroom example should be familiar as a way to identify the theoretical benefits of note-taking.

I have written about the generative function of note-taking at length, but it is important to point out some unique specifics that apply to some digital note-taking tools. A source such as Ahrens’ Taking Smart Notes might provide the right mindset. I think of generative activities as external actions intended to produce a beneficial mental (cognitive) outcome. The idea is that external activities can encourage or change the likelihood of beneficial thinking behaviors. One way of operationalizing this perspective is to consider some of the specific activities Ahrens identified as external work resulting in such cognitive benefits. What are some of these activities? Isolating specific ideas and summarizing each as a note. Assigning tags that characterize a note. Making the effort to link notes. Periodically reviewing notes to generate retrieval practice, to reword existing notes, and to add new associations (links).

Retrieval is easier to explain. Note-taking apps with highly effective search capabilities make it easy to search and surface stored information when it might be useful. Links and tags may also be useful in this role, but search alone will often be sufficient.

What about the potential conflict?

The conflict I see proposes that some tools or approaches rely more heavily on search arguing in a way that generative processes are unnecessary.

I starting thinking about this assumption when contrasting the two note-taking systems I rely on – Mem.ai and Obsidian. While Mem.AI and Obsidian could be used in exactly the same way, Mem.ai developers argued that the built-in AI capabilities could eliminate the need to designate connections (with tags and links) because the AI capabilities would identify these connections for you. Thus when retrieving information via search, a user could use AI to also consider the notes with overlapping foci. If a user relied on this capability it would eliminate the work required to generate the connections manually created in Obsidian, but this approach would then also avoid the generative benefits of this work. 

AI capabilities fascinate me so I found a way to add a decent AI capability to Obsidian. Smart Connections is an Obsidian plugin that finds connections among notes and allows a user to chat with their notes. So, I found a way to mimic Mem.ai functionality with Obsidian. 

I find I have found a way to alter my more general PKM approach because of these capabilities. Rather than taking individual notes while reading, I can annotate and highlight pdfs, books, and videos and export the entire collection for each source and then bring this content into both Mem.ai and Obsidian as a very large note. Far easier than taking individual notes, but at what generative cost?

Smart Connections has added a new feature that even facilitates the use of the large note approach. Connections finds connections based on AI embeddings. An embedding is the mathematical representation of content (I would describe as weights based on what I remember of statistics). The more two notes embeddings’ weights are similar the more the notes consider similar ideas. Smart Connections used embeddings to propose related notes. Originally embeddings were generated at the note level and now at the “block” level. What this means (block level) is that Smart Connections can find the segments of a long document that have a similar focus as a selected note. 

Why is this helpful? When I read long documents (pdfs of journal articles or books in Kindle), I can export a long document containing my highlights and notes generated from these documents. With Smart Connections I can then just import this exported material into Obsidian and use Smart Connections to connect a specific note to blocks of all such documents. I can skip breaking up the long document into individual notes and assigning tags and creating links.

Why is this a disadvantage? Taking advantage of this capability can be a powerful disincentive to engaging in the generative activities involved in creating and connecting individual notes the basic version of Obsidian requires. 

Summary

As note-taking tools mature and add AI capabilities, it is important for users to consider how the way they use such tools can impact their learning and understanding. The tools themselves are quite flexible but can be used in ways that avoid generative tasks that impact learning and understanding. If the focus is on the retrieval of content for writing and other tasks, the generative activities may be less important. However, if you start using a tool such as Obsidian because a book such as Smart Notes influenced you, you might want to think about what might be happening if you rely on the type of AI capabilities I have described here. 

References
Ahrens, S. (2022). How to take smart notes: One simple technique to boost writing, learning and thinking. Sönke Ahrens.

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A use for Obsidian Unlinked Mentions

Have you had the experience of coming across an application feature and wondering why did a software designer decide to go to the trouble of creating and then shipping that feature? Somewhere I encountered a comment on an Obsidian feature called an Unlinked Mention. It took me some time to find it and then even more time in an effort to understand why it exists. I am still not certain how it is to be used and why there wouldn’t be similar features that would be more useful. I have come up with one way I find it offers some value so I will explain what seems a hack and then hope others can find my description helpful in encouraging similar or additional uses. 

Note: My description and proposed actions are based on Obsidian on a computer. Some of the actions I describe I could not get to work on my iPad. 

So, I think an unlinked mention is supposed to be understood as something like a backlink. In Obsidian when you create a link among two notes (A – B), Obsidian recognizes but does not automatically display the backlink (B-A). For a given note (A), you can get Obsidian to display any backlinks to that note using the backlinks option for the right-hand panel of the Obsidian display. For the note that is active in the middle panel, the right-hand panel should indicate linked mentions and unlinked mentions. You may have to select which you want displayed and it is possible nothing will be displayed for either option. The linked mentions are the backlinks and you can select and display the backlinked notes from this display. 

The unlinked mentions are other notes that contain the same exact phrase as you have used to title Note A. Who knew? Why? Maybe I never quite understood the power of a title or how my notes were supposed to be titled. I have tried to think about this and I still don’t get it.

Here is my hack and I think a way to take advantage of unlinked mentions. Start with a blank note and add a title likely to be used within other content you have stored within other notes. To make the effort, your word or phrase would have to be something you want to investigate. I used the word “metacognition” because this is an important concept in the applied cognitive psychology research I read and attempted to apply to educational uses of technology. I have notes about this concept, but the greatest value I found in this hack was taking advantage of all of the Kindle notes and highlights I had stored in Obsidian via Readwise. In my account, there are more than 200 books worth of notes and highlights and the content for each book is often several pages long.  I create notes myself as I read, but there is all of this additional content that may contain things I might find useful. Certainly, several of these books would contain content, especially highlights, focused on metacognition. 

Once I have my new note with the simple title “metacognition” and for this note look under unlinked mentions in the right-hand column, I now have lots of entries. At this point, my note is still blank, but I now can access many other mentions of metacognition from this list of unlinked mentions. If I select one of these mentions, a “link” button appears and if I select this button Obsidian generates a forward link in the A document and adds the A document to my blank B document as a backlink. The B note is still blank.

Here comes the hack. One of the core plugins for Obsidians is called backlink (use the gear icon from the panel on the left) and it contains a slider that will display backlinks at the bottom of a note (see following image). Now you can display backlinks on your blank note that allow access to the unlinked content you have linked. See the second image below.

The process I have described is a way to generate a collection of links on a topic that would not be available without this hack. It is the process that finds specific mentions of a concept within much larger bodies of content (the highlights from Kindle books) that I find useful. Give it a try.

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