notetaking – Learning Aloud

Karpathy Plugin for Obsidian

I have spent a significant amount of time over the past week or so developing a Karpathy wiki based on a large portion of my Obsidian notes. This process began in April when I decided to purchase a Macintosh Mini I intended to devote exclusively to the exploration of AI on the desktop. I was a bit slow in making this purchase and it took until last week to receive my purchase. My tardiness cost several hundred dollars more than it would have a few months ago.

I was motivated to invest and explore this area for two reasons. First, my main interest in AI continues to focus on retrieval-augemented generation (RAG) of the notes and highlights I have collected to serve as a foundation for my writing projects. As I have used AI plugins to interact with the content I have stored and organized in Obsidian, I discovered that the API-based services for interacting with these notes are relatively expensive because the process of first feeding the notes to the AI service must be repeated each time a session is initiated. Karpathy proposed that AI could be used to create a wiki based on the concepts and connections in a collection of source material, either once (when the collection was created) or as each new item of content was added, and this wiki could then be the focus of future explorations, reducing the cost due to the repeated input of the same content to the AI service.

My second motivator was personal curiosity, sparked by the many posts promoting the potential of AI tools and models that could run on personal hardware, avoiding the costs and scrutiny associated with using online services from major AI companies. The proposal was that many common uses of AI no longer required access to $20 or $200-a-month subscription services.

I understand that another tutorial or “how I did it” post may be required at this point, but I read a post explaining that getting started with self-hosting LLMs will not be easy as the posts newbies are likely to read make it sound, and a good deal of exploration and personalization will be required. The message was intended not to be discouraging but to communicate that “don’t give up, you should be able to get it to work.” This was pretty much my experience, and I thought it worthwhile to explain the issues I encountered and why I had to make adjustments to my specific situation. My experiences with tech since the mid 1980s have kind of gone this way.

So, I have two Mac Minis now, and the first challenge was how to connect both to the same large monitor so I can switch back and forth as required by a general-use and a specific-use computer arrangement. I knew I would have to purchase a KVM (keyboard, video, mouse), but I had not considered that my current setup uses a Bluetooth mouse and keyboard. More specifically, Apple’s Magic Keyboard and Mouse are not intended to be linked to more than one device. You charge your Magic keyboard with a USB cable, so the cable can be used as it has long been used to connect to a computer. You also charge your Magic Mouse, but the cable is inserted on the bottom of the mouse, preventing it from being used while it is being charged. Solution – purchase a mouse with a cable. The first challenge is overcome.

My plan was to use the Obsidian Karpathy LLM wiki plugin because this seemed the most efficient way to create a working system. The plugin’s setup allows selecting multiple AI sources, including subscription services. I did use Anthropic’s Claude API when I was having difficulty getting either of the two local options (Ollama or LMStudio) to work. Claude worked great, but adding one new source document cost 70 cents. My present collection is close to 300 note files, and the work the AI does increases as the complexity of the wiki increases so I treated the success as a sign the struggles I was experiencing could eventually be overcome.

When using Ollama, I was experiencing a consistent problem with some, but not all of the note files the AI was ingesting to build the wiki. I spent a considerable amount of time over several days comparing the files that could and could not be processed and I never did find a difference. It wasn’t the length, the presence of specific markdown tags, the tool I had used to create the original markdown file, or any other variable I could imagine. Nothing. However, the problem was consistent. The same files, time after time, would either work or fail.

My typical strategy in such situations is to ask questions of the Internet. One proposal was that the JSON history had become corrupted. The solution was to reveal the invisible files (the .files and folders) and delete these files. New files would be generated when the Obsidian app was next launched. This was done without consequence.

One issue I encountered was that the models displayed as options within Ollama did not contain the model (qwen2.5) I had found recommended when I read the descriptions of others. I searched how to add other models to Ollama and found it could be done with a terminal command (ollama pull <model name>. Now qwen2.5 appeared. Qwen3.6 was originally listed and I assumed there would be little difference, but for some reason, I was wrong, and the system worked with qwen2.5.

Without going into details because others have already provided tutorials, you first add and install the Karpathy LLM Wiki plugin for Obsidian. The gear icon associated with this community plugin provides a “fill in the blank” form where you enter information linking Obsidian to the AI online service or local option you want to use.

The wiki construction process is controlled by the commands that appear in the Obsidian command list when the Karpathy plugin is installed.

So, you start Ollama and select the model you will use in Obsidian. Start Obsidian and select the command to ingest a file or folder and be patient. Eventually, your wiki will be generated, and you can query the wiki rather than the source files. The right-hand column displays a response to a prompt.

So, I was able to generate a wiki based on more than 150 of my notes. In examining some of the components of the wiki I did find some weird artifacts. There were some with Chinese characters. I happen to be listening to LeoLaporte talking about different AI models and he said that qwen originated in China. It then made sense to me that the model might translate some of the Chinese names in my article summaries and include their Chinese translations (no idea if that is actually what happened). I also found some md pages with titles, but no content.

When I used the Karpathy command to submit queries, I found the quality of the responses to vary. Some made sense and some ignored sources I knew existed and were central to what I expected. Rewording of the query in ways I thought the model should have understood as equivalent sometimes resulted in the response I expected.

The following comparison (first from querying my new wiki, and the second from using Claude with my original source files) demonstrates fairly substantial differences. As you can tell from a quick skim, there are significant differences in the eloquence and completeness of the responses. The sample responses are presented as an Appendix.

Summary

Each user is likely to have a unique experience when applying a local AI system to their content to generate a Karpathy-style wiki. Expecting that it will take some tinkering is good advice even when following instructions or “how to do it” videos on YouTube. My effort here was to describe what this tinkering experience looked like.

After at least getting the system to work, I was able to compare my first successful effort with what I generated for 44 cents using Claude. The differences were substantial.

I assume there are many more issues to explore. I am currently repeating the process with a different script that instructs the AI on what to do when creating the wiki. If that effort produces substantial improvements, I will have to write another post.

*******

Response of local model to wiki

Summary of Research Comparing Handwritten Notes vs. Computer Notes

According to the literature summarized from various studies, there are several key findings regarding the comparison between handwritten notes and notes taken on computers:

Repetition in Note-Taking:

– A study by Bui et al. 2015 suggests that repeated exposure to material enhances learning outcomes, especially when coupled with effective note-taking strategies.

Handwritten Notes and Memory Retention:

– Longhand notes are described as more paraphrased and containing more signals and images, which can lead to higher text-related achievement when reviewed (from Longhand Notes).

– Lecture Note-Taking Strategies indicate that students who take notes by hand outperform those who use digital devices, as handwritten notes require a higher level of processing and engagement.

Editing and Revisions:

– Research by Mueller and Oppenheimer (2014) found that while typing is faster, it leads to less cognitive effort and thus less retention due to the lack of engagement required in handwriting notes.

– Follow-up revisions are crucial as they enhance memory retention. According to a study cited by AI response, revising digital notes can mitigate some of the disadvantages of digital note-taking, improving long-term recall and academic performance (from AI Response to Challenging Luo Study).

Professional Note-Taking:

– Additionally, in the context of professional training, effective note-taking is vital for future practitioners (from “Notetaking in Professions”).

References

Longhand Notes — Core mechanism explaining why handwritten notes are more beneficial.
Bui et al. 2015 — Effects of Repetition on Note-Taking and Recall Strategies in College Lectures.
“Notetaking in Professions”. Stacy and Cain, American Journal of Pharmaceutical Education (2015) — Importance of note-taking skills for professional training.
Mueller and Oppenheimer (2014) — Pen and Pad versus Laptop for Note-Taking.
AI Response to Challenging Luo Study — How Note Modification Research Might Counter Luo et al. (2018)

*******

Paste from Claude plugin within Obsidian

Handwritten vs. Computer Note-Taking: What Your Notes Say

Your vault contains extensive research on this topic, and the picture that emerges is more nuanced and contested than the popular narrative suggests. Here is a synthesis of what your notes reveal:

The Foundational Study

The most influential study is Mueller & Oppenheimer (2014), documented in Pen is mightier than the keyboard. Their key finding was that faster keyboard transcription led to more verbatim, less generative notes, while the slower speed of handwriting forced summarization and paraphrasing. Notably, their Study 3 found no differences when note review was not allowed, but longhand was superior when review was allowed—a surprising result.

The Generative Processing Argument

Several of your notes outline the theoretical rationale:

Translation hypothesis: Writing adds a distinctive encoding channel beyond just listening (Luo, Linlin, Kenneth A. Kiewra, Abraham E. Flanigan, and Markeya S. Peteranetz2018)
Generative hypothesis: Handwriting’s slower speed forces paraphrasing, organization, and integration with prior knowledge, leading to deeper processing (Depth and Generative, EncodingEffect)
As noted in transcription speeds, adults type at ~33 wpm and write longhand at ~22 wpm, meaning handwriters must be more selective

Your note in transcription speeds raises a sharp critique of this logic: it “suggests a strange lack of awareness on the part of the learner. It would seem that the keyboarding learner is oblivious to the benefits of generative processing and goes with what is easier, but less effective.”

Contradictory and Inconsistent Findings

Your notes consistently emphasize that research findings in this area are contradictory:

Urry.et.al documents a major replication of Mueller & Oppenheimer that found inconsistent results. Urry found laptop users took more notes and more notes related to better performance. Critically, they differentiated quantity from verbatim overlap—quantity was positively related to performance while verbatim proportion was negatively correlated.
Luo, et al 2018 found that when notes were recorded but not reviewed (process function), laptop was actually better for image-related learning. Only when notes were reviewed (product function) did longhand show an advantage. The authors themselves note that “findings in this area of research are often contradictory and uncontrolled variables may be responsible.”
Flaniganetal2023 found that, surprisingly, longhand and computer note takers recorded a similar number of ideas during the lesson, contradicting the expected computer advantage. However, longhand revisers added three times as many complete ideas during revision pauses.

The Note Completeness Counter-Argument

Your notes in NoteCompleteness and Colllaborative Notes document an important counter-narrative: note completeness predicts achievement, and computers produce more complete notes. As noted:

“The studies of note volume and completeness would seem to challenge the argument that taking notes on a computer is a liability because more notes are taken implying less thinking about the content.”

Bui et al. (2013) found that students with access to their more complete (computer-generated) notes demonstrated better performance, directly contradicting Mueller & Oppenheimer’s interpretation.

The Revision Factor

Multiple notes highlight that the handwriting vs. computer debate may miss the most important stage entirely—revision:

Three stage model of note-taking proposes that effective note-taking is a three-stage process: recording ? revision ? review, and most studies ignore the revision stage.
Cojeanatal2024 found that computer note-takers were more likely to reformat and revise their notes after class, potentially compensating for less generative initial encoding.
Flaniganetal2023 found longhand revisers added more ideas during revision pauses, but this study used interspersed pauses—an artificial design unlikely to reflect real practice.
Cohen2013ActiveSummary demonstrated that note restructuring significantly improved exam scores regardless of medium, suggesting what you do after taking notes matters more than how you take them.

The Children’s Research

Your note childrennotes documents a unique study (Horbury & Edmonds, 2021) with 10–11-year-olds that found:

Conceptual understanding was superior with handwritten notes
Unlike adult studies, there were no significant differences in note quantity between conditions
The authors speculated that children’s limited keyboarding experience may have increased cognitive load when typing, a different mechanism than proposed for adults

Your AI-Generated Synthesis

Your note AI response to my question challenging the Luo study that assumed the notes themselves could not result in generative activity offers a compelling reframing:

Luo et al. Conclusion	Modification Research Counter
Laptop notes are transcription-oriented	Generative processing can be added during revision
Longhand notes are better review products	Laptop notes can be transformed into superior products through revision
Laptop notes lack images and signals	These can be added easily using laptop affordances
Reviewing longhand notes yields higher achievement	Studies only tested passive review, not active modification
Longhand is generally preferable	The medium matters less than the strategy

Overall Conclusions From Your Notes

The popular narrative favoring handwriting is overstated. Replication attempts and meta-analyses show inconsistent results.
The mechanism matters: Quantity of notes is positively related to achievement; verbatim overlap is negatively related. These are separate variables that should not be conflated.
Most studies use artificial conditions (immediate testing, brief delays, no real revision opportunities) that don’t reflect actual academic practice.
Revision and post-processing may be more important than the initial recording medium, and computers offer superior affordances for revision.
The real issue is strategy, not medium. Untrained students default to transcription on keyboards and forced summarization by hand—but training could equalize outcomes.
Note completeness matters for the storage function, and the storage function is generally more important than the encoding function (ExternalStorage).

Digital Devices and Effective Studying and Long-Term Note Use

Lately, I seem to encounter a great deal of advice warning against reading and note-taking on a device. Paper and a pencil are argued to be better. In a recent post, I argued that I found these complaints ill-advised. This is a second attempt to present the same argument and a different way to justify my position.

Most simply put, I don’t think the researchers and I are talking about the same thing, even though it seems the anti-tech types would make the case that we are. The research frequently cited reading and taking notes tend to focus on more focused and short-term processes than what I have in mind. My focus, and I think the actual focus of most learners, is more on what I might describe as studying or the use of notes as imagined by the PKM/Second Brain aficionados. When I read a fiction book for pleasure, I might have a better understanding of that book if I read the content on paper. This is very different from how I would best get from reading a textbook to doing well on an exam a couple of months from now. A similar comparison might be made with taking notes during a lecture. I would seldom be taking notes for an exam the same day, but more likely for one week away.

Process Models

I write a lot about process models relevant to understanding and developing both learning skills and the knowledge that results from applying those skills. The process model of writing (Flower & Hayes) makes a good example. These researchers proposed that a process model of writing was useful to researchers because the model identified subskills that could be studied to see how these contributing skills might explain the performance of more and less effective writers and to educators trying to understand what contributing behaviors might be isolated for practice and development.

I suggest that the same type of process model would be helpful for developing study skills and for taking a different look at the possible advantages of using digital devices for reading and note-taking. The argument in this second case is that research comparing tech vs. traditional approaches has overlooked important processes in studying and note-taking applications.

Processes in tasks involving the collection and eventual application of information

There have been efforts to identify the processes involved in translating a presentation (e.g., a lecture or book chapter) into intended applications. Several researchers (e.g., Cojean & Grand, 2024; Flanigan et al., 2023; Luo et al., 2016) have extended the original two-stage model (note-taking and external storage) to emphasize the importance of revision. Returning to the importance of multi-process models in understanding the potential issue of whether it matters if one takes notes on paper or using a device, the studies differ. Flanigan and colleagues engaged the unusual practice of inserting pauses during a presentation to allow for revision and found that those taking notes by hand created more revisions. In contrast, Cojean and Grand found that after class those taking notes on a device made more revisions. Systems of taking notes, for example Cornell Notes (Pauk & Owens, 2011) and recent PKM systems (Ahrens, 2022; Forte, 2022), differentiate revision as a separate process in the use of notes.

In the spirit of the writing process model, I have created my own identification of note-taking and note-using processes listed as a sequence with the recognition that notetakers frequently revisit earlier processes after finding a limitation in what a later process makes available. The sequence of descriptors for these processes follows.

Collecting
Considering
Elaborating
Exporting

Collecting – creating a representation of content (presentations, videos, text material) for use in the future

Examples – creating annotations, notes, highlights

Considering – offline processing of the information collected for personal understanding and to evaluate gaps in understanding

Examples – rewrite existing notes based on comparison of personal collection with that of peers, return to source material to fill in gaps

Elaborating – speculation based on personal understanding of original information for fit within existing knowledge and potential application

Examples – links to existing notes on similar topics, Internet searches to locate and augment existing notes with additional examples of key concepts

Exporting – use of cumulative stored content to meet personal or assigned goals

Examples – test performance, assigned writing tasks, personal writing projects

The Processes and The Question of Handwriting vs. Digital

My contention is that when tasks involve all of the processes I have identified, digital tools offer advantages in the efficiency of collection, storage, search, and manipulation. These advantages are magnified when the task’s time frame is extended and initial goals are unclear. I have written at length on these topics and I have tried to organize some of these posts, organized by process, below. I have avoided considering how AI might be used in these processes, but such engagement would be far easier if working in a digital environment.

Collecting

Take digital notes for best lecture performance

Note and highlight extraction for efficient review and storage (Readwise for books, Highlights for PDFs)

Considering

Note and highlight extraction for efficient review and storage (Readwise for books, Highlights for PDFs)

The Power of Collaboration: Enhancing Your Note-Taking Experience

Preserving context in digital writing

Elaborating

Smart Connections finds note connections

Highlighting in the age of digital content

Notes and the Translation Process

The Space Between Encountering Information and Application

Digital for serious reading tasks

School and Professional Note-Taking

Exporting

School and Professional Note-Taking

Resources

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

Cojean, S., & Grand, M. (2024). Note-taking by university students on paper or a computer: Strategies during initial note-taking and revision. British Journal of Educational Psychology, 94, 557–570. https://doi.org/10.1111/bjep.12663

Flanigan, A. E., Kiewra, K. A., Lu, J., & Dzhuraev, D. (2023). Computer versus longhand note-taking: Influence of revision. Instructional Science, 51(2), 251-284

Forte, T. (2022). Building a second brain: A proven method to organize your digital life and unlock your creative potential. Simon and Schuster.

Luo, L., Kiewra, K. A., & Samuelson, L. (2016). Revising lecture notes: How revision, pauses, and partners affect note-taking and achievement. Instructional Science, 44(1), 45-67.

Pauk, W., & Owens, R, (2011). How to study in college. Boston, MA: Wadsworth, Cengage Learning.

What does the role of revision in classroom note-taking research offer PKM advocates?

Most of what I write about PKM and Second Brain focuses on relating the vast body of high-quality research on academic note-taking to what many of us do outside the classroom as independent learners. The nonclassroom use of notes and related strategies for making and using notes has been termed Personal Knowledge Management (PKM) by those offering self-improvement advice. The PKM area is driven mainly by common sense. I cannot find focused research to inform this transition, but I have been investigating classroom note-taking and studying for decades and now focus on synthesizing findings from one area to support or evaluate strategies in the other.

The classroom research primarily focuses on the interrelated tasks of taking and reviewing notes, and, more recently, on handwritten versus keyboarded notes. With PKM, there is a greater emphasis on continually revisiting stored notes. This topic has not been emphasized in the research with classroom notes, but some studies do exist and it is this more minimal area I want to explore in this post. Again, the advantage is in the research evaluating efficacy and what cognitive processing is enabled or encouraged in modifying original notes in various ways.

I now primarily focus on note-taking on a digital device. While studies have focused on whether handwriting is superior for initial learning, approaches that encourage a deeper look at your notes reveal a powerful consensus that transcends the medium: there is unique value in notes that involve not just how notes are taken, but in how notes are revised.

This insight provides a critical link between academic research on learning and the practical strategies of Personal Knowledge Management (PKM). If your goal is to move beyond simply collecting information to actively building a knowledge base, you must embrace the often-overlooked middle stage of note-taking: revision and restructuring.

The Three-Stage Model: Beyond Capture and Review

Traditional study advice often reduces note-taking to two phases: recording during a lecture or reading and reviewing before an exam. However, classroom-oriented research by Luo et al. (2016) and Flanigan et al. (2023) suggests a more productive, three-stage process: recording, revision, and review. This intermediate revision stage is where the magic happens – where passive information capture transforms into active knowledge construction.

The research on this topic is compelling. A study by Cohen et al. (2013) demonstrated the causal role of a note-restructuring intervention in improving student learning. Students who were required to restructure and reorganize their notes, summarize the main point, and elaborate on a detail performed significantly better on exams. The researchers concluded that this process was essential for students to “make information one’s own, by processing it, restructuring it, and then presenting it in a form so that it can be understood by others (or by oneself at a later point).”

Sounds very similar to the pitch for PKM strategies. Revision isn’t just about neatness or completion; it’s about deepening understanding through elaboration, incorporating entirely missed ideas, and creating retrieval cues that activate deeper memory networks.

From Note-Taking to Note-Making

In the world of PKM, a distinction is often made between note-taking (the act of recording external information) and note-making (the act of processing that information into a new, personalized, and connected knowledge item). The revision stage is precisely where you transition from a passive note-taker to an active note-maker.

PKM methodologies, such as the Zettelkasten, emphasize that a permanent note should be able to stand alone, expressed in your own words, and contain enough context to be meaningful without referring back to the original source. This is a direct parallel to the restructuring intervention that required students to summarize the main point and elaborate on a detail.

When you revise a note in an academic setting, you are performing the cognitive work that drives learning: elaboration (connecting new ideas to what you already know), organization (clarifying underlying structure and identifying themes), and synthesis (cross-referencing the new idea with other sources). Without this deliberate revision, you risk falling into a common trap: mistaking familiarity for understanding. Most learners fail to organize their notes after class because they recognize the content and mistakenly assume they have mastered it. Active processing, often based on concepts such as generative processing, is the focus of much research.

The Longhand Advantage in Revision

The handwriting versus keyboard comparison recurs in studies of revision. Some, but not all, studies contradict my assumptions about the advantages of a digital approach. Flanigan et al. found that longhand note-takers added three times as many complete ideas to their notes during revision compared to computer note-takers, and twice as many partial ideas. These researchers argue that handwriting engages deeper cognitive processing during initial recording, making those notes more effective retrieval cues when revisited later.

However, the digital environment isn’t without its strengths. Research by Cojean and Grand (2024) found that students who take notes on a computer are more likely to reformat their notes during revision. The ease of manipulating text digitally encourages a strategy where transcription is prioritized during capture, and the deeper work of reformulation and organization is deferred until the revision stage.

In a modern PKM system, this deferred processing is not a weakness, but a feature. Digital tools make it effortless to refactor (break long notes into smaller, single-idea notes), link (create hypertext connections between related ideas), and organize (file processed notes into multiple collections). The digital environment transforms revision from a tedious manual task into a fluid, creative act of knowledge gardening.

Making Revision Your PKM Habit

Those offering practical advice for students seem to recommend a structured approach to the revision stage. Treat it as a non-negotiable part of your workflow, not an optional step before an exam. Here are three practical revision strategies:

The “Foot” and “Socks” Method: Immediately after capturing a new note, summarize the main point in a concise “foot” (like a title or summary field) and elaborate on a key detail in the “socks” (the body of the note). This forces immediate processing and mirrors the Cohen et al. intervention.

The Atomic Note Refactor: If your initial note is a long transcription, dedicate time to breaking it down into smaller, single-idea notes. Write each new note in your own words and link it to at least one other existing note in your system. This practice creates the interconnected knowledge web that makes PKM powerful.

The Cross-Reference Check: When revising, actively search your existing notes and collections for related concepts. Link your notes back to original sources to resolve ambiguities and provide context. Make an effort to relate lecture content to what appears in your textbook. This is the moment to create connections that integrate new information into your existing knowledge structure, moving beyond simple storage to true knowledge management.

Schedule dedicated revision sessions, ideally spaced throughout your learning timeline rather than clustered after completion. Consider handwriting your first draft or deeply processing material before digital capture to maximize the depth of your initial notes. Make note revision an ongoing habit, integrated into your learning cycles rather than a single end-of-lesson task.

Conclusion

By making revision a deliberate and structured part of your note-taking, you stop merely collecting information and start actively building a powerful, interconnected knowledge base that supports long-term learning and creative work. The research is clear: revision elevates note-taking from passive transcription to active knowledge building. It transforms fragmented jottings into complete, interconnected ideas ready for recall and application.

For anyone committed to lifelong learning and effective Personal Knowledge Management, understanding and embedding the practice of careful, thoughtful revision into your workflows will create richer, more useful knowledge bases – helping you learn smarter, not just harder. Classroom studies encourage a structured approach and often control such activities through assignments. Independent learners must take personal responsibility to produce similar results. The missing link in your note-taking isn’t the tool you use or the speed at which you capture—it’s the intentional work of revision that transforms information into true personal knowledge.

References

Cohen, D., Kim, E., Tan, J., Winkelmes, M. (2013). A note-restructuring intervention increases students’ exam scores. College Teaching 61(3), 95-99.

Flanigan, A. E., Kiewra, K. A., Lu, J., & Dzhuraev, D. (2023). Computer versus longhand note taking: Influence of revision. Instructional Science, 51(2), 251-284

Luo, L., Kiewra, K. A., & Samuelson, L. (2016). Revising lecture notes: how revision, pauses, and partners affect note-taking and achievement. Instructional Science, 44(1), 45-67.

Building Better Note-Taking Skills in Elementary and Middle School Students: Research-Backed Strategies for Educators

Note-taking is a foundational skill that supports comprehension, retention, and critical thinking. However, many students below high school age struggle to develop effective note-taking habits on their own. There is comparatively little research on the development of note-taking skills in K12 compared to higher education, and within K12, the development of note-taking skills in elementary and middle schools receives extremely little attention. Still, from typically fourth grade on, it is commonly accepted that the goal in reading skills switches from learning to read to reading to learn.

While I have always been interested in note-taking research and practice, my wife and I worked with a second-grade teacher to explore our early ideas about the creation of multimedia projects as learning opportunities. Pam Carlson, our elementary teacher colleague, was preparing her students to participate in what we called the butterfly project, in which they were learning about the life stages of butterflies, migration, and other relevant topics related to butterflies. Students were creating a HyperCard stack to share what they had learned, and each student selected a specific butterfly to describe in the card they created for the stack. In reviewing various books Pam provided students as resources, she offered the following instructions to guide the information students wrote down. When you find something you want to include, she suggested, think about that information carefully and then turn your book over so you will write down what you learned without copying from the book. I could rephrase her instructions in the way researchers would describe the goals of her required strategy (summarization, personalization, generative processing, etc.) when I taught or wrote about note-taking, but these concrete instructions still pop into my memory when I address the topic.

This post summarizes the few studies I was able to locate that I thought would be relevant to educators who work with younger students and I will try to describe what seems to me to be the implications for classroom implementation. As always, more work is needed. One basic observation that probably seems obvious to most educators, the studies I reference here, Ilter (2017), Lee et al. (2013), and Chang & Ku (2014), highlight the importance of explicit instruction and scaffolded strategies to help young learners master note-taking skills. An interesting generality about note-taking seems to be that while nearly all learners take notes in some form or another, few of any age experience direct instruction and evaluation of this important skill.

Below, you will find key recommendations from these studies to help educators guide their young students toward becoming capable note-takers.

1. Explicit and Scaffolded Instruction of Note-Taking Strategies

One of the most important takeaways from the research is that note-taking skills should not be left to chance. Ilter (2017) emphasizes the need for early and explicit instruction in note-taking, starting in elementary school. Students often lack the intuitive ability to identify key information or organize their notes effectively, so educators must provide clear guidance.

Scaffolding is a critical component of this instruction. As the word implies, scaffolds are supports offering structure. A partial outline makes a reasonable example. Teachers should begin by modeling note-taking strategies and gradually shift responsibility to students as they gain confidence. For example, early lessons might involve guided practice with teacher feedback, while later lessons encourage students to take notes independently. This gradual release of responsibility ensures that students build the skills they need to succeed on their own.

2. Writing in Their Own Words

One of the biggest challenges for young students is avoiding verbatim copying. As I previously mentioned, Pam Carlson’s strategy for her second-grade students is noteworthy. Ilter (2017) and Lee et al. (2013) stress the importance of teaching students to paraphrase information in their own words. This practice not only improves comprehension but also helps students engage more deeply with the material. A related skill was brevity. One researcher liked the label “terse”. So, the goal was not just to paraphrase, but to focus on key or interesting ideas.

To support this skill, educators can:

Model how to paraphrase by thinking aloud during lessons. A think-aloud is simply an effort to externalize your thinking. It is a common strategy suggested to help learners get a grasp on mental behaviors they cannot see.
Provide practice exercises where students rewrite sentences or paragraphs in their own words.
Emphasize the value of organizing information logically, rather than simply copying it.

By focusing on paraphrasing and organization, students can develop a more meaningful understanding of the material they are studying.

3. Guided and Partial Graphic Organizers

Lee et al. (2013) highlight the benefits of using guided notes and partial graphic organizers to support young learners. Researchers often use the label “scaffolding” to describe this strategy. The goal is to offer guidance and reduce the “cognitive load” beginners face with a new skill. These tools reduce cognitive load by helping students focus on the most important information, rather than trying to capture everything at once.

For example:

Provide students with partially completed notes that include blanks for them to fill in during a lesson.
Use written prompts to guide students in identifying main points, summarizing content, and organizing their notes.

These strategies are particularly effective for elementary students, who may struggle to process and record information simultaneously. By reducing the mental effort required, guided notes and graphic organizers allow students to concentrate on understanding the material.

4. Focusing on Key Ideas, Keywords, and Text Structures

Chang & Ku (2014) emphasize the importance of teaching students to identify and use key ideas, keywords, and text structures in their notes. Their research with 4th graders provides several practical strategies for educators:

Highlighting Main Ideas: Teach students to use titles, headings, and guiding questions to identify the most important information in a text.
Recognizing Keywords: Help students identify function words like “however,” “because,” and “therefore,” which signal relationships between ideas.
Using Visual Aids: Introduce charts, diagrams, and other visual tools to represent similarities, differences, and other relationships. For example, how are moths and butterflies the same and different?
Analyzing Text Structures: Teach students to recognize organizational patterns, such as sequences or classifications. Is the author describing the steps in a process or the characteristics of a phenomenon or concept you should list in your notes.

These strategies not only improve the quality of students’ notes but also enhance their ability to understand and retain information.

5. Practice and Feedback

Finally, practice and feedback are essential for developing strong note-taking skills. Ilter (2017) recommends providing students with ample opportunities to practice taking notes independently. This practice should be paired with regular feedback from teachers and peers to help students refine their techniques.

For example:

After a lesson, ask students to share their notes with a partner and discuss what they found most important.
Provide specific feedback on how students can improve their notes, such as by adding more keywords or organizing information more clearly.
Encourage students to revise their notes based on feedback and reflect on what they learned.

By creating a supportive environment where students can practice and receive constructive feedback, educators can help them build confidence and competence in their note-taking abilities.

The Integrated Process

Itar suggests a sequence educators can follow in working with students to develop these skills.

The Five-Step Instructional Model for Note-Taking

Ilter (2017) introduces a structured five-step approach to teaching note-taking, which can be applied to both reading and listening tasks. This model provides a clear framework for students to follow, making the process of taking notes more manageable and effective.

Step 1: Identify the Main Idea

Students should learn to highlight or underline important information and paraphrase it in their own words. Teaching them to use textual clues, such as headings or topic sentences, can help them pinpoint the main idea without resorting to verbatim copying.

Step 2: Information Reduction

Encourage students to condense paragraphs into essential points. This step helps them avoid excessive copying and focus on the most critical information.

Step 3: Keyword Identification

Teach students to recognize keywords that signal relationships between ideas, such as “because,” “however,” or “finally.” These words can help students understand the structure of the information and create meaningful connections in their notes.

Step 4: Use of Representations

Introduce visual tools like symbols, charts, diagrams, or graphic organizers to help students organize their notes. These representations make it easier to see relationships between ideas and improve recall.

Step 5: Analysis of Text Structures

Help students recognize text structures, such as headings, subheadings, sequences, and classifications. Understanding these structures allows students to organize their notes more effectively and see how different pieces of information fit together.

Summary

This post is intended as an extension of my previous posts on note-taking focused on academic settings and younger learners. Beginning in approximately fourth grade, learners both read to learn and listen to brief teacher presentations. The skills of taking notes is an important life skill seldom directly taught to learners of any age. Researchers are proposing and describing how elementary and middle school teachers can help students begin to develop these skills.

References

Chang, W., & Ku, Y. (2014). The effects of note-taking skills instruction on elementary students’ reading. The Journal of Educational Research, 108(4), 278–291.

Ilter, I. (2017). Notetaking skills instruction for development of middle school students’ notetaking performance. Psychology in the Schools, 54(6), 596-611

Lee, P., Lan, W., Hamman, D. & Hendricks, B. (2008). The effects of teaching notetaking strategies on elementary students’ science learning. Instructional Science, 36(3), 191–201.

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.

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.

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.
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.
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.

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.
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).
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.
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.

Academic Studying – History of Note-Taking Research, Note-taking as a Generative Activity, Cornell Notes and Beyond
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.
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.

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.