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.
I became interested in the development of writing skills through feedback focused on alternatives to the teacher or professor as editor. I worked with educators who developed writing skills and was acquainted with the time demands of providing feedback and had my own experience reviewing students’ theses and dissertations. When you have read the 200+ page dissertation of a Ph.D. candidate through a couple of drafts, you have put in some hours. I felt sorry for the English department English composition adjuncts paid a few thousand for each of 4 sections of 25 students and the time it would take to review multiple writing assignments. Still, you learn to write by writing, and feedback and rewriting in response to feedback are essential.
There are ways to provide an acceptable alternative source of feedback. Peers and now AI can critique writing, and while some more expert involvement is important, the quantity and diversity of learning activities required for skilled performance cannot consistently be monitored by instructors.
I began reviewing the research on peer editing because I was aware of the time issue faced by instructors, but also because I was interested in the role digital word processing tools could play in the feedback and revision processes. For example, Google docs offers a great way to add comments at precise locations in a document and to exchange related remarks as a document is passed back and forth between the writer and reviewer. Revision is efficient and can be explained if the editor wants to take a second look. I thought that Goodle docs offered an example of a tool that would improve the efficiency with which learners could interact with peers and then rewrite efficiently in response to comments.
As I reviewed the research literature, I came across some studies that changed my thinking on how I should advocate for peer feedback. These studies (see Cho references at the end of this post) demonstrated that peer editing also had an impact on the writing performance of the editors, and this benefit might be more important than the feedback a writer received from others. The Cho research focused on a specific population of writers generating a particular type of writing product, and understanding the focus of such research is always important in considering how and if findings might generalize to other situations. Cho focused on college students writing lab reports, i.e., the description and results of experiments performed in the lab. I know my own profession has an undergraduate course (Research Methods) with a core focus on the same type of writing task. Cho conducted several studies in which peer editing was a component. Students could either review their lab reports without feedback, with feedback, or with feedback after providing feedback on the same task to other students. The greatest difference was found when writers also provided feedback to others. When it came time to revise their own original drafts, the product they produced was judged to be superior, on average, to the products generated by those in the other groups. Moreover, statistical analysis showed that editing had a more powerful impact than having the edits of others to review.
The researchers offered two possible explanations for their findings. First, they proposed that the process of editing provides a perspective on how others might view a written product (audience effect). Writers are always told to consider their audience, but perhaps serving as the audience might provide insight into what that means for a specific written product. The other explanation involved what I would describe as a generative effect. Serving as an editor has some similarities to the research topics of writing to learn and teaching to learn. When you must externalize a position you take, this forces a concreteness and specificity you may fail to generate when just thinking about something. Having to put a position into words can lead to the understanding that you really can’t explain yourself or make you work to come up with a concrete way to express what you think.
This notion that working to improve understanding and develop proficiency seems to be raised repeatedly as educators grapple with the role AI should play in educational settings. For all of the ways AI might reduce “busy work,” there seems to be a related potential that AI provides a way to avoid the cognitive work so necessary in developing a cognitive skill. So, while AI may provide a way to provide feedback to students, there is also evidence that the work of providing feedback to others involves work that is productive both for others and for yourself. Educators face a significant challenge in communicating this reality to learners and other stakeholders.
When it comes to how we use technology, familiarity can limit analysis and exploration. I started thinking about this challenge when encountering the work of an academic who has examined the history of word processing. When I first wrote about word processing in the 1990s, the issues were similar to current topics of whether students should read from paper or screen and whether it was better to take notes on paper or on a laptop. There were comparisons of which method was more productive and efforts to account for the advantages that were identified. It was once similar with word processing. Should students learn to write on paper or using a computer? What were the advantages and disadvantages of each approach? How might the instruction of writing skills with computers be modified to take advantage of the unique capabilities of a digital approach? My thought is that many are now no longer aware of these questions and conclusions and that personal practice and instructional emphases may ignore key findings. This concern seems especially relevant given the new issues raised by the use of AI in writing and learning to write.
I decided to write again about this topic after listening to an interview with Matthew Kirschenbaum on the “This Week in Tech” network’s “Intelligent Machines” podcast focused on Kirschenbaum’s recent focus on the role of AI in writing and learning to write. The podcast guest was a member of the Modern Languages Association (MLA) panel, generating what are likely to become several influential position papers on learning to write and AI. This interview, which makes up maybe the first half hour of the podcast, is worth the attention of any educator trying to make sense of how AI will impact schools and universities. As part of the brief introduction of the podcast guest, Krischenbaum it was noted that the guest had recently written “Trach Changes: Literary History of Word Processing”.As I suggested, word processing had been a personal interest so I did purchase and read the book.
It wasn’t that the book wasn’t well written, but I did struggle to get through it. The podcast focus resulted in my misunderstanding of the topic of the book. The history of the transition from writing on paper and typewriter was of some interest, because I lived through that transition and the mention of technology hardware and software and the required skills involved in writing with a computer brought back plenty of memories. I was less interested in which noted author had made his or her transition from a notepad or typewriter to a word processor during their career. Concerns of the reading community related to how technology might influence literature likely offers similar insights into what some think about AI. A better example might be how Bob Dylan’s fans reacted when he switched from acoustic to electric guitar. What I had falsely anticipated was that the author would examine how digital storage and revision changed writing and the teaching of writing.
I imagined I would encounter an analysis of changes in personal revision, educator feedback and learner revision, peer revision, and possibly even AI as a sounding board for a writer’s efforts. These are the topics in what I see as the evolution of writing and writing education. I decided to generate a post that would offer my own thoughts about the role of word processing in the writing process. The podcast and the book on word processing are still worth your time.
Will digital tools change our writing?
I assume you complete many of the writing tasks you take on using a word processing application. Do you do this because you assume this approach makes you more efficient or do you assume this approach makes you a better writer? Maybe you have never even thought about these questions. However, when functioning as a teacher and asking your students to engage in activities in a particular way, it may be helpful to consider why the approach you expect students to use will be productive. Often, to realize the full potential of an activity, the details matter and some insight into why an approach is supposed to be productive may be helpful in understanding which details to track and emphasize. The following comments summarize some ideas about the value of word processing and of learning to write using word processing applications.
In learning, as in other areas of life, you seldom get something for nothing. Still, a logical case has been proposed for how simply working with word processing for an extended period may improve writing skills and performance. Perkins (1985) calls this the “opportunities get taken” hypothesis. The proposal works like this. Writing by hand on paper has a number of built-in limitations. Generating text this way is slow, and modifying what has been written comes at a substantial price. To produce a second or third draft requires the writer to spend a good deal of time reproducing text that was fine the first time, just to change a few things that might sound better if modified. Word processing, on the other hand, allows writers to revise at minimal cost. They can pursue an idea to see where it takes them and worry about fixing syntax and spelling later. Reworking documents from the level of fixing misspelled words to reordering the arguments in the entire presentation can be accomplished without crumpling up what has just been painstakingly written and starting over.
With word processing, writers can take risks and push their skills without worrying that they may be wasting their time. The capacity to save and load text from some form of storage makes it possible to revise earlier drafts with minimal effort. Writers can set aside what they have written to gain new perspectives, show friends a draft and ask for advice, or discuss an idea with the teacher after class, and use these experiences to improve what they wrote yesterday or last week. What we have described here are opportunities—opportunities to produce a better paper for tomorrow’s class and, over time, opportunities to learn to communicate more effectively.
Do writers take the opportunities provided by word processing programs and produce better products? The research evaluating the benefits of word processing (MacArthur, 2006; Wollscheid, Sjaastad, & Tømte, 2016) is not easy to interpret. Much seems to depend on the experience of the writer as a writer and familiarity with word processing, and on what is meant by a “better” product. If the questions refer to younger students, it also seems to depend on the instructional strategies to which the students have been exposed. It does appear that access to word processing is more beneficial for older learners and some even interpret this difference as having a neurological basis (Wollscheid, Sjaastad, & Tømte, 2016). General summaries of the research literature (e.g., MacArthur, 2006) seem to indicate that students make more revisions, write longer documents, and produce documents containing fewer errors when word processing. However, the spelling, syntactical, and grammatical errors that students tend to address and the revision activities necessary to correct them are considered less important by many interested in effective writing than changes improving document content or document organization. The natural tendency of most writers appears to be to address surface-level features.
Writers appear to bring their writing goals and habits to writing with the support of technology. Beginning writers and perhaps writers at many stages of maturity may not have the orientation or capabilities to use the full potential of word processing, and their classroom instruction may also emphasize the correction of more obvious surface errors. Thus, there are typically improvements in the products generated when working with word processing tools, but the areas in which younger writers seem to improve are not necessarily the most important ones
Many of the potential educational advantages of word processing appear only as students acquire considerable experience writing with the aid of technology and some question whether using a keyboard is better than a pencil for young writers (Wollscheid, Sjaastad, & Tømte, 2016). Perkins’s (1985) argument that writing with word processing programs will improve writing skills because word processing allows students to experiment with their writing makes sense only in situations in which students have written a great deal and experimented with expressing themselves in different ways. The fact that most research evaluating the benefits of word processing has examined performance over a short period of time, with students having limited word processing experience, thus represents a poor test of the potential of word processing (Owston, Murphy, & Wideman, 1992). Research based on a three-year study following elementary students as they learned to write with and without access to word processing opportunities has demonstrated a significant advantage for students with ready access to technology (Owston & Wideman, 1997). A recent study (Yamaç, et al., 2020) examining the benefits of consistent writing on laptops found a similar advantage in contrast to paper and pencil writing tasks for early elementary learners. These researchers point to social media activities such as blogs and multimedia writing with tablets as expanding the writing opportunities available in classrooms.
The National Assessment of Educational Progress (NAEP) demonstrates that in the U.S. greater experience writing with technology is predictive of schools with more proficient writers (Tate, Warschauer & Abedi, 2016). Studies such as this are still controversial as it is difficult to parse out other variables such as the income levels of the majority of students in different schools that may influence both access to technology and writing proficiency. Overall, the role of word processing in developing writing skills depends on the goals of the teacher and individual students, the social context provided for writing, and the amount of writing that students do with the assistance of word processing.
Summary
Many of the posts I write concern the cognitive processes involved in learning, thinking, and academic behavior. Often, I focus on how these processes are impacted for good or bad by involving technology. We seem to be past the point at which educators question writing on a computer, but the distinction I raised between opportunities get taken and desirable difficulty have yet to be resolved with writing. This is clearly the case when educators debate the role AI should play. My suggestions related to the opportunities get taken hypothesis should also be approached would even be that we examine whether the opportunities (often called affordances) of revision are actually employed. Do students get useful feedback from which they might learn to improve what they have written? Despite the likely benefit of revision, do students quantitatively do much revision? Perhaps like other ideals (tutoring, personalizing learning) that are impractical for one reason or another (e.g., cost, teacher time), AI might find a productive role in guiding revision experiences.
References:
MacArthur, C.A. (2006). The effects of new technologies on writing and writing processes. In C.A. MacArthur, S. Graham, & j. Fitzgerald (Eds.) Handbook of Writing Research, pps. 248-262. New York: Guilford.
Owston, R., Murphy, S., & Wideman, H. (1992). The effects of word processing on students’ writing quality and revision strategies. Research in the Teaching of English, 26 (3), 249–276.
Owston, R., & Wideman, H. (1997). Word processors and children’s writing in a high-computer-access setting. Journal of Research on Computing in Education, 30 (2), 202–220.
Perkins, D. (1985). The fingertip effect: How information-processing technology shapes thinking. Educational Researcher, 14, 11–17.
Tate, T. P., Warschauer, M., & Abedi, J. (2016). The effects of prior computer use on computer-based writing: the 2011 NAEP writing assessment. Computers & Education, 101, 115-131.
Wollscheid, S., Sjaastad, J., & Tømte, C. (2016). The impact of digital devices vs. Pen (cil) and paper on primary school students’ writing skills–A research review. Computers & Education, 95, 19-35.
Yamaç, A., Öztürk, E., & Mutlu, N. (2020). Effect of digital writing instruction with tablets on primary school students’ writing performance and writing knowledge. Computers & Education, 157, 1-19.
Google recently offered NotebookLM users an exciting opportunity. Personal Notebooks can now be shared with others. The shared version is read-only, so the curator need not worry that unknown individuals could modify the existing work. Collaborative use of such a tool would represent a different opportunity.
I have written multiple posts focused on note-taking, collaborative note-taking, and the focus of AI on personal notes. These posts were related to, but a side focus of a career as an academic investigating study behavior and examining the application of cognitive theories of learning to taking notes. In a way, I have taken notes for years, focused on note-taking research. I have access to digital notes and highlights associated with hundreds of journal articles and books.
In a recent post, I described my approach to uploading a large body of these notes into NotebookLM, and now I can offer this content to any interested individual. I encourage you to take a look. What might be unique about my content is the amount of material and the personal process of generating this content through annotation and highlighting. My hope is that others will make similar offers.
When you use the link I provide (end of post), you will encounter the following interface. Ignore the references to Obsidian — this is the tool I use to accumulate digital content. This material was uploaded to NotebookLM. Try chatting with my content — green box in the middle, or use some of the suggestions made under the rightmost Studio column. I accumulated content mostly focused on study behavior, classroom applications of technology, and reading skills.
Here is a sample prompt you might try — How does the effectiveness of taking notes on paper compare with taking notes using a digital device?
Here is the link for access. It is not necessary, but if you have a reaction, I would appreciate a comment. Again, I think there is an opportunity for sharing here and hope offering my notes will provide an example.
My recent focus on losing an author’s perspective when consuming AI-generated content, particularly the AI response now preceding the typical hits generated by a search query, has encouraged a personal exploration of what might be a middle ground. I frequently use AI tools to chat with the notes and highlights I have generated in reading hundreds of journal articles and books. This body of content has a perspective of sorts because the notes I generate and the content I identify through highlighting reflect my personal way of viewing my field and represent ideas that both support and oppose scientific concepts and theories important to these topics. Any researcher who has relied on the accumulation of relevant articles over the years and makes use of PDFs rather than paper could do a similar thing to make extended use the content they have accumulated over the years. This accumulated body of content seems a great example of what the personal knowledge management advocates describe as a second brain.
Here, then, is what I believe to be an interesting question. Do AI chats with personally curated content provide different insights than a similar AI chat without this curated focus? Perhaps a more concrete example would be a better way to communicate my issue. So, I have the highlights and notes I have accumulated from years of reading in a designated area (e.g., educational applications of cognitive psychology), and I can chat with this content using identifiable services (e.g., NotebookLM). Would the reply to a prompt applied under these circumstances yield different insights than the same prompt applied using an AI tool not focused on a designated body of content (e.g., Perplexity)?
At first, this might seem a silly comparison. Certainly, one could find a biased assortment of resources taking a common flawed view on a topic, and then show that AI limited to consolidating this content would yield different prompt replies than similar prompts asked of an unfocused AI tool. But this does not seem to be what those building a second brain think they are doing. They would likely be offended by the suggestion that their efforts were for naught, and AI queries would yield more accurate information. They would probably suggest they are doing exactly the opposite. They are using their expertise to identify high-quality sources, and their notes would address both the strengths and weaknesses of the sources they curate. I am not certain the outcome of my proposed comparison is obvious.
My Test Case
I write a lot about study behavior and have found the controversy involving whether learners are better off reading and taking notes using paper or digital content of some interest. While many researchers suggest paper is superior, my personal experiences and focus on the benefits of previous learning experiences over time, see a unique value in digital processing. Simply put, highlights and annotations saved and organized offer advantages over a year or 50 years later that most would find difficult to replicate with paper. Even over short periods, studying is more than simple review, and digital tools offer unique opportunities for “post processing”.
The specifics here are important only if the type of information generated in pursuit of the information I encounter would change as a function of how I might use AI. I provide the background material because the topic could interact with the different uses of AI I identify in ways I cannot anticipate. Part of what I propose is that others with different collections of digital content might replicate the test I am applying to their own material and share their observations. There are so many uncontrolled variables I assume that while this is an interesting issue, personal preference will always be the deciding factor. Variations in topic, tool, and prompt could result in different conclusions.
The Prompt I used follows. The variation of the prompt I used when engaging a non-focused use of AI simply eliminated the phrase “Using my notes and highlights”.
Prompt: Using my notes and highlights, write a 400 word blog post comparing the advantages and disadvantages of reading and taking notes from paper and digital devices.
I used the directed prompt with Mem.AI, NotebookLM, and Smart Connections (Obsidian plugin). Perplexity was used as the nondirected AI tool. I will offer my observations first and provide the full prompt responses at the end as Appendices.
Sources – Perplexity is unique in comparison to other chat tools in that it provides specific sources for comments it generates. These tend to be what I would call secondary sources (see list following the Perplexity example). In contrast, see the sources in the Mem.AI responses. The names that appear are a crude version of the citation method academics use to reference journal articles and books (which were the sources I highlighted and annotated). One way to think about this may be that Perplexity is accessing the summaries generated by various individuals who have read primary sources, while Mem is accessing my personal summaries of similar sources. If identifying primary sources is important, it is easier to do this when you can show what these sources were.
Identification of unique insights – It would seem that an AI analysis based on specific notes, highlighting, and source selection would generate an output more useful for tasks you want to pursue. While obvious if the content of interest was selected with a task in mind and based on a small amount of material, this is not the way a “second brain” is built. The hundreds of sources I have collected represent a wide range of topics in my field. Specific topics of interest emerge within this process of more general learning, and part of the assumption in using a second brain is that the broader background will reveal connections that may not have been anticipated. The hope is that the application of AI, rather than basic searching, will help surface such connections.
With the exception of the sources cited, much of the information in the two types of searches was similar. Perhaps asking for a 400-word blog post as an outlet was not the best way to reveal subtle differences. I will direct your attention to sections I have highlighted in the NotebookLM and Perplexity prompt responses. Both NotebookLM and Perplexity provide citations that do not appear when copying the text. Because I was looking for comments related to the use of content over time, I was paying attention to any mention of searching or other mentions of delayed activity. The Perplexity response did not offer a citation. The NotebookLM output mentioned export, organization, and search. In addition, there were multiple citations, and the linked citations identified notes and highlights in the digital form.
Summary
AI tools with various capabilities are now available. For those of us who read digitally, we have the opportunity to export highlights and annotations that can be stored over time. AI can be used to chat with this stored content. My interest here was an attempt to determine if there was a unique value in applying AI to such content in comparison to asking questions of AI without this targeting of curated information.
I doubt the effort I describe here would convince anyone to change their existing strategy, but my hope is that I have offered an approach they might try to explore the options that are available.
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Appendices
Mem.ai
The debate between reading and taking notes on paper versus digital devices is a nuanced one, with research highlighting various advantages and disadvantages for each medium. While digital tools offer convenience and speed, traditional paper methods often promote deeper cognitive engagement.
Advantages of Digital Reading and Notetaking
Digital devices offer several benefits. For instance, digital note-takers tend to record more content, including more verbatim lecture strings, due to faster typing speeds compared to handwriting Luo et al 2018. This increased volume of notes can be beneficial for later review, especially when notes are not immediately studied Luo et al 2018. Digital platforms also facilitate collaborative note-taking, allowing students to share the cognitive load and potentially create more complete notes Courtneyetal2022. Furthermore, digital tools can offer features like multimedia integration and online research capabilities, enriching the learning experience Yamac et al 2020. For example, digital writing instruction with tablets has been shown to improve writing performance and knowledge in primary school students, partly due to features like class blogs and multimedia components Yamac et al 2020.
Disadvantages of Digital Reading and Notetaking
Despite the advantages, digital reading and note-taking come with notable drawbacks. A significant concern is the potential for distraction. Studies suggest that the perceived advantage of longhand note-taking in some research may be attributed to the distractions inherent in digital devices, such as web surfing and social media Voyer 2022 summary. This can lead to shallower processing of information SingerAlexander2017b. Research indicates a “screen inferiority” effect, where reading comprehension can be lower on digital devices, particularly for informational texts and under time pressure Delgado2018. This effect has even been observed to increase over time Delgado et al 2018. The lack of physical cues, like the feel of pages, in digital reading can also hinder the formation of a mental map of the text, impacting comprehension of chronology and temporality Mangen et al 2019.
Advantages of Paper Reading and Notetaking
Paper-based methods often foster deeper engagement and better retention. Handwriting, being slower than typing, forces individuals to process and summarize information, leading to a more generative encoding of knowledge MuellerOppenheimer2014. This deeper processing can result in better performance on conceptual questions
MuellerOppenheimer2014. The physical act of writing and the tactile feedback from paper contribute to a stronger mental representation of the material Mangen et al 2019. For instance, studies have shown that paper readers are better at recalling “other relevant information” and performing better on questions related to key points SingerAlexander2017b.
Disadvantages of Paper Reading and Notetaking
While beneficial for deep processing, paper note-taking can be less efficient in terms of speed and volume compared to digital methods Luo et al 2018. It also lacks the inherent searchability and organizational capabilities of digital notes, which can make retrieval and restructuring of information more challenging SmartWisdom. Converting highlights from paper to more elaborate notes can also be a more cumbersome process Highlighting&fleeting.
In conclusion, the optimal choice between paper and digital depends on the specific learning goal and context. For tasks requiring deep comprehension and conceptual understanding, paper often holds an advantage. However, for efficiency, volume, and collaborative efforts, digital tools offer compelling benefits, provided distractions are managed effectively.
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NotebookLM
Here’s a look at the advantages and disadvantages of reading and taking notes using paper versus digital devices, drawing from the sources provided:
The rise of digital devices has shifted how many people read and take notes. However, research comparing reading from paper and screens reveals a complex picture, with nuances depending on the text type, reader’s age, and even the specific device used. Several meta-analyses indicate a general advantage for reading comprehension when reading from paper compared to screens, particularly for informational texts. This paper advantage has even been found to increase over time. However, this difference is often not seen with narrative texts, and studies comparing reading on tablets specifically have sometimes found smaller or no significant differences compared to print.
When it comes to note-taking, there’s also ongoing debate about the best method. Some studies comparing handwriting and typing notes have found a benefit for handwriting notes, particularly for understanding concepts. This has been attributed to the slower speed of handwriting, which may encourage more summarization and paraphrasing rather than simply transcribing verbatim, leading to deeper cognitive processing. However, other research and meta-analyses have found inconsistent results or no significant overall difference between handwritten and typed notes. Some studies suggest that typing can lead to more complete notes, and note completeness can be related to better performance.
Digital tools offer powerful affordances for reading and note-taking, such as the ease of highlighting and adding annotations directly to the text. Digital notes and highlights can be easily exported, organized, and searched later. Digital environments also facilitate collaborative annotation and note-taking. However, digital environments can also present challenges. They may be more prone to distractions, and frequent use of digital media, particularly for quick interactions with short texts (like social media), may contribute to the development of shallow reading habits like scanning and skimming. Some online content may also have lower linguistic quality.
Ultimately, the effectiveness of reading and note-taking, whether on paper or digitally, depends significantly on the strategies and cognitive processes employed by the reader. While paper might offer some advantages for deep comprehension of informational texts and handwriting for conceptual processing, digital tools provide powerful functionalities for capturing, organizing, and retrieving information, as well as facilitating collaboration. Focusing on how one engages with the material and utilizes the tools, rather than just the tool itself, is likely key to effective learning.
The following is a screen capture of the original view of the highlighted section described above.
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Prompt: Write a 400 word blog post comparing the advantages and disadvantages of reading and taking notes from paper and digital devices.
From: Perplexity
Comparing Reading and Note-Taking: Paper vs. Digital Devices
Choosing between paper and digital devices for reading and note-taking is a personal decision shaped by convenience, effectiveness, and lifestyle. Both formats offer distinct advantages and disadvantages.
Advantages of Paper
Better Comprehension and Retention: Studies show reading from paper leads to higher comprehension and test scores. Students who read print books outperform those who read digitally, and handwritten notes often result in better memory retention compared to typing[1][6].
Fewer Distractions: Paper books and notes keep things simple—no pop-ups, notifications, or temptations to multitask, which helps maintain focus[1][6].
Emotional Connection: Many readers find a deeper emotional bond with physical books, appreciating the tactile experience and the satisfaction of seeing their progress[1].
No Power Needed: Paper never runs out of battery and is always ready to use[1][6].
Disadvantages of Paper
Storage and Portability: Physical books and notes take up space, can be heavy, and are cumbersome to transport, especially when traveling or moving[5].
Accessibility: Finding a specific book or note can be time-consuming, and you must visit libraries or bookstores for new material[5].
Environmental Impact: Paper production contributes to deforestation and environmental harm[5].
Vulnerability: Paper can be easily lost, damaged by water or fire, and is harder to back up[5][6].
Advantages of Digital Devices
Convenience and Accessibility: Digital libraries offer instant access to thousands of titles and notes, all stored on a single device. Searching for information is quick and efficient[3][4].
Eco-Friendly: Digital reading and note-taking reduce paper usage and environmental impact[3][4].
Interactivity and Multimedia: eBooks and digital notes can include videos, images, and interactive elements, making learning more engaging[3][4].
Collaboration and Organization: Digital notes are easy to organize, search, and share. Real-time collaboration and version control are possible, which is ideal for group work[4].
Accessibility Features: Text-to-speech and adjustable font sizes make digital content more accessible to people with different needs[3].
Disadvantages of Digital Devices
Distractions: Devices can tempt users with games, notifications, and other apps, reducing focus[6].
Lower Retention: Typing notes can lead to lower retention compared to handwriting, as it often encourages verbatim transcription without deeper processing[6].
Dependence on Power: Devices need batteries and charging, which can be limiting in certain situations[6].
Cost: Digital devices are more expensive upfront than basic paper and pen[6].
Conclusion
Paper excels in comprehension, retention, and simplicity, while digital devices shine in convenience, organization, and collaboration. The best choice depends on your priorities—whether you value focus and memory or accessibility and efficiency. Many find a hybrid approach, using both formats as needed, offers the best of both worlds.
“Before the web did anything, Hypercard did everything” was the subtitle of an Ars Technica article I cited and liked in 2019. I use it here to celebrate the life of Apple software genius Bill Atkinson following his recent passing. HyperCard played a significant role in my academic career, and while I have written about the personal connections in the past, one more mention seems appropriate. Hypercard, often called a software erector set, was innovative and accurately foretold many future innovations we now take for granted.
Among the unique features were:
Hypertext/hypermedia
Object-oriented programming
Low bar / high ceiling software
I will attempt to call attention to these features as I offer a brief description. I spent hundreds of hours developing educational applications in Hypercard and would love to display some screen captures of my work. Unfortunately, Apple last updated HyperCard in 1998. I do have some old discs with my original work, but neither an appropriate drive nor an Apple operating system suited to run HyperCard. For a few images, I used my phone to capture from a textbook I wrote with my wife in 1996. One more comment. While I did work on HyperCard stacks for hundreds of hours, that was 25 or so years ago, so I may be fuzzy on some of the details.
The analogy – a stack of cards
Card, field, button
HyperCard was based on a hierarchy of objects. The most basic and encompassing element is a stack. A stack is made up of cards. Each card has a background and a foreground to which the user could add elements, such as text, images, text boxes, and buttons. The difference between the background and foreground was important when a card was duplicated. Typically, cards were intended to look the same with only key elements changing (e.g., a unique image, text information). Rather than create each card from scratch, it was possible to duplicate a card to retain the background and then add the unique features.
The following image shows a card from a series of cards built to provide information about the birds most commonly found in North Dakota. There are several text fields and buttons that would be common across all cards, and a unique image and descriptive text for each species. HyperCard, in this case, was used as a type of database.
Adding Action – Hypertalk was the language of HyperCard
Nearly anything done with HyperCard, e.g., opening a stack, clicking on a button, generated what was called an event. Events had no consequence unless there was a handler available appropriate to that event. A handler was pretty much a segment of code that would be executed when the relevant event was encountered. So, for example, mouseUp would respond to a mouse click.
On mouseUp
go next
End mouseUp
This handler added to a button would advance the card from a stack that was visible to the next card.
A unique feature of HyperCard, consistent with the philosophy of low bar, high ceiling, was that HyperCard would write many of the basic event handlers for you. You could do many things without coding, but also use the powerful scripting language, hypertalk, to do much more.
HyperCard came with a large assortment of symbols many appropriate as buttons (first image). However, when added to a card, the symbols were inert unless scripted. It was easy to find and add a button to a card, but then HyperCard was willing to help make the button do something (Button actions 1 and 2). The process here was to select an icon from button choices and then select the desired action.
Some of the button choices
Button Actions 1
Button Actions 2
If you opened the script for the button created in this fashion, you would see the script I included above as an example. Of course, once you learned hypertalk, the scripting language, you could just input this script from the keyboard.
Scripts could be added to most HyperCard objects and created actions originating from the object to which the script was attached. There was no single program, but rather a collection of programs associated with the various objects from which a stack was assembled (object-oriented programming). Events associated with one object (say a card) might trigger a handler somewhere else, where it would make more sense. I think of this as an event looking for a home. If an event does not find a handler on the object that generated the event, it falls through the HyperCard hierarchy to the next level. Because so many actions generate an event, every mouse click, opening of a card, opening the stack, etc., many do not find a handler and nothing happens. If you forget to assign a “go to the next card script” to a MouseUp associated with a button, nothing happens.
I have tried to find an old online manual that might provide a complete exposure to HyperTalk without luck. This description of hypertalk from Wikipedia includes sufficient samples of scripts to offer a way to consider just how powerful the language could be.
What I did with HyperCard
I used HyperCard for a variety of things. Here are a couple of examples.
The North Dakota Wild clipart collection
I used my tech skills outside of my role as a college professor. I had an interest in technology applications in science education and was interested in project-based learning. North Dakota Game and Fish had a program called OWLS (outdoor wildlife learning sites) and gave small grants to schools to support the development of small sections of land (think native plant gardens) associated with schools. I became involved in attempting to create activities and develop the sharing of project ideas between schools using technology. One of the projects involved the creation of HyperCard stacks of North Dakota Wildlife. The image used here was from the Bird stack. The idea was to provide students with images that the students could use in their own creations. The entire collection of images is still available from my server. Again, to imagine how this resource might be used, you have to put yourself back in time more than 20 years.
Technology Enhanced Study
Much of my academic research concerned study effectiveness, and I was particularly interested in large lecture, introductory, college courses. The freshman lecture course represents an interesting case. It places the least experienced students in a setting that is the most impersonal and most isolating of their college experience – heavy reading loads, long lectures, and the expectation that you process the inputs without guidance to take high-consequence exams that are likely unlike those you took in high school. My interest was in helping student identify their areas of weakness as they studied and providing an efficient way to address any weaknesses identified. You don’t need to review the entire chapter again. Study the poorly understood sections or ask a colleague for assistance with the topics you don’t understand. Don’t just mindlessly go over the same material again and again.
The course I had in mind was the Introduction to Psychology. I had access to the test item database provided by the textbook company (approximately 200 MC questions for each chapter). The items from the test bank included associated page numbers from the book and what I would call topics (maybe 20-25 for each chapter). Topics were simply identified by number and designated a group of questions addressing the same topic and section of the chapter. These questions provided the basis for the digital study environment I provided to students. Half of the questions for each chapter were used in the study tool, and the other half were reserved for possible use on examinations
The HyperCard study tool took me most of three months during a sabbatical to write. A study experience from the perspective of a student would work like this. Opening the stack on a Mac would offer the student the option of working on one of several chapters (usually 1-4) covered on the next examination. Once selected, Hypercard would display a randomly selected multiple-choice item from that chapter. The student would respond and the computer would then indicate whether the response was correct, and if not, the page numbers in the textbook associated with that question. The idea was that the student could use their textbook to review the page or so associated with that question and possibly take a note in their notebook or highlight the textbook. If the response was incorrect, the stack would then select another item at random from the other items with the same topic number. This would not guarantee a direct test of their understanding of a specific issue they found difficult, but at least would address the same topic. If correct, the system would select another topic at random from the chapter. As the student worked, the stack recorded the date and time of each response and whether the response was correct or incorrect. Aside from general performance, the data allowed consideration of when during the interval between examinations the student used the system (was the student cramming or studying systematically) and the time delay between questions. The delay following incorrect responses was regarded as particularly important because longer median delays were assumed to indicate targeted rereading, notetaking, or some other form of reflection. Students who showed little difference following correct and incorrect responses were using the system in a more passive manner, possibly assuming that responding to the questions alone was beneficial.
The process of preparing the HyperCard study tool was augmented by other Hypercard programs that would take a flat file of questions and create the full study tool by creating the study tool card by card adding a card for each line of text from the flat file representing one question. A procedure built into the Study Tool stack also exported data and added an identifier for the student who had used that specific stack.
Making this system work also required some concessions. Many students were not assumed to have their own Macintosh computer, and for research to be meaningful, access to the tool had to be standardized. At the beginning of each course segment, I took trays containing 200 disks to the reserve desk of the library. The library had a Mac lab always available to students. The disks were assigned an identification number with each student assigned their own disk that had a unique bar code so the disks were checked out in the same manner as other material made available for a specific course. After each exam, I would collect the disks, dump the data for analysis, and prepare the same disks with the questions appropriate to the next examination.
Readers who are familiar with such topics as comprehension monitoring, retrieval practice (testing effect), and distributed versus massed practice should be able to identify the theoretical bases for the tool and how I intended it to be used. What may not surprise educators is the finding that study opportunities are typically designed to address recognized study challenges, yet when released into the wild, students do not use them as intended. The tool was great for investigating actual student study behavior, but the benefits assumed are more difficult to generate than one might think. Capable students not really needing support flocked to the study tool. They used it more frequently and as intended. When answering questions incorrectly, their post-question delays were longer, indicating they were engaged in some effort to act on this awareness. This is not to say that students who were more likely to need help received no benefit, but the difference in who used the system and who used it most appropriately was one of the more challenging findings.
Eventually, I moved on from HyperCard to create online versions of a technology-enabled study environment using a small server, PHP, and MySQL. Students could work from their dorm rooms or any location with Internet access using their own equipment and any browser. My interest in actual student study behavior was more authentic when it did not require a trip to the library. Still, HyperCard was a way to get started and provided a sophisticated, user-friendly experience. For anyone who finds this type of research to be interesting, my published studies based on the study environments can be picked from the list of my publications provided by Google Scholar.
One final Bill Atkinson product
When Bill retired, he began working on one final vision. He lamented the total focus on online image collections and wondered what physical objects would remain to save personal memories. His passion project resulted in PhotoCard was a tool for creating personal postcards. These cards could be sent using the Internet, but Bill really wanted you to pay a small fee to have him print cards you created and he would send them for you.
I corresponded with Bill about PhotoCard and explained I had been a fan since HyperCard. I ended up with this mental image of him personally printing these postcards on his high-quality printer and making the effort to make small adjustments to get things just right. Then, he would head off with a box of these cards to mail them at the post office. This was not about the money as seemed his general approach. This was about making great things that people would use.
Bill Atkinson will always be one of my technology heroes.
In a recent post, I lamented the feeling that what I write becomes part of some anonymous glob that feeds “search AI” [Will anyone read my words?]. I admit that when I do a Google search I first read the AI response and that may provide just what I was looking for. So, ignoring the feeling of personal invisibility that comes with this reality, I began to think about what, in my comments, offers something of value to others. What in following bloggers using RSS did I lose in this transition from following a writer on topics of personal interest did I really lose in being able to apply AI search to address personal interests?
As I considered this question, my mind flashed on an argument I made several years ago in an attempt to justify textbooks and other long-form informative texts. [Why a textbook?]. Ignoring the cost issue and whether or not college students actually study assigned textbook material, I recognized that, mostly to save students money, profs often felt it helpful to create a course syllabus/outline with the reading assignments linked from elements in the outline to free online content. My counter argument was that learning is about each student building a personal model of understanding and there was unique value in a single integrated source as this source was a model of how an experienced learner (the author) had tried to export his or her model of how the many ideas in a course fit together. If I had to argue with myself, I would probably suggest that the job of the professor in creating the outline and presenting on his/her model of the course repeatedly was trying to do a similar thing. I have since decided that, now that I must function as a self-directed learner, I benefit from exposure to a book that provides a more complete and integrated model of some topic. For example, Ahrens’ book – How to take smart notes – offers a better integrated model of the whys and hows of notetaking than the many individual comments I might find searching online.
How do I explain this opinion and why I think it has value? I have decided that what I want is a perspective, and this is what you get from a single source sharing long-form content (perhaps in the form of multiple posts). Elements of information can be combined in multiple ways, and perhaps this is the difference between how we use the concepts of information and knowledge. Knowledge is the way a given individual has organized selected elements of information to provide meaning orusefulness.
Perhaps you can anticipate then how I see the difference between the output of AI search and the more idiosyncratic perspective of a single writer. Both provide information, and on most topics, when there is something specific I want to know, the homogenized summary of many inputs offered by AI may be accurate and possibly superior. However, in building my own personal knowledge of a complex topic, I think it is useful to follow how one knowledgeable individual selects and organizes information. Could a diligent individual create personal understanding from either source? Definitely. I still think there is something unique and useful in following how one individual I trust puts ideas together.
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