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Clark Quinn’s Learnings about Learning

A complex look at task assignments

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I was thinking (one morning at 4AM, when I was wishing I was asleep) about designing assignment structures that matched my activity-based learning model.  And a model emerged that I managed to recall when I finally did get up.  I’ve been workshopping it a bit since, tuning some details. No claim that it’s there yet, by the way.

ModelAssignmentAnd I’ll be the first to acknowledge that it’s complex, as the diagram represents, but let me tease it apart for you and see if it makes sense. I’m trying to integrate meaningful tasks, meta-learning, and collaboration.  And there are remaining issues, but let’s get to the model first.

So, it starts by assigning the learners a task to create an artefact. (Spelling intended to convey that it’s not a typical artifact, but instead a created object for learning purposes.) It could be a presentation, a video, a document, or what have you.  The learner is also supposed to annotate their rationale for the resulting design as well.  And, at least initially, there’s a guide to principles for creating an artefact of this type.   There could even be a model presentation.

The instructor then reviews these outputs, and assigns the student several others to review.  Here it’s represented as 2 others, but it could be 4. The point is that the group size is the constraining factor.

And, again at least initially, there’s a rubric for evaluating the artefacts to support the learner. There could even be a video of a model evaluation. The learner writes reviews of the two artefacts, and annotates the underlying thinking that accompanies and emerges.  And the instructor reviews the reviews, and provides feedback.

Then, the learner joins with other learners to create a joint output, intended to be better than each individual submission.  Initially, at least, the learners will likely be grouped with others that are similar.  This step might seem counter intuitive, but while ultimately the assignments will be to widely different artefacts, initially the assignment is lighter to allow time to come to grips with the actual process of collaborating (again with a guide, at least initially). Finally, the final artefacts are evaluated, perhaps even shared with all.

Several points to make about this.  As indicated, the support is gradually faded. While another task might use another artefact, so the guides and rubrics will change, the working together guide can gradually first get to higher and higher levels (e.g. starting with “everyone contributes to the plan”, and ultimately getting to “look to ensure that all are being heard”) and gradually being removed. And the assignment to different groups goes from alike to as widely disparate as possible. And the tasks should eventually get back to the same type of artefact, developing those 21 C skills about different representations and ways of working.  The model is designed more for a long-term learning experience than a one-off event model (which we should be avoiding anyways).

The artefacts and the notes are evidence for the instructor to look at the learner’s understanding and find a basis to understand not only their domain knowledge (and gaps), but also their understanding of the 21st Century Skills  (e.g. the artefact-creation process, and working and researching and…), and their learning-to-learn skills. Moreover, if collaborative tools are used for the co-generation of the final artefact, there are traces of the contribution of each learner to serve as further evidence.

Of course, this could continue. If it’s a complex artefact (such as a product design, not just a presentation), there could be several revisions.  This is just a core structure.  And note that this is  not for every assignment. This is a major project around or in conjunction with other, smaller, things like formative assessment of component skills and presentation of models may occur.

What emerges is that the learners are learning about the meta-cognitive aspects of artefact design, through the guides. They are also meta-learning in their reflections (which may also be scaffolded). And, of course, the overall approach is designed to get the valuable cognitive processing necessary to learning.

There are some unresolved issues here.  For one, it could appear to be heavy load on the instructor. It’s essentially impossible to auto-mark the artefacts, though the peer review could remove some of the load, requiring only oversight. For another, it’s hard to fit into a particular time-frame. So, for instance, this could take more than a week if you give a few days for each section.  Finally, there’s the issue of assessing individual understanding.

I think this represents an integration of a wide spread of desirable features in a learning experience. It’s a model to shoot for, though it’s likely that not all elements will initially be integrated. And, as yet, there’s no LMS that’s going to track the artefact creation across courses and support all aspects of this.  It’s a first draft, and I welcome feedback!

 

Cheers for #chats

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For a reason I can no longer recall, I was thinking about twitter chats.  Two, in particular, came to mind  – #lrnchat and #chat2lrn  –    for one specific reason. And I think it’s worth calling attention to them for that reason.

They have a format that for an hour, questions come out every few minutes or so to the hashtag associated with the chat. And the participants answer the questions, continuing to use the hashtag. One of the interesting phenomena to me is that unlike many conversations, the answers can diverge as much as converge, and that’s OK. The topics vary, and in the questions and answers, you can learn a lot.  It’s valuable  to even see what the questions are, as well as the responses by others.

What’s fun about them is that people have fun with it; they riff off others’ posts in fun ways, they make silly tweets, and are generally real people as well as answering the questions.  They truly are learning events, and yet very human as well. When you finally meet in person a participant you’ve met online, it can be much more familiar than meeting someone you’ve heard about, because you’ve interacted with them. And while the community that participates isn’t huge, the learnings and insights are, and percolate through subsequent work, eventually impacting the industry.

Not completely coincidentally, both are on Thursdays: #lrnchat runs pretty much every Thursday US evening (8:30 ET, 5:30 PT) for an hour, and #chat2lrn runs every other week at 11 AM EST (which is 8 AM PDT when the US is in Daylight Savings Time). What’s amazing is  that they run!

What you need to know about these two chats (and others as well, I suspect), my specific issue here, is that they’re fully volunteer run.  That means that a group of folks has to decide a topic in advance, craft a series of questions, many times arrange an associated post, and arrange to get the questions  posted at the appropriate time.  This is a significant amount of work to achieve week in and week out. And I know, because I was a  #lrnchat moderator  for a number of years!

So  we owe these folks a big thanks for continuing on for a rewarding but effortful task. All these people have other jobs, but their contributions help all of us. There are other chats (specifically #guildchat, Fridays at 2 PM PT, 11AM ET) that follow the same format, but there the principals are salaried. Still, the fact that the organization provides resources to support them is appreciated, though they get some marketing capital as a return.

So I want to point out that the folks at lrnchat and chat2lrn  are owed thanks by the community (and all the other chats that others participate in that are supported by volunteers and organizations).  I salute you!

Activity-Based Learning

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On a recent conversation with some Up to All of Us colleagues, I was reminded about my ‘reimagining learning‘ model. The conversation was about fractals and learning, and how most tools  (e.g. the LMS)  don’t reflect the conversational nature of learning.  And I was thinking again about how we need to shift our thinking, and how we can reframe it.

I’d pointed one colleague to Diana Laurillard’s model of  conversational  learning, as it does reflect a more iterative model of learning with ongoing cycle of action and reflection. And it occurred to me that I hadn’t conveyed what the learner’s experience with the activity curriculum would look like. It’s implicit, but not explicit.

New Learning CycleOf course, it’s a series of activities (as opposed to a series of content), but it’s about the product of those activities.  The learner (alone or together) creates a response to a challenge, perhaps accessing relevant content as part of the process, and additionally annotates the thinking behind it.

This is then viewed by peers and/or a mentor, who provide feedback to the learner. As a nuance, there should be guidance for that feedback, so that it explicitly represent the concept(s) that should guide the performance. The subsequent activity could be to revise the product, or move along to something else.

The point being that the learner is engaged in a meaningful assignment (the activity should be contextualized), and actively reflecting. The subsequent activity, as the Laurillard model suggests, should reflect what the learner’s actions have demonstrated.

It’s very much the social cognition benefits I’ve talked about before, in creating and then getting feedback on that representation.  The learner’s creating and reflecting, and that provides a rich basis for understanding where they are at.

Again, my purpose here is to help make it clear that a curriculum properly should be  about  doing, not knowing.  And this is why I believe that there must   be people in the loop. And while much of that burden might be placed on the other learners (if you have a synchronous cohort model), or even the learner with guidance on generating their own feedback, with rubrics for evaluation, but you still benefit from  oversight in case the understanding  gets off track.

We can do a lot to improve asynchronous learning, but we should not neglect social when we can take advantage of it. So, are you wanting to improve your learning?

Aligning with us

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One of the realizations I had in writing the Revolutionize L&D book was how badly we’re out of synch with our brains. I think alignment is a big thing, both from the Coherent Organization perspective of having our flows of information aligned, and in processes that help us move forward  in ways that reflect  our humanity.

In short, I believe we’re out of alignment with our views on how we think, work, and learn.  The old folklore that represents the thinking that still permeates L&D today is based upon outdated models. And we really have to understand these differences if we’re to get better.

AligningThe mistaken belief about thinking is that it’s all done in our head. That is, we keep the knowledge up there, and then when a context comes in we internalize it and make a  logical  decision and then we act.  And what cognitive science says is that this isn’t really the way it works.  First, our thinking isn’t all in our heads. We distribute it across representational tools like spreadsheets,  documents, and (yes) diagrams.  And we don’t make logical decisions without a lot of support or expertise. Instead, we make quick decisions.  This means that we should be looking at tools to support thinking, not just trying to put it all in the head. We should be putting as much in the world as we can, and look to scaffold our processes as well.

It’s also this notion that we go away and come up with the answer, and that the individual productivity is what matters.  It turns out that most innovation, problem-solving, etc, gets better results if we do it together.  As I often say “the room is smarter than the smartest person in the room  if you manage the process right“.  Yet, we don’t.  And people work better when they understand why what  they’re doing is  important and they care about it. We should be looking at ways to get people to work together more and better, but instead we still see hierarchical decision making, restrictive  cultures, and more.

And, of course, there still persists this model that information dump and knowledge test will lead to new capabilities.  That’s a low probability approach. Whereas if you’re serious about learning, you know it’s mostly about spacing contextualized application of that knowledge to solve problems. Instead, we see rapid elearning tools and templates that tart-up quiz questions.

The point being, we aren’t recognizing that which makes us special, and augmenting in ways that bring out the best.  We’re really running organizations that aren’t designed for humans.  Most of the robotic work should and will  get automated, so then when we need to find ways to use people to do the things they’re best at. It should be the learning folks, and if they’re not ready, well, they better figure it out or be left out!  So let’s get a jump on it, shall we?

Bill Nye (Science Guy) #LSCon Keynote Mindmap

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As the opening keynote for the always excellent Learning Solutions conference, Bill Nye gave an entertaining talk on the benefits of science and learning, drawing on his experience.  I really liked how he paid tribute to his father’s fascination with sundials to get one put on the Mars rovers.

Metacognitive Activity?

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So, as another outcome of the xAPI base camp a few weeks back, I was wondering about tracking not only learning, but meta-learning. That is, not only what activity might mean ‘learning’, but what might mean ‘meta-learning’ is happening?  I started wondering about a vocabulary, but realized that you’d have to have activity that you could actually detect that was evidence of meta-learning.  And I didn’t know what that was. Naturally, I started diagramming.

I started with Harold Jarche’s Personal Knowledge Mastery  model  of Seek-Sense-Share.  This is about how you continue to learn in manageable ways, and it served as an organizing framework.  To each of the elements, I attributed activities that would constitute learning in that model, and then above it I was thinking what would constitute meta-learning.

MetaCogSo, for seek, we start with reading what comes into your feeds, searching about particular topics, and asking questions of your network. Sensing is about reconciling what’s found with your own knowledge. So you could write or present, diagram (see what I  did there?), or experiment. And then to share you can post, or comment, or send a pointer to something.

So what are actions that reflect on those actions?  For seeking, you can adjust your feeds of what you follow, you can try a different search mechanism, or you can follow new people.  These are all detectable, I reckon.

For sensing, I see it as a little harder.  How do we know when you’re annotating a document  with the underlying thinking, not just documenting your progress?  How do we know when you’re explaining the thinking behind a diagram (here it’d be about my choice of vertical dimension, and spreading things below and above)?  How do we know when you’re actually reviewing your experimental approach or the results?

For sharing, it’s a mixed bag. If you choose to use a different media (perhaps it’s relative, like when I created an  animation  after blogging for > 10 years ;), we might know. If you try out a new social media platform/channel, we can probably note that.  If you’re reflecting on your comments from others, how would we know?

And this is just one way of carving it up.  The point being, meta is good, but detecting and tracking it is hard.  We might ask people to annotate it with tags, but that’s problematic too.  I have no obvious answers, but it’s a question I had, and I’m thinking out loud about it.  I welcome your thoughts, too.

Mindmapping

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So, if you haven’t figured it out yet, I do mindmaps.  As I’ve recited before, I started doing it as a way to occupy my brain enough so I could listen to keynotes, but occasionally I use it to other purposes, such as representing structure or even planning. And thru  my esteemed colleague Jane Hart  (who’s Modern Workplace Learning book I’m going through and thoroughly impressed), I’m giving a mindmapping webinar today for a group of several universities in Ireland.  I thought I’d share what I’m presenting.

MindmappingMindmaps are a visual way of representing knowledge.  You use links to show connections between concepts (represented as nodes), developing a structural relationship.  A true semantic network would have those links labeled, as there are many different types of relationships (causal, precedence, hierarchical), but mindmaps typically have unlabeled links.  Still, mindmaps capture structural information in a visual way, that supports tapping into our powerful visual processing system. (This is the one I created for them to advertise the talk, it’s neither the order I ended up for them or am using here. ;)

You can add information to them; as a visual tool, you can add extra graphical information, like tables or charts, to augment the map.  You can similarly add color as a way to layer additional semantic information such as similarity. And the links can be plain or directional.  Importantly, while a mindmap can be essentially equivalent to an outline  if you maintain a strict tree structure, you can create a graph by having more complex links that generate loops.

The process of mindmapping is fairly straightforward: you have a central node, and then generate additional nodes and link them. I tend to go counter-clockwise, and include an arrow indicating that, because I’m capturing a linear presentation, but generating a static representation of information doesn’t have any directional requirement. I find that I have to frequently rearrange to fit the mindmap appropriately to the image, but that’s part of the benefit.

The evidence appears to show that mindmapping is superior to note-taking. I don’t do it all the time, but there are reasons to think you should.  The reasons, I believe, that it  is better is that you’re not just transcribing a presentation, but you’re actively parsing it to represent the structure. If you do take notes, you should be paraphrasing what you hear in your own words, to have active processing of the information. The additional effort to extract the structure as well is a form of valuable cognitive processing that elaborates the information.  Doing both, paraphrasing and extracting structure, would be a great way to really comprehend what you’re hearing.

As suggested, it’s helpful to mindmap talks, but it can also be a thinking tool, to analyze situations and sort out your thoughts or plan activities and add elements as you think of them. No real advantage over an outline, potentially (though the ability to add other graphics and to make non-strict maps may counter that), though I suspect some find the drawing and rearranging to be a nice physical overhead to facilitate reflecting.  And, of course, it can be an evaluation tool, asking someone to create their maps to see their understanding.

While there are dedicated tools for mindmapping, both applications and in the cloud, which will make creating and rearranging easier (I presume), you can use almost any drawing package (I use OmniGraffle). You could use Powerpoint or Keynote, and even pencil and paper (if it’s just for the processing) though it can be harder to revise.

So, that’s my riff on mind mapping.  I welcome your thoughts.

Working wiser?

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Noodling:   I’ve been thinking about Working Smarter, a topic I took up over four years ago.  And while I still think there’s too little talk about it, I wondered also about pushing it further.  I also talked in the past about an interest in wisdom, and what that would mean for learning.  So what happens when they come together?

Working smarter, of course, means recognizing how we  really think, work, and learn, and aligning our processes and tools accordingly. That includes recognizing that we  do use external representations, and ensuring that the ones we want in the world are there, and we also support people being able to create their own. It means tapping into the power of people, and creating ways for them to get together and support one another through both communication and collaboration.  And, of course, it means using Serious learning design.

But what, then, does working  ‘wiser’ mean?  I like Sternberg’s model of wisdom, as it’s actionable (other models are not quite specific enough).  It talks about taking into account several levels of  caring about others, several time scales, several levels of action, and all influenced by an awareness of values.  So how do we work that into practices and tools?

Well, pragmatically, we can provide rubrics for evaluation of ideas that include considerations of others inside and outside your circles of your acquaintances, and in short- and long-term timeframes, and the impacts on existing states of affairs, ultimately focusing on the common good. So we can have job aids that provide guidance,  or bake it into our templates.  These, too, can be shown in collaboration tools, so the outputs will reflect these values.  But there’s another approach.

But, at core, it’s really about what you value, and that becomes about culture.  What values does the organization care about?  Do employees know about the organization’s ultimate goal and role?  Is it about short-term shareholder return, or some contribution to society?  I’m reminded about the old statements about whether you’re about selling candles or providing light.  And do employees know how what they do fits in?

It’s pretty clear that the values implicit in  steps to make workplaces more effective are really about making workplaces more humane, that is: respecting our inherent nature.  And movements like this, that provide real meaning, ongoing support, freedom of approach, and time for reflection, are to me about working not just smarter but also wiser.

We can work smarter with tools and practices, but I think we can work better, wiser, with an enlightened approach to who we are working with and how we work to deliver real value to not only customers but to society.  And, moreover, I think that doing so would yield better organizational  outcomes.

Ok, so have I gone off the edge of the hazy cosmic jive?  I am a native Californian, after all, but I’m thinking that this makes real business sense.  I think we can do this, and that the outputs will be better too, in all respects.  No one says it’d be easy, but my suspicion is it’d be worthwhile.

Model power!

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So, last  night I was talking with my lass, and happened to show her one of my diagrams. I keep a batch of  them around, and it happened to resonate. And (to use a horrible social media ploy): you’ll never believe what happened next!

So, we were talking about her school things, and among the topics was the strategy for studying.  She’s seen a friend who basically studies the night before an exam, and does well.  Of course, she’s forgotten it all within a week. Whereas my lass works hard, doesn’t do quite as well on the test (she has a wee bit of test anxiety, but not much), but will remember it later.  She’s (fortunately) interested in learning for intrinsic interest, rather than to meet the hurdles (but capable and willing to do those too).

Which, as I explained to her, is exactly predicted by the research. Spacing out studying means you don’t have it quite as accessible right afterward, but it’s there much later.  It’s a known phenomena of our cognitive architecture (and not neuroscience, citing my colleague Will who pointed me to the original research).  So, if you want to do well on the test, massed practice is just fine. If you want people to retain it, well, space it out!

Now, I have argued the power of models before, and that’s why I keep a suite of diagrams (essentially a quiver of models) on my devices (the qPhone and the qPad).  I can share them at relevant times as a tool for explanation or prediction, and together we can figure out what it  means. And that’s what I was doing, connecting her experience to frameworks that make sense.

What I heard today is that she’s gone and mapped out her study schedule for her finals, spacing it out to get the best results.  She’s applying the model to her own life!  So she’s comprehended the model and the implications. And I’m not touting this to show off my daughter (yes, I’m proud of her, but that’s between me and her), but to show how models serve as the guidance for making important decisions.

Models are powerful guides to making decisions. So are you baking models into your learning, personally and for others?