I haven’t posted in a while and it will be a while until I post again. I did not want people to think I had abandoned my blog. We are on an expidition cruise ship exploring Patagonia.
I have a separate blog for our travels and if you are interested I would invite you to take a look. My wife and I are heavy tech users no matter the activities we are engaged in and you may find things you will enjoy.
The following is the Pios XI glacier in Chile and the video shows the glacier calving.
We know that tutoring is one of the most successful educational interventions with meta-analyses demonstrating the advantage to be between .3 and 2.3 standard deviations. In some ways, the explanation of this advantage seems obvious as it provides personal attention that cannot be matched in a classroom. The challenges in applying tutoring more generally are the cost and availability of personnel. One of my immediate interests in the AI tools that are now available is in exploring how students might make use of these tools as a tutor. This is different from the long-term interest of others in intelligent tutoring systems designed to personalize learning. The advantage of the new AI tools is that these tools are not designed to support specific lessons and can be applied as needed. I assume AI large language chatbots and intelligent tutoring will eventually merge, but I am interested in what students and educators can explore now?
My initial proposal for the new AI tools was to take what I knew about effective study behavior and know about the capabilities of AI chatbots and suggest some specific things a student might do with AI tools to make studying more productive and efficient. Some of my ideas were demonstrated in an earlier post. I would still suggest interested students try some of these suggestions. However, I wondered if an effort to understand what good tutors do could offer some additional suggestions to improve efficiency and move beyond what I had suggested based on what is known about effective study strategies. Tutors seem to function differently from study buddies. I assumed there must be research literature based on studies of effective tutors and what it is that these individuals do that less effective tutors do not. Perhaps I could identify some specifics a learner could coax from an AI chatbot.
My exploration turned out to be another example of finding that what seems likely is not always the case. There have been many studies of tutor competence (see Chi et al, 2001) and these studies have not revealed simple recommendations for success. Factors such as tutor training or age differences between tutor and learner do not seem to offer much as whatever is offered as advice to tutors and what might be assumed to be gained from experience do not seem to matter a great deal.
Chi and colleagues proposed that efforts to examine what might constitute skilled tutoring begin with a model of tutoring interactions they call a tutoring frame. The steps in a tutoring session were intended to isolate different actions that might make a difference depending on the proficiency with which the actions are implemented.
Steps in the tutoring frame:
(1) Tutor asks an initiating question
(2) Learner provides a preliminary answer
(3) Tutor gives confirmatory or negative feedback on whether the answer is correct or not
(4) Tutor scaffolds to improve or elaborate the learner’s answer in a successive series of exchanges (taking 5–10 turns)
(5) Tutor gauges the learner’s understanding of the answer
One way to look at this frame is to compare what is different that a tutor provides from what happens in a regular classroom. While steps 1-3 occur in regular classrooms, tutors would typically apply these steps with much greater frequency. There are approaches classroom teachers could apply to provide these experiences more frequently and effectively (e.g., ask questions and pause before calling on a student, make use of student response systems allowing all students to respond), but whether or not classroom teachers bother is a different issue from whether effective tutors differ from less effective tutors in making use of questions. The greatest interest for researchers seems to be in step 4. What variability exists during this step and are there significant differences in the impact identifiable categories of such actions have that impact learning?
Step 4 involves a back-and-forth between the learner and tutor that goes beyond the tutor declaring the initial response from the learner as correct or incorrect. Both teacher and learner might take the lead during this step. When the tutor controls what unfolds, the sequence that occurs might be described as scaffolded or guided. The tutor might break the task into smaller parts, complete some of the parts for the student (demonstrate), direct the student to attempt a related task, remind the student of something they might not have considered, etc. After any of these actions, the student could respond in some way.
A common research approach might evaluate student understanding before tutoring, identify strategy frequencies and sequence patterns during a tutoring session, evaluate student understanding after tutoring, and see if relationships can be identified between the strategy variables and the amount learned.
As I looked at the research of this type, I happened across a study that applied new AI not to implement tutoring, but to search for patterns within tutor/learner interaction (Lin et al., 2022). The researchers first trained an AI model by feeding examples of different categories identified within tutoring sessions and then attempted to see what could be discovered about the relationship of categories within new sessions. While potentially a useful methodology, the approach was not adequate to account for differences in student achievement. A one-sentence summary from that study follows;
More importantly, we demonstrated that the actions taken by students and tutors during a tutorial process could not adequately predict student performance and should be considered together with other relevant factors (e.g., the informativeness of the utterances)
Chi and colleagues (2001)
Chi and colleagues offer an interesting observation they sought to investigate. They proposed that researchers might be assuming that the success of tutoring is somehow based on differences in the actions of the tutors and look for explanations in narratives based on this assumption. This would make some sense if the intent was to train or select tutors.
However, they propose that other perspectives should be examined and suggest the effectiveness of tutoring experiences is largely determined by some combination of the following:
In differentiating these categories, the researchers proposed that in the learner-centered and interactive labels, the tutor will have enabled an effective learning environment to the extent that the learner asks questions, summarizes, explains, and answers questions (learner-centered) or interactively as the learner is encouraged to interact by speculating, exploring, continuing to generate ideas (interactive).
These researchers attempted to test this three-component model in two experiments. In the first, the verbalizations of tutoring sessions were coded for these three categories and related to learning gains. In the second experiment, the researchers asked tutors to minimize tutor-centered activities (giving explanations, providing feedback, adding additional information) and instead to invite more dialog – what is going on here, can you explain this in your own words, do you have any other ideas, can you connect this with anything else you read, etc. The idea was to compare learning gains with tutoring sessions from the first study in which the tutor took a more direct role in instruction.
In the first experiment, the researchers found evidence for the impact of all three categories of tutor session benefits, but codes for learner-centered and interactive had benefits for performance outcomes relying on deeper learning. The second experiment found equal or greater benefits for learner-centered and interactive events when tutor-focused events were minimized.
The researchers argued that tutoring research that focuses on what tutors do may have yet to find much regarding what tutors should or not do may be disappointing because the focus should be on what learners do during tutoring sessions. Again, tutoring is portrayed as a follow-up to classroom experiences so the effectiveness of experiences during tutoring sessions should be interpreted given what else is needed in this situation.
A couple of related comments. Other studies have reached similar conclusions. For example, Lepper and Woolverton (2002) concluded that tutors are most successful when they “draw as much as possible from the students” rather than focus on explaining. The advocacy of these researchers for a “Socratic approach” is very similar to what Chi labeled as interactive.
One of my earlier posts on generative learning offered examples of generative activities and proposed a hierarchy of effectiveness among these activities. At the top of this hierarchy were activities involving interaction.
Using an AI chatbot as a tutor:
After my effort to read a small portion of the research on effective tutors, I am more enthusiastic about the application of readily available AI tools to the content to be learned. My post which I presented more as a way to study with such tools, could also be argued as a way for a learner to take greater control of a learner/AItutor session. In the examples I provided, I showed how the AI agent could be asked to summarize, explain at a different level, and quiz the learner over the content a learner was studying. Are such inputs possibly more effective when a learner asks for them? There is a danger that a learner does not recognize what topics require attention, but an AI agent can be asked questions with or without designating a focus. In addition, the learner can explain a concept and ask whether his/her understanding was accurate. AI chats focused on designated content offer students a responsive rather than a controlling tutor. Whether or not AI tutors are a reasonable use of learner time, studies such as Chi, et al. and Lepper et al. suggest that more explanations may not be what students need most. Learners need opportunities that encourage their thinking.
References:
Chi, M. T., Siler, S. A., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001). Learning from human tutoring. Cognitive science, 25(4), 471-533.
Fiorella, L., & Mayer, R. (2016). Eight Ways to Promote Generative Learning. Educational Psychology Review, 28(4), 717-741.
Lepper, M. R., & Woolverton, M. (2002). The wisdom of practice: Lessons learned from the study of highly effective tutors. In Improving academic achievement (pp. 135-158). Academic Press.
Lin, J., Singh, S., Sha, L., Tan, W., Lang, D., Gaševi?, D., & Chen, G. (2022). Is it a good move? Mining effective tutoring strategies from human–to–human tutorial dialogues. Future Generation Computer Systems, 127, 194-207.
First and second brain are terms used by those proposing strategies for learning, remembering, and applying that take advantage of external storage tools and techniques. In this descriptive system, your first brain consists of the biological organ in your body and the cognitive activities you can apply within this biological system. This combination of organ and cognitive activity accomplishes what we typically describe as remembering, thinking, and creativity. The concept of a second brain is a way of referencing external devices and activities generating some type of external representations that are intended to augment first brain functions. I purposively have made the generation of an external record a component in my description of a second brain recognizing that external activities that many might describe as study techniques exist that do not involve the generation of an external record. For example, responding to questions is proven as a way to improve retrieval and if done verbally does not involve the creation of anything permanent. Advocates of the second brain concept do emphasize the generation of a record of experiences.
I tend to equate references to the second brain with some system for taking notes. This is a simplification, but a way to quickly provide a reference for those not steeped in this topic. As I have tried to argue when referring to first brain topics, it is more than just the record that is important. It is also the variety of tactics in storage and retrieval and deciding when a given tactic should be applied that can be important.
Finally, first and second-brain proposals can and should include consideration of the interaction between these two systems. As potential users of both brains, we have some control of each system and access to a second brain implementation could change the way we make optimal use of our first brain in comparison to what might be optimal use if we had to rely on the first brain system only.
We all or at least most of us took notes in our high school and college classes. Taking this background as a starting point, you should have a context within which to think about this topic. Now add some additional expectations. What if the goal was not to use a second brain application to prepare for next week’s exam or the paper you had to write in a couple of weeks? What if the goal was to augment your first brain function over several years in order to address life tasks you might not be even able to describe at this time? Even this later question might be applied to formal education because very few were thinking in this way when studying for that next exam or preparing for that next paper. Most of us probably cannot even find or did not keep the second brain artifacts we created while engaged in our formal education.
Now this was a long introduction I hope was valuable in and of itself to some. Many of my previous posts concerned second-brain topics such as note-taking and second-brain technology tools. Please take a look if my introductory comments piqued your interest. I spent the time to generate this overview in order to provide a context for the content that now follows.
The application of tags in first and second brains
One of the interesting characteristics of the work of cognitive scientists and second-brain developers is how there seems to be a reciprocal impact of ideas that originate in one field on the other. While I am at it, I can see a similar reciprocity in the ideas of cognitive and AI researchers. To be clear, cognitive researchers rely on hypothetical concepts to represent yet-to-be-discovered biological functions. This is my way of thinking about the challenges of neuroscientists and cognitive researchers. Obviously, mental activity must be a function of biology, but our mastery of this field is far from being useful in addressing most human learning challenges. A hypothetical construct is a proposed mechanism for how something works that has yet to be explainable via a physical equivalent. So cognitive constructs such as short-term memory, metacognition, associative networks, links, etc. seem to be useful in understanding and even proposing effective learning strategies and this is possible without having to reference or consider the underlying biological mechanisms that must be involved. For example, we can measure short-term memory and we can propose ways to improve the effectiveness of short term without reference to actual biological structure or process. My focus in this post is on the role played by tags in both first and second brains.
Shank and his focus on stories
I have been rereading Roger Shank’s Tell Me a Story. I first read the book probably 30 years ago. How I now relate to this book on human cognition and AI has changed a great deal because of my recent exposure to personal knowledge management (PKM). As the full book title indicates, Tell me a story: Narrative and intelligence is about stories serving a far different role than entertainment. Shank presents stories as playing a central role in how we think, learn, and communicate. Shank goes as far as suggesting that telling a useful story at the right time is a great sign of intelligence. He proposes that an expert is an individual who has a great number of stories relevant to a given area and has these stories indexed so that he/she can tell a useful story at the right time. He recommends that we recognize that our conversations with others often focus on stories with one individual telling a story and then the other person telling a related story to indicate he or she understands and to offer some additional element of information.
This proposal fits with my own way of thinking about human memory. In cognitive psychology, one way to describe the contents of long-term memory is to propose that meaning is retained in units of information connected by links. This web is different in each individual as differences exist in what units are stored and in how these units are linked. Explaining in detail what cognitive researchers mean by units of information can get pretty dense, but for the present purpose perhaps concepts and facts is close enough. This web is called semantic memory. In addition to the elements of meaning are episodic memories. These episodes are often described as the way we remember events and I always thought we could think of these events as stories. What I heard in class today is an episode with a progression of information. It might also be described as a story.
Some key ideas from Shank’s book:
Intelligence is an abstraction; different experts explain it and sometimes propose how it can be assessed differently. Shank argued that an individual’s use of stories could reveal a lot about how intelligent that person is. Two aspects were informative. The first is having stories worth telling and the second is being aware of which story would be effective when conveyed to a specific individual in a specific situation.
Reminding is using an input in a way that involves the prediction and generalization allowing the retrieval of relevant stored stories. Intelligence is reflected in that capacity to translate new experiences, perhaps stories told by someone else, into effective retrieval cues.
In the process of understanding, we compare experiences with what we have already experienced. This process of reminding is the basis for gaining new insights from differences between similar stories.
Thinking involves indexing. Shank proposed that a useful memory combines specific experiences and indices or labels. The more indices the better. Shank spent a great deal of effort identifying what indices people used proposing that locations, attitudes, challenges, decisions, conclusions, and other labels are used as indices.
We are not necessarily aware of the process of labeling. The application of labels can be assumed based on what individuals recall in response to an input (story/experience). A story that is recalled in response to a story told must share at least one common index.
Understanding is equivalent to the extraction of indices from an input that match the indices associated with stored stories. We learn when the identification of a match between new and old allows further analysis of differences in the stories.
Tags, links, and indices
Careful attention to Shank’s explanation of the value and role of stories is recognition that it is not the stories alone that are important, but the combination of indices and stories. The combination is important, but in addition, it is personalized through the imposition of an indexing approach that creates this productive system. Perhaps thinking about experiences searching for understanding translated as indexing.
So Shank’s importance relies on the combination of indices and stories. Cognitive researchers describe long-term memory in terms of units of information (semantic memory) and episodes linked to facilitate retrieval and understanding.
Those developing and implementing second-brain systems offer tools (e.g., Obsidian, Mem.ai, LoqSeq) offer a digital system for storing notes, for attaching tags to notes, and for linking notes to each other. Notes are not stored as extended documents as might be the case for the handwritten notes taken during a lecture, but as individual ideas or concepts and labeled with multiple tags and one or many connections to other notes. Users are encouraged to review their notes and their system of connections periodically and to add more connections that occur to them. The goal is value over the long term.
Idea for practice
Aside from reflecting on the commonalities across these systems and how the functioning of one system might encourage how another system might be understood, here is one observation that occurred to me while completing this analysis. I don’t think the second brain advocates take advantage of the power Shank sees in how our use of the first brain relies on stories. Perhaps there is some attention to identifying and connecting examples, but I see little attention paid to the storage, tagging, and linking of stories. I told stories as examples when I lectured. In the time I have spent developing my second brain, I don’t remember ever adding and linking one of the stories I tell and I have not documented in my notes the stories I have read as examples in the sources I might translate into notes. If Shank’s argument for the value of stories is valid, not including stories in a second brain would be an opportunity missed.
Reference
Shank, R. C. (1990). Tell me a story: Narrative and intelligence. _Evanston, IL: Northwestern University Process_.
I have spent considerable time in the past year reviewing the literature on personal note-taking and trying to identify what is substance and what is hype. My interest is based on personal experience as a 40-year academic attempting to track my reading of many books and journal articles recognizing that in my discipline anchoring arguments and methods to previous reports is essential in research and teaching, present initiatives that seem to be triggered by a couple of influential books (Ahrens and Forte), involvement with a reading group interested in knowledge management (Making History), and my largely unsuccessful search for research associated with PKM systems and applications.
I have a reasonable background for analyzing and commenting in this area. I can argue that I have deep knowledge of student note-taking which is certainly a reasonable background for expanding into related areas. I have read the literature on student note-taking for decades and have been actively involved in research and writing projects on related topics. While this background offers an understanding of the cognitive processes involved in successful note generation and note study processes, using this background to write about personal knowledge management (PKM) and the successful use of digital tools designed to implement PKM strategies has revealed limitations in generalizing from classroom note-taking to what I have come to describe as adult note-taking. All I mean by this distinction is that taking notes when not in the role of a student is different in some important ways.
My general summary of differences might be captured in the following statement based on the classic distinction used to identify and study the benefits of taking notes. Note-taking is typically described as having two stages – a recording stage and a study stage. Benefits are typically argued to result from generative activities and retrieval effectiveness. With lecture and content-related notes taken by students, the recording stage is mostly about getting as much down as possible (storage) in order to have an accurate and complete record available (retrieval) for processes to improve retention and understanding. Thinking is more of a generative process than is retention. Outside of formal educational settings, adults engage in note-taking with somewhat different goals. Within the model I have described, the generative component increases in value and is more involved in both the encoding and the review stages of note activity. I am not suggesting this suggestion is ideal, but I think it is accurate. Educators likely prefer that their students place greater emphasis on personal understanding which is what comes with greater generative processing, but only part of such underperformance can be blamed on students. I believe there is a maxim suggesting that “what is tested is what is learned”. Some additional thoughts may offer additional insights
I have identified unique distinctions between the knowledge base associated with student note use and some hypothetical knowledge base that would be ideal for my more present interests. What I mean by this is that properties associated with nonclassroom note-taking and note use lack a research base. There are certainly books and many YouTube or Substack proposals for strategies to improve knowledge-based productivity, but there is very little that evaluates these strategies – lots of hype, many products, and little data.
Understanding the basics of notetaking and note use is of some value, but distinctions that can be identified with present externalized personal knowledge management systems and some of the related goals for use point to some obvious voids in the research concerning the effectiveness of strategies of application. Here are some differences I believe are important. First, student notetaking must deal with the reality that what is to be known (or at least tested) is defined by someone else. Goals of the processes involved in taking notes must be subservient to this reality and this prioritizes certain unique goals. What are the priorities of the information presenter? What are my tasks as a learner following from my understanding of such goals?
One reality of student note-taking is that generating a useful record for later review depends on an imperfect understanding of what must be retained. In recognition of this challenge and understanding the limits of cognition especially in a real-time lecture setting, getting as much down on paper or screen as possible is a reasonable response. More thoughtful and time-demanding prioritization and even the determination of the accuracy of what was recorded may have to be put off until the study/review stage. Some students may recognize the need to take the subsequent step of comparing notes with others to fill in gaps or correct misunderstandings. Some may not realize that this remediation would be helpful or not bother with the extra effort required.
A second distinction concerns the time frame involved and the implications this time frame may have for initial processing. A student’s perceived time frame for priority payoffs (test scores, superior paper construction) tends to be relatively short. A student might vaguely understand that knowledge acquired from his or her high school or college classes is useful throughout life, but he or she is likely to be focused on the next graded activity. The artifacts created to facilitate study or project activities are typically discarded once a course has been completed. As an adult, my time perspective is more undefined and part of my motivation is to create a system of external storage intended to be valuable over a much longer time frame and that recognizes I will likely face limited recall of the context within which the stored information was acquired. As a consequence, the record I choose to create must include more of the context making delayed understanding requires.
There are likely many other significant differences, but my point here is simply to argue that the vast literature associated with student note-taking leaves significant gaps that would guide “adult” self-guided note-taking and note use. We seem to be at a stage in which the statement that phrase “more or at least some research is required” should be included in more commentary on PKM. I use this phrase as commonly included in research to indicate that researchers/authors understand what they have studied has important limitations when it comes to established validity.
Here is an example of a research question I would like answered. It relates to the strategy of taking Smart Notes a strategy proposed by Ahrens. I think of a smart note in my own way as writing earlier in the process of content creation. So, instead of reading, highlighting, and copying key ideas into a notebook and then waiting months or years before trying to make sense of the notebook entries, smart notes are written based on personal understanding to generate a note that contains enough context that it would stand alone as a representation of a useful idea after an extended period of time. It should be useful to self or to someone else with a reasonable background. Ahrens describes several types of notes including fleeting notes and smart notes. The difference in these two representations is the personalization of completeness of the idea represented as a smart note. A fleeting note might meet the demands of quick immediate storage and the smart note is more carefully constructed to be meaningful.
I think of fleeting notes as serving a similar purpose as highlighting – selection without personalization.
So, this idea seems reasonable and I can create such notes, store them within a knowledge management system such as Obsidian, tag and cross-link them, and review them periodically waiting for the day I might use the idea in something I write. Obsidian also automatically stores the highlights I have taken reading Kindle books or journal article pdfs (transferred to Obsidian using Readwise). Here is a question related to these two options – smart notes or highlights. Using search in Obsidian, I can locate either Smart Notes or highlights related to search terms I provide. The highlights are typically not interconnected, but I can use the links automatically stored with each highlight back to the place in the original document where I highlighted the original content. While smart notes sound useful are they really worth the extra time? Should I just spend my time searching for highlights that are related to what I want to write about and then quickly review the original documents should I need to refresh my understanding when a highlight seems to identify a useful idea I needed to refresh in my mind.
There are many similar questions I can generate related to the storage and thinking systems that have been proposed by PKM advocates. Do these strategies actually deliver improved content production?
Important research questions about any type of long-term benefits come with several challenges. Again, I cannot presently provide extensive analysis, but here are a couple of examples. The classic experimental/control group methodology is very difficult to implement. The development of second brain methods (external collections of notes implementing the various methods for tagging, linking, secondary reworking and other strategies) are developed and applied over years rather than weeks or months. Holding a research project together over such a period of time is difficult and costly. I have been unable to find such examples.
The time frame issue is compounded by the reality of technology. The pace of questions raised by ever-changing methods seems nearly incompatible with straightforward experimental/control methods. The tools and questions of interest change faster than the methods of answering these questions can provide results.
I keep looking for research I can use to shape my thinking and writing. My frustration was one of the motives for this post. I had hopes when I encountered a notice announcing a new book – Digital writing technologies in higher education. This was one of those resources including multiple authors who proposed individual chapters. In the editors’ forward, the expectations for each chapter are provided and each chapter is to include a section on the related research. There was not much there in the chapters I have read to this point, but the “more research is needed” statement appeared repeatedly. By the way, the book I mentioned allows the free download of chapters as pdfs and anyone interested in this general field should take a look.
More research is needed. I will summarize relevant studies when they appear.
Citations mentioned:
Ahrens, S. (2017). How to Take Smart Notes: One Simple Technique to Boost Writing, Learning and Thinking–for Students, Academics and Nonfiction Book Writers. Sönke Ahrens.
Forte, T. (2022). Building a Second Brain: A Proven Method to Organize Your Digital Life and Unlock Your Creative Potential. Simon and Schuster.
Kruse, O., Rapp, C., Anson, C. M., Benetos, K., Cotos, E., Devitt, A., & Shibani, A. (Eds.). (2023). Digital Writing Technologies in Higher Education: Theory, Research, and Practice. Springer Nature.
I have had at least one blog since 2002. Since that time, I have also had control of the server on which my blog and other content I created was stored. At the beginning of this period of time, I worked at a university and was able to run a server through the university network. This translates as I had a dedicated IP for my site and once someone found my content and bookmarked the site, the site would always be available at that address. I can’t remember the exact address, but it did indicate my server was identified as a part of the more general university network.
When I began to generate free content I intended to supplement the textbook my wife and I had written through what was originally Houghton-Mifflin, I decided it might appear that even though the content I was offering was free to any viewer, it might seem I was using university resources to benefit me financially and so I began renting server space. I have continued to host my content through Bluehost since that time. This company provides services at multiple levels. My blogs make use of WordPress, but I have a general account because I use Bluehost for content other than blogs.
I spend about $200 a year for the server space and the cost of two domains (learningaloud and curmudgeonspeaks). I include this financial information because part of the issue of how you provide online content has a financial component. Among the financial issues are whether you want to make money and whether you want to minimize personal costs. None of the content on my server is behind a paywall and there are Google ads on some of my content. The income from ad clickthroughs is less than $25 a year. So, I must recognize that my site is a hobby and the inclusion of ads is pretty much a matter of personal curiosity. I follow the analytics my site generates as part of this hobby. The activity level the site generates is sufficient to maintain my interest, but has declined in this last decade. I attribute this decline to moving from having textbooks sold through a textbook company to self-publishing via Amazon. My motives for this transition have been documented in my blog posts and were related to my interest in investigating a different model for textbooks that combined a smaller and less expensive book with online resources.
I am writing this post partly as an extension of a previous post that considered cross-posting my blog content to Medium and Substack. One way to look at the purpose of this post might be to explore the question of why with the availability of services such as Medium and Substack (and other outlets) would anyone want to continue to pay to host personal content. I am not alone in asking this question. My take is related to, but not equivalent to the concept of COPE (compose once publish everywhere), but focuses on different values and factors.
I find that a core belief I have about having a location where you store and host your own content has considerable overlap with my beliefs concerning the value of books. I believe book authors and content providers bring a perspective and context to their creative work that is not maintained in pieces of content experienced in isolation. You might argue that this is fine because as a consumer you will build your own understanding based on the elements of information you pick up from multiple authors. I agree you might and probably should do this. However, models of understanding are transferable and can be used to build on and contrast with personal efforts to develop understanding.
Yes, this sounds pretty abstract and vague. Think of what I describe as a model as a way of understanding – how you see things working and what causes what to happen. Ways of understanding (models) can be general and specific and they can be complete or incomplete. Sometimes we have flawed ways of understanding that seem to work in some situations, but we may at some point find our way of understanding does not work in others. We can be convinced we have things figured out when this is really not the case and only when we try our models in actual situations or compare them to the models of others with different and perhaps more experience that we see a bigger picture.
I have generated thousands of posts over the 20+ years I have been involved in blogging. I am certain some of my posts are naive and wrong and some may be inconsistent. Like a book, the collection does emphasize a limited set of ideas and provides connections among these ideas. These posts are tagged and organized so any interested party can explore related ideas to explore the broader context of my ideas. You just don’t get this with the selection of posts I add to Substack or Medium.
This post is intended to be the final contribution in my series of posts describing generative activities and classroom applications. My previous contributions identified two hierarchical systems, SOI (selective, organizing, integrative) and ICAP (interactive, constructive, active, passive), proposing more and less powerful activities for influencing learning effectiveness. Both systems propose collaborative activities to be potentially most effective. Several of my posts have concerned how taking notes can improve achievement so I decided to conclude this series with a focus on collaborative notetaking.
Before I address the topic of collaboration, it may be helpful to provide a more general background on how educational psychologists and researchers such as me describe the process of taking notes. First, we differentiate the overall process into a storage and a retrieval phase. I assume this is obvious. A learner takes notes at one time to improve performance of some type at a later time. Second, we identify what might be accomplished during each stage. What is recorded during the storage phase determines what is available during the retrieval (study) phase. Learners may differ in how completely and how effectively they record key ideas so both completeness and quality of what is recorded could be important. The idea of a generative activity also proposes that the process of taking notes (whether available for review or not) might be helpful because of the cognitive activities that are involved. By extension, an instructor could prepare a quality set of notes and give them to students so they don’t have to take notes themselves. It matters if having personally taken notes is key to effectiveness. So attempts to determine if taking notes yourself has some unique value are useful.
Again, the importance of a retrieval and a study phase probably seems obvious. But again, there are important wrinkles that could be important. Does it matter if you review your own notes in comparison to expert notes? When in the time period between taking notes and the attempt to use knowledge should notes be reviewed? How many times and in what ways should this external record be used for review?
How might collaboration impact these processes? Some of the ways in which collaboration might modify notetaking are generative and some not. Collaboration could mean that others record notes you miss or record some things more accurately than you and access to their notes would allow you to achieve a more complete and a more accurate representation of the content. Maybe you just miss some things or misunderstand some things. When you have help, maybe you can record less and think more during the reception phase reducing the working memory demands of taking notes. These factors could be important if you don’t “slack off” knowing that you have some way to augment your own optimal efforts. These advantages are not generative. Collaboration could also involve actual interaction. Learners could discuss their understanding in reviewing their composite notes adding additional processing to what individuals might do on their own. This is what generative notetaking really proposes.
There are lots of other variations in notetaking that might be important and could be beneficial or harmful. There are postprocessing variations other than talking through notes with other students. Some systems (e.g., Cornell notes) propose a system of postprocessing?—?a secondary process of commenting on notes. Other ways of working with notes taken (Smart notes) also can be applied as part of the retrieval/study stage.
Another interesting proposal challenges the way we tend to think about taking in information during a live lecture. With asynchronous presentations that were increasingly common during the pandemic and also a way to think about the advantages of a flipped classroom, content is experienced in a recorded format. A learner or a small group of learners can control the pace of the presentation by simply stopping the playback of a video or even repeating segments of a recording reducing the working memory and note creation challenges of keeping up. With recorded content, a small group of students can even discuss as they record notes making the process more generative.
I have several motives in presenting notetaking in this way. First, I wanted those who think the processes are simple and fixed to think again. Second, I wanted to set you up for arguing that while determining if collaboration helps or not is pretty straightforward, understanding why what is observed in a dependent variable is not obvious. For example, if collaboration improves achievement, does this happen because the combination of notes is more complete and accurate or because the process of students working together led to some unique processing that would not have occurred without the interaction. Some have even observed that collaboration led to better quiz performance, but poorer implementation of the skills being taught (Fanguy, et al. 2021). These authors argued that the processing required of individual learners varied as a function of whether they had to depend entirely on their own notes. Deep understanding required for application might suffer when responsibility was shared.
I have concluded based on a review of most of the studies on collaborative notetaking that teasing apart the potential benefits does not presently allow clear conclusions. The core problem is that it is difficult to document how much actual interaction occurs and what are the characteristics of such interactions. Fanguy, et al. (2023) offer some interesting suggestions for how interaction might be operationalized, but few studies have included such data. So while studies do demonstrate the positive impact of collaborative notes (e.g. Baldwin, et al. 2019), the mechanisms responsible are unclear.
One additional factor is likely quite significant. Group comparisons between individual and collaborative notetaking ignore the individual nature of contributions within the collaborative groups (Fanguy, et al., 2023). No matter the nature of the inputs, we all learn as individuals and without a mechanism for identifying the type and extent of individual involvement, group comparisons will always be somewhat deficient. Even if group differences can be demonstrated, some within a group may benefit and some may not. The typical ending for many research articles?—?more research is needed?—?clearly applies to this topic.
One final point, I can and will suggest several digital collaborative tools for those of you who are interested, but I also caution that it is important to understand the purpose and hence perhaps the the strategies of notetaking that are to be recommended. As an academic, I studied student notetaking as would be applied to improve performance on future examinations. In my own work as an academic, I was and continue to be interested in the way I can take notes myself. There are several important differences in these circumstances. A student needs to understand the priorities of the course and instructor as would be relevant to an upcoming examination or writing project to take the most useful notes. Complete notes when requirements are unknown would seem a reasonable goal. My own goals are more self-imposed, but also are to record information that would potentially be useful over a much longer span of time. Capturing what seem to be important ideas in a form that will make sense to me several years in the future seems a different task.
Recommendations:
Google docs?—?collaborative notetaking may work with tools already familiar to educators. Multiple studies I have reviewed were conducted by assigning small groups of students (say 4–5) to a common Google doc file.
Hypothes.is?—?Hypothesis is a free tool that has been around for a while and is increasingly integrated into many LMSs used in higher ed. The tool is flexible allowing annotations and highlights to be publicly shared or shared with a designated group.
Glasp?—?Glasp is a recent entry to this category and is the tool I use for my own work. I like the tool because it is flexible in ways similar to Hypothesis and allows me to export the content I generate for long-term use in other Personal Knowledge Management (PKM) systems.
References:
Baldwin Matthew, P., Mik, F., & Costley Jamie, H. (2019). The effects of collaborative note-taking in flipped learning contexts. Journal of Language and Education, (4), 20.
Fanguy, M., Baldwin, M., Shmeleva, E., Lee, K., & Costley, J. (2021). How collaboration influences the effect of note-taking on writing performance and recall of contents. Interactive Learning Environments, 1–15.
Fanguy, M., Costley, J., Courtney, M., & Lee, K. (2023). Analyzing collaborative note-taking behaviors and their relationship with student learning through the collaborative encoding-storage paradigm. Interactive Learning Environments, 1–15.
When explaining it helps to have examples both for personal understanding and for communication. My more recent interest in long-term notes has provided a useful example that relates well to my long/term interest in generative activities. This specific collection of note collection activities is convenient because the activities are similar yet illustrate important differences. Notetaking is also an activity most have applied and comments on variations in how the activity can be applied are relatable contributing to my efforts to communicate. My more general goal is to help educators understand the purpose behind the assignments or study suggestions they make.
Generative activities are external tasks learners engage in that encourage productive cognitive behaviors. External tasks to influence thinking activities. Several researchers have identified hierarchies that attempt to explain the benefits of the external tasks and differentiate the less and more powerful activities.
Two examples of hierarchies include the proposals of Chi (2009) and Fiorella and Mayer (2016)
Chi (2009) proposed the SOI framework – selective, organizing, and interactive.
Fiorella and Mayer (2016) proposed a similar ICAP framework (reversed here to show the parallels with Chi) – passive, active, constructive, interactive.
Some further clarification may be necessary. Selective seems self-explanatory. When reading selective is the active process of identifying important material. Constructive, when applied to taking notes, has a specific meaning. It implies the integration of new information with what one already knows. For example, thinking of an example (something you already know) associated with a concept or principle just learned creates a new representation. The learner is putting things together or finding applications. Interactive as defined here is a social process. It could relate to processes such as might be involved in cooperative learning. Both parties or even a larger group combine their individual understandings to create a superior composite.
I am relating these hierarchies to note-taking activities as might be explained by Aherns (2022). This author described notetaking in a little different way than might be assumed to apply in a school or college setting. I like to think of it as taking notes for the long term. This might describe the purpose I have for taking notes. I am not taking notes for an exam in a couple of weeks or at the end of the semester. I am not taking notes to write a paper for my instructor. I am engaging in reading for purposes that might be realized in a few years. I want my notes to be useful when in the future I have a need for the information I understood when the note was created, but may not be remembered when that information would be valuable.
I am extending Aherns a bit here, but a sequence based on his writing might include the following:
Here are some clarifications of these terms. Reading (or listening) is the lowest stage and involves the exposure to information. Fleeting notes involve the recording of information with little elaboration. Students tend to take this type of notes while listening to a lecture possibly because they must get the information down while the lecturer continues to speak. Highlighting is similar in that it involves selection with little additional processing. Smart notes is Ahern’s term for notes that I remember him describing as providing sufficient context that a note would make sense to me in the future. In other words, this type of note must stand alone as a useful resource. Such notes would also be understandable by others with reasonable background knowledge.
It is important to recognize that learner engagement in generative activities involves potential rather than guaranteed benefits. Roscoe and Chi offer an interesting way of describing potential. They were writing about peer teaching as a generative activity, but the distinction they identify makes sense when applied to other activities. Their distinction is between knowledge telling and knowledge building. If learners are asked to explain a concept to a peer or summarize a concept as a note, they can repeat what they heard or read or they can interpret what they have heard or read in generating an output. Similarly, learners can merge their notes with a peer or they can compare and contrast their notes resulting in deeper processing of the content.
Because most generative activities involve the production of a product, educators can review these products from time to time to evaluate how active learners are being in thinking about what they are learning.
Insights
A few additional comments to consider as a summary. These ideas are interesting and quite concrete. In addition, the analyses are realistic in recognizing that positive results are not automatic.
First, what may seem to be a similar activity may have different consequences as a function of the kind of thinking applied
Second, it is what the student does in completing a generative task that results in learning not just the task assigned.
References
Ahrens, S. (2022). How to take smart notes: One simple technique to boost writing, learning and thinking.
Chi, M. T. (2009). Active?constructive?interactive: A conceptual framework for differentiating learning activities. Topics in cognitive science, 1(1), 73-105.
Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28(4), 717-741.
Roscoe, R. D., & Chi, M. T. H. (2007b). Understanding tutor learning: Knowledge-building and knowledge-telling in peer tutors’ explanations and questions. Review of Educational Research, 77, 534–574.
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