Writing to Learn Activities Understood as a Process Trail: No AI

The concept of a process trail is likely novel to most. I first encountered the idea in the context of qualitative research. Qualitative research is a systematic inquiry that aims to understand social or human phenomena in depth, focusing on meanings, experiences, and processes rather than on numerical measurement or statistical relationships. It typically involves collecting and interpreting non‑numerical data, such as interview transcripts, observations, documents, images, or audio. To make findings and claims based on these data sources replicable, the researcher(s) must carefully identify the steps (processes) followed to translate the raw input. The first we did this, and then we did this, and then we did this, etc., represents a process trail. How was it that you turned something from the observations or documents into categories, and something that can be counted? Documentation of the processes involved is necessary so that others can duplicate your procedure or critique a step you took.

A similar documentation of the processes involved in an activity can be identified in other domains. I have written many posts about the processes involved in writing. And it seems that the concept of a process trail can also be applied to the completion of writing tasks. This seems similar to the Writing Process Model advocated by Flower and Hayes. Their model has had a significant impact on writing researchers and the teaching of writing, as it identified the subprocesses involved in writing, enabling researchers to investigate individual differences in these processes and their correlations with writing skill, and encouraging educators to target specific processes for instruction.

The dual benefits of a process trail

I suggest that those involved in the development of writing skills (learning to write) or the use of writing as a way to improve the understanding and retention of content from other areas of study (writing to learn) apply strategies that involve a process trail. A recent and very serious concern in these areas has been students’ substitution of AI for the expected thinking and content construction they are expected to apply. What I am suggesting by proposing that we expect a process trail is that there are benefits to both the development of writing and content study, as well as to the documentation that students have done the work involved.

What processes can be externalized for observation?

Rather than using a more complex model, such as the Writing Process Model, here is my simplified proposal. 

  1. Read the content
  2. Identified what you think are important ideas in the content
  3. Process this collection of ideas to understand and apply

With most writing to learn projects, what you are writing about to demonstrate understanding has to come from somewhere. When the source is a book, document, or website, reading the content would seem obvious. However, with AI available, we know we cannot make this assumption. The second process involves identifying the ideas that you want to eventually include in your written product. Finally, how have you personalized and organized these ideas? 

My thinking about processes has originally been based in my academic interest in note-taking and, more recently, in Personal Knowledge Management (PKM) and Second Brain strategies. These perspectives have nothing to do with cheating, but focus on improving the long-term connections between what we experience (reading, watching, listening) and what we eventually apply in some way. How do we store, understand, retrieve, and eventually apply knowledge?

So, I am suggesting that both accountability and performance can be enhanced using the same process trail techniques. 

Hypothes.is – a simple and FREE tool for process documentation

My own process trail implementation relies on tools I am not presenting here mostly because my goals are more long-term and some of the multiple tools require I purchase subscriptions. Simple and free make more sense in classrooms. There is less investment required to learn the tool itself, and the suggested activities do not require a purchase that would strain already constrained school budgets.

I have used Hypothes.is in my own college classes, but the tasks in my case were focused on social annotation. The idea was that there would be value in comparing highlighting and annotations among students. What did others find important (highlights) and what thoughts did the content generate in other readers (annotations)? Recently, I have been more interested in the personal note-taking capabilities and the potential to allow the teacher to examine individual students’ reactions to what they have read.  

What follows is a quick tutorial in how Hypothes.is might be applied as a PKM tool.

Hypothes.is is a browser extension that allows the annotation of any file type one can open with a browser (text, PDFs, images, web pages). 

The following image displays the window with the Hypothes.is the extension activated? The left-hand column here, which is only shown partially, is the file of interest. The right-hand section displays the open Hypothes.is sidebar. Here you see at least a portion of each of the individual highlights and annotations. The full addition appears if you select one of the individual entries in this column. 

The procedure I want to emphasize is how to export your highlights and notes. I have identified the key “button” in red. 

The button I mentioned opens up the following dropdown. Here you should find the button to export the entries containing highlights and annotations. Also, the link that allows public access to highlights and annotations. A similar link is provided if you set Public to a specific individual or designated group. 

From this menu, you can assign a name to the output file (or leave as is), determine the format for this file (here set to text), and copy this content if you would rather copy and paste instead of outputting a file. 

Finally, the following image shows the text content corresponding to the first highlight/annotation. Note that each of the additions to the content viewed through the browser is assigned a unique identifier. In this case, this is the first addition. 

Use of this information as a process trail

I will work my way through the three processes I identified. First, the highlights and annotations stored demonstrate that the reader has worked her way through the document. Second, the reader has identified information she felt was either relevant to an assignment or important. The existence of the file or viewing the highlights and annotations in context as would be available via the unique link to provide access would demonstrate the effort in executing this process.

Finally, I think it makes sense for the writer to append individual content cut and pasted from the highlights and annotations file as endnotes to the written product. The unique identifier for each endnote could be attached to the section within the writing project where appropriate. The goal in this would be the same as any method for citing a source or sources. Here is the basis for this section of my paper. Here is how I have interpreted and integrated and applied this information. This final activity assures there was a connection between the annotations created and the written product.

Summary

This post explains how to deploy a three-stage process trail using Hypothes.is. This trail engages student in activities that externalize content identified by a reader as important or useful and then connects these elements to specific locations in the product written based on what students have been asked to read and understand or apply. The externalized content also verifies that the reader has executed this process rather than using AI to complete the assignment. 

The intent here is not to discourage appropriate uses of AI. The intent to ensure the practice of key skills when practice of these skills is the goal of the assignment 

Citation

Flower, L., & Hayes, J. R. (1981). A cognitive process theory of writing. College Composition & Communication, 32(4), 365-387.

Hayes, J. R. (2012). Modeling and Remodeling Writing. Written Communication, 29(3), 369-388. [https://doi.org/10.1177/0741088312451260](https://doi.org/10.1177/0741088312451260) 

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Accessing AI Through APIs

I have written several posts about using AI plugins in Obsidian. Part of this process requires you to connect the plugin to an AI service. This is done by interacting with the AI provider (e.g., OpenAI, Anthropic), creating an account, and obtaining a key that the plugin uses to authenticate your use of the AI service and charge you against the credits you have purchased. While Obsidian is free and the AI plugins may or may not be, you must pay for your AI activity. In comparison to the typical $20 a month AI subscription fees, my expenses for use of AI within Obsidian are very small – typically only less than a couple of dollars a month. I have also secured access to a couple of AI services (OpenAI and Anthropic) so I can compare and contrast the content they generate. 

Adding Anthropic AI Capabilities to Obsidian

Here is a quick, complete explanation of the process for obtaining an API key, intended for those who have not yet explored it. 

The site for securing Anthropic API access is console.anthropic.com. The page you will see when you use this link is shown below. You will need to provide a credit card to cover the initial $5 fee. This is not a subscription, but an amount from which the costs you generate are subtracted. This is plenty to get you started and more than I have spent in a given month. You can add to this amount at any time if necessary. The Get API Key button initiates this process. 

If this is first use of an API from Anthropic, you will encounter the following. Change the name of the API if you want; you don’t make use of the name, but a long alphanumeric key that will be provided. 

Your key will look something like the following. I have blurred a portion to protect my account. Copy this key. I keep a copy in a secure place, but this key is what you will add to your Copilot options. 

The Copilot plugin is listed among your community plugins in Obsidian. The Copilot options are accessed using the gear icon. 

API keys should appear near the top of your options. You access using the Set Keys button.

Adding the API to the Copilot Plugin

Copilot supports multiple AI services. The key you copied should be saved into the box associated with Anthropic. 

Back in the Anthropic Console, you can view your spending using the billing option.

Summary

This post explains how to access the Anthropic API to use AI with Obsidian content via the Copilot plugin. I found APIs (both OpenAI and Copilot) to be easy to use with Obsidian and much less expensive. You pay for your level of activity rather than a monthly subscription. Another advantage of Obsidian is its support for exploring multiple AI services. One final comment about Copilot – you must select a model associated with the AI company from which you have paid for service. Copilot lists many different models, but only those for which you have a key will work. 

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AI Plugins for Interaction with your Obsidian Notes

There are several ways in which you can add a plugin to your Obsidian setup to explore your notes with AI. I have considerable experience with two and I have decided to transition from the Smart Connections Obsidian plugin to the Copilot plugin. Both plugins have met my personal needs and I will explain the motivation for my change from one to the other. 

I have been impressed with Smart Connects and have written several accounts of how I have benefited from this tool (example1example2). Still, I am changing. I have experienced similar issues with several products. A helpful product is updated and improved, and as a result, is no longer free or increases substantially in cost. With subscription models, you must decide. Are the additional capabilities useful to you and do other services meet your needs at a lower cost?

Smart Connections allowed me to focus AI prompts on my notes (RAG) and perform other useful functions (e.g., identify related notes). I have nothing against paying for AI and I pay for multiple AI tools or other tools that already contain AI capabilities. It is easy enough for me to export batches of my notes from Obsidian to apply AI tools (e.g., NotebookLM). While Smart Connections was free, you had to grant it access to an OpenAI account to engage in chat. 

The new, more powerful version of the Smart tool is $20 a month. I am certain it continues to be a great tool and it is reasonably priced for those who rely heavily on Obsidian. However, I would suggest that there is greater flexibility with an API AI approach as the same account can be connected to multiple services and I pay based on what I use rather than a flat fee. Again, the approach that makes the most sense depends on individual interests and needs.

I have moved to Obsidian Copilot. It allows me the opportunity to use the same OpenAI account I used with Smart Connections. There is a Pro version, but again, the free level offers the capabilities I want. As with the original version of Smart Connections, I could use my OpenAI account.  

Copilot controls and the content it generates appear in the panel on the right side of Obsidian. The following image shows the controls at the bottom of this column. Red boxes indicate where you set the AI tool you want to apply and the prompt (add context) you intend to focus on. Selecting the “add context” button generates a menu I usually want the prompt to be applied to a folder of notes. 

Copilot allows access to multiple AI APIs. I have an OpenAI account, so during setup I entered a key associated with it. When Copilot asks which model I want to apply, I must select one of the models from OpenAI. 

The following image shows the entire Copilot display, including some content generated by a prompt I applied to my file of Cognitive notes. The prompt includes 

To summarize, my switch from Smart Connections to Copilot has been motivated by the opportunity to use the AI services I already pay for rather than duplicating the subscription cost now required for the latest Smart Connections upgrade. This switch has nothing to do with the capabilities of either system as they appear similar.

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Huxe – AI Driven Daily Updartes

Perhaps you start your day by asking your Echo to provide your daily update. A new AI tool called Huxe now allows you to accomplish a similar goal but in multiple ways that you can personalize. Huxe is a new venture created by some ex-engineers who worked on Google’s NoteBookLM and the service is similar in some ways to the audio overview available through that product. Presently, Huxe is available for iOS and Android. 

Huxe is a free service, but it only make sense that ad or subscription versions must be on the horizon.

There are basically two ways to use Huxe. The most basic functions allows you to select from designated topics and the tool than creates a sort of podcast with two speakers based on recent “news stories” associated with those topics. You can access this feed repeatedly in a day and the feed will be different. The podcast identifies you, remembers when you last connected, and provides basic weather information at the beginning of each session related to your area. One of the most unique feature is that you can intervene while the podcast is playing, ask a question, and the AI tool will pause to respond. The idea is that you can go deeper whenever something is presented that you want to know more about. More about this feature later.

The second basic and less well-promoted capability allows a user to create what amounts to their own personalized “station” based on a prompt rather than the selection of designated topics, request new “episodes” from this station at later dates, and share this station with other users of Huxe. I have read multiple descriptions of Huxe available through web searches and I want to concentrate here on this second approach.  

The following image shows the screen image you encounter once you have set up your Huxe account. The “play button” stands ready to play what I have described as your “daily brief”. To get to the personally created stations and the option to create your own, you use the icon within the red box at the bottom of the image.

This link opens up access to “shows” developed by others with the button allowing you to create your own appearing in the bottom right (see red box in following image). 

At this point, you have the opportunity to enter a prompt to generate the topic you want to follow. My prompt for this example was “How has AI been used to individualize instruction in K12 classrooms.” 

Unlike the “Daily Brief” which changes each time you connect, the “Shows” are created once, but you can then generate additional episodes using your original prompt. 

As I suggested earlier, one of the unique capabilities of Huxe’s AI audio shows is that you can interrupt and ask a question. In the following image, you can see the point at which I interrupted because I was interested in a study being described and wanted a citation so that I could read the original study. Huxe responded with the title of the study and I was able to search and find the study.

Summary

Huxe is an AI tool allowing access to audio programs created as daily briefs or personal shows. The personal shows can be shared. A useful feature allows the listener to interrupt a program and ask a question which the AI tool will then stop to answer. I rely on full text primary sources for what I consider my serious work, but Huxe seems a great way to access a useful morning brief to listen to while I have my first cup of coffee.

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Ask AI About Yourself

A podcast I was listening to suggested that you ask what your commonly used AI tools can tell you about yourself. This suggestion was made in the context of a discussion of AI security, but to me it seemed something interesting to try. From time to time, I search for my name using a search engine just to see what I could find and this always seemed to turn up something unexpected, but it had not occurred to me to try the same thing with AI.

I use a ChatLLM from Abacus.AI, which is a bit less expensive than the $20 per month tools, but it offers the opportunity to apply multiple AI services, which seemed like an interesting way to experiment with this task (see the following image). I used Claude for this example. 

I used this prompt: What do you know about the Mark Grabe living in Minnesota?

I don’t have access to private or comprehensive background files on individuals, but I can share what’s publicly visible online for someone named “Mark Grabe” who appears to be associated with Minnesota and let you infer if that’s the person you mean.

From public sources, there is a:

1. Retired academic / educational technologist

Several profiles and sites point to a retired academic named Mark Grabe, described as an educational psychologist and educational technologist:

  • A personal profile on Glasp lists him as a “Retired academic – educational psychologist, educational technologist” and shows that he is highly active in reading and highlighting articles about education, AI, note‑taking, and related topics, with thousands of highlights and pages saved over several years [Glaspprofile](https://glasp.co/j3h2xdri1p632t4w).
  • He has a Substack newsletter called “Mark’s Substack” described simply as “My personal Substack” [Substack](https://markgrabe.substack.com/). Topics there (from titles and tags) typically relate to education, technology, and broader commentary.
  • He has posted as a retired academic still writing about educational technology and mentions Minnesota (e.g., comments about snow, fall colors, and Twin Cities parks) on social media [Threadsprofile](https://www.threads.com/@markgrabe).

While these pages don’t all explicitly say “Minnesota” in the bio line, the content and posts clearly reference Minnesota weather and locations, strongly suggesting he lives in or around Minnesota.

2. Author of education / ed‑tech books

The same name appears as the author of multiple books on integrating technology into teaching and learning:

  • “Integrating Technology for Meaningful Learning”
  • “Integrating the Internet for Meaningful Learning” (often co‑authored with Cindy Grabe)
  • “Learning With Internet Tools: A Primer”, etc.

These are listed on his author page on Goodreads [Goodreads–MarkGrabe](https://www.goodreads.com/author/show/312712.MarkG​rabe). The topics line up with:

  • Educational psychology
  • Classroom use of technology
  • Internet tools and instructional design

That matches the description of a long‑time education/ed‑tech professor who later retired but stayed active writing online.

3. Likely background (inferred, not private data)

Based on the combination of sources above, the public picture of “the” Mark Grabe tied to Minnesota is:

  • Retired academic, likely a former professor of educational psychology/educational technology.
  • Has written multiple textbooks and practitioner books for teachers on integrating technology and the internet into instruction.
  • Is still active blogging and writing online about:
    • Educational technology
    • AI and learning
    • Note‑taking, reading, and study tools
    • Broader social/technology themes

I don’t have access to protected records (e.g., address, employer HR info, phone numbers, or anything similar), and I can’t confirm that every online “Mark Grabe” is the same person, only that these public profiles look very likely to refer to the same academic/author who mentions Minnesota.


If you’re trying to figure out whether this is a specific Mark Grabe you know (e.g., a relative, professor, or colleague), tell me:

  • In what context you know him (university, school district, family, etc.), or
  • Any known details (field, approximate age, institution),

and I can help you cross‑reference public information more precisely while staying within privacy boundaries.

Reaction

This information is accurate and does not contain anything I would call private information. The links are accurate and take you to some, but not all of my most active online accounts. For example, I have been a blogger since 2002 and while this is recognized, there is no link. The same is the case with my Mastodon accounts. Other AI tools I tried did identify these sources.

What about images?

It then occurred to me that it might be possible to generate an image to accompany something I might write about this content. I switched to Nano Banana.

Prompt: What can you show me about Mark Grabe.

The AI responded with “I can show you a portrait of Mark Grabe”.

After viewing the image, I asked Nano Banana to place a copy of the book “Integrating Technology for Meaningful Learning” on the desk resulting in the following image.

I don’t think those who know me would recognize this individual as me, but many of the attributes – hair line, glasses, beard are perfect. The AI must have found examples of my appearance to come this close.

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Taking Notes – How?

In a previous post, I mentioned TwinMind as an interesting tool that transcribes an audio input and then uses AI to summarize. While the technology is impressive and seems to work very well, my comments were mostly focused on what this tool allows and what it may prevent.

I certainly encourage you to take a look at TwinMind. The tool is available as an app and as a Chrome extension, with the Chrome extension being more capable. There is a free plan and a $10 a month pro version with the current free plan being ideally suited to student use. TwinMind was created by some of the developers of NotebookLM who decided to create their own company (nice description of origins and capabilities). It has several nice features for those concerned about privacy and operates on your device. The transcription and summarization capabilities do not require that any data be uploaded for assistance from a corporate AI service. I can’t say I use this tool personally, but I have been exploring its capabilities by opening my iPad and launching the app while I participate on my desktop in my weekly two-hour book club. The transcript, complete with “you knows” and (uhs) as well as the AI summary of both our small talk and book comments, was accurate (see sample summary below).

Concerns

Here is my objection. This tool would be great for applications such as having a complete transcript of a meeting (with summary) and perhaps sharing class notes with students unable to attend (perhaps the prof would generate and post to the course management system). However, there is value in taking your own notes that is avoided by relying on AI notes. 

This study of the value of taking your own notes goes back decades and I address this research which I first studied in the 1960s, in multiple posts (here is just one). Taking notes requires thinking – selecting, paraphrasing, writing – and this thinking contributes to understanding and retention. You can review notes self generated or AI generated, but to this point the benefits of one approach versus the other has yet to be investigated. The closest comparison I can think of might be studies that provided what were called expert or instructor notes (e.g., Kiewra, 1985) and produced results superior to what students produced when relying only on their own notes (although using both personal and instructor notes produced the best results). Compounding the complexity of this topic is the issue of short versus long term benefit. Expert or AI notes may provide immediate benefit, but limit the development of personal skills important to functioning outside of a classroom environment. To my knowledge the benefits of AI have yet to receive much in the way of attention from researchers using sound methodologies. Asking learners what they think of the experience is not the type of work I trust.

Taking digital notes

How learners take notes (on paper or using a digital device) has its own controversy. I don’t intend to get into this debate in this post, but I back digital because I believe the opportunity to search, share, and reprocess offers advantages over time (one post). 

I prefer a specific tool that allows simultaneous recording of audio from a presentation and links it to notes taken by the learner. This requires a digital approach. By connected, I mean the text in the notes is linked to the audio so that after saving the combination, selecting any given notes plays that audio at the point that the learner began taking that note. Because of this connection, the learner can review the audio later if a note does not make sense. When a learner is having difficulty interpreting a specific part of a presentation, I tell them to simply record something like ???? in their notes so they know what to listen to later when they have more time to focus on the problematic content. 

I have made this recommendation for some years and see that the apps I originally recommended still work on my iPad, but some that were free now require a subscription. Interestingly in reference to my earlier comments about AI, many of the options I recommended that now require a subscription include AI, allowing summarization and interaction as added features.  

Services I have used to record audio and take notes:

Goodnotes

Soundnotes

Summary

Like many application of AI in educational settings, it is possible to identify both opportunities and concerns. Notions such as second brain (storage of notes, annotations, etc.) recognizes the limitations of human cognition and the opportunities to augment cognition in ways that improve performance. 

So many concerns for AI activity by learners fall into a common theme. Learners may use AI to replace an activity intended to develop a specific learner skill. By completing the task without personally exercising the intended skill, learners avoid the purpose of the task – learning a skill. This is obvious when used to avoid a writing task, but applies to a broader set of educational assignments. Taking notes is not necessarily a skill educators focus on developing, but researchers have studied how learners benefit in detail and in this case the activity itself is not the focus, but rather the benefits on understanding and retention that are improved because of the process. 

I am not claiming reviewing AI summaries has no value, but am concerned that avoiding the process of taking the notes may be detrimental. As I have already stated, researchers have yet to investigate this topic. Note taking research isolates two major components – note making and note reviewing. Obviously, AI notes still allow for note review and the research on note taking indicates it is the less impactful of the two interrelated activities. 

If I could presently create the ideal tool, I probably would add the opportunity to take notes in real time to something like TwinMind. The learner would then have personal notes linked to some type of audio or text transcript and the AI summary as a second study opportunity.

Reference

Kiewra, K. A. (1985). Providing the Instructor’s Notes: An Effective Addition to Student Notetaking. Educational Psychologist, 20(1), 33–39. https://doi.org/10.1207/s15326985ep2001_5

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