BJ Fogg, known from his work on persuasive technology, talked about making persistent behavior change via tiny habits. Very interesting research with important implications both personally and commercially.
George Siemens #iel12 Keynote Mindmap
George Siemens delivered an enlightening talk contextualizing analytics, tying the need for more effective coupling in decision making with new types of data.
Flipping assessment
Inspired by Dave Cormier’s learning contract, and previous work at learner-defined syllabi and assessment, I had a thought about learner-created project evaluation rubrics. I’m sure this isn’t new, but I haven’t been tracking this space (so many interests, so little time), so it’s a new thought for me at any rate ;).
It occurred to me that, at least for somewhat advanced learners (middle school and beyond?), I’d like to start having the learners propose evaluation criteria for rubrics. Why? Because, in the course of investigating what should be important, they’re beginning to learn about what is important. Say, for instance, they’re designing a better services model for a not-for-profit (one of the really interesting ways to make problems interesting is to make them real, e.g. service learning). They should create the criteria for success of the project, and consequently the criteria for the evaluation of the project. I wouldn’t assume that they’re going to get it right initially, and provide scaffolding, but eventually more and more responsibility devolves to the learner.
This is part of good design; you should be developing your assessment criteria as part of the analysis phase, e.g. before you start specifying a solution. This helps learners get a better grasp on the design process as well as the learning process, and helps them internalize the need to have quality criteria in mind. We’ve got to get away from a vision where the answers are ‘out there’, because increasingly they’re not.
This also ties into the activity model I’ve been talking about, in that the rationale for the assessment is discussed explicitly, make the process of learning and thinking transparent and ‘out loud’. This develops both domain skills and meta-learning skills.
It is also another ‘flip’ of the classroom to accompany the other ways we’re rethinking education. Viva La Revolucion!
Making rationale explicit
In discussing the activity-based learning model the other day, I realized that there had to be another layer to it. Just as a reflection by the learner on the product they produce as the outcome of an activity should be developed, there’s another way in which reflection should come into play.
What I mean here is that there should be a reflection layer on top of the curricula and the content as well, this time by the instructor and administration. In fact, there may need to be several layers.
For one, the choice of activities should be made explicit in terms of why they’re chosen and how they instantiate the curricula goals. This includes the choice of products and guidance for reflection activities. This is for a wide audience, including fellow teachers, administrators, parents, and legislators. Whoever is creating the series of activities should be providing a design rationale for their choice of activities.
Second, the choice of content materials associated with the activities should have a rationale. Again, for fellow teachers, administrators, parents, and legislators. Again, a design rationale makes a plausible framework for dialog and improvement.
In both cases, however, they’re also for the learners. As I subsequently indicated, I gradually expect learners to take responsibility for setting their own activities, as part of the process of becoming self learners. Similarly, the choice of products, content materials, and reflections will become the learners to improve their meta-learning skills.
All together, this is creating a system that is focused on developing meaningful content and meta-learning skills that develops learners into productive members of the society we’re transitioning into.
(And as a meta-note, I can’t figure out how to graft this onto the original diagram, without over-crowding the diagram, moving somehow to 3D, or animating the elements, or… Help!)
Applying Expertise
I’m trying to get my mind around how the information we’re finding out about expertise matches to the types of problems people face. Clearly, you want to align your investments appropriately to situations you face. If you look across the literature on expertise, and the recent writing on how our brains work (c.f. Kahneman’s Thinking Fast and Slow), you see an emerging picture of expertise. When you combine this with the situations organizations are increasingly facing, you recognize that we need to get more granular about the types of problems we’re facing and the solutions we have on tap.
Starting with the types of problems, there are more than just the problems we know and the ones we don’t. When you look at the Cynefin model, which characterizes the types of problems we face, we see what types of expertise are helpful. Beyond work that should be automated, there are formulaic types of complicated problems that can be outsourced or accomplished by skilled or well-supported practitioners. Then there are the complex problems that require deeper expertise. Beyond that is the chaotic state where you have to try something to move it into one of the other states, and there are certainly reasons to believe that deep expertise .
So now we look at what’s known about our knowledge. We’ve known for a while that expertise is slowly accumulated, and becomes deeper in ways that are hard to unpack (hence why you need some detailed approaches to get at their understanding). What’s also becoming clear is that this ability to make expert judgements, once compiled away, is most effective in quick (not laborious) application, with a caveat. As Kahneman tells us, this expertise needs to be developed in a field that is “sufficiently regular to be predictableâ€, and in which the expert gets quick and decisive feedback on whether he did the right or the wrong thing. Otherwise, you need to do the hard yards, the slow thinking that’s effortful and systematic. Now, if it’s out of your area of expertise but a known problem, you have two choices: either take a well-known (and appropriate) but laborious approach, or hire the appropriate expertise. If it’s a relatively novel situation, either unique or new, you’ll need a different type of expertise.
We can infer that having a rich suite of models and frameworks helps in circumstances where the right solution isn’t obvious. The conclusion is clear: advanced experts may not immediately know the solution if the problem is reasonably complex (if so, you can get by with a practitioner), but their deeply developed intuition, based upon experience, and associated approaches to those types of problems will have a higher likelihood of finding a solution. Particularly if their expertise spans problem-solving in general, and specific expertise in at least some of the involved domains. Experience solving complex problems, and having a deep and broad conceptual background increases the likelihood of a systemic and comprehensive solution.
To think about it another way, this article makes a distinction between puzzles and mysteries. Puzzles have an answer, once you identify the information needed, collect it, and execute against it. This is the ‘Complicated’ part of the Cynefin situation. Mysteries are where you can’t know what will happen, and you have to experiment. This is the ‘Complex’ or ‘Chaotic’ parts of the model. You’re better off in the latter two if you’ve got good systems thinking, and a suite of useful models in your quiver.
So, when facing a problem, you have to characterize it: is this a puzzle where someone has an off-the-shelf solution “ah, we know that pain, and we solve it this way”, versus the mystery situation where it’s not clear how things will sort out, and you need a much richer conceptual background to address it. In the former case, you can find vendors or consultants with specific expertise. In the latter, the implication clearly is that you want someone who’s been thinking and doing this stuff as long as possible. You want someone who can guide some experiments.
The risk of trying to solve the complex problems with off-the-shelf solutions or DIY is that your answer is likely to be missing a significant component of the situation, and consequently the solution will be partial. You need the right type of expertise for the right type of problem.
Mentoring
I was talking today with an organization that has mentoring as a very core feature of their culture, and it got me reflecting on the fantastic luck I’ve had in my career. Even before working, I had some great teachers, and then many folks have helped shape me through my job experience.
Dick Bergeron was a 12th grade teacher at SPHS who really helped me understand a different path to learning and thinking. He did what I now know to be reciprocal teaching, had us take turns talking about what we were learning from our reading, and discussing it, with him facilitating our reflection.
I got a job while I was in college at UCSD, maintaining the computer records for the office that did tutoring on campus, and Carmel Myers and Ken Majer helped me learn how to be professional (particularly when I screwed up).
Seeing the connection between computers and learning via that job, I designed my own major in college, and with the guidance of Hugh Mehan and Jim Levin learned a lot about what constituted good research. They also lived what great student development was.
In my first job, designing and programming educational computer games for DesignWare, Jim Schuyler and Lesley Czechowicz helped me learn quite a bit about how organizations run and what good management is.
I returned to grad school at UCSD after a summer working with Ken Majer again, and Don Norman patiently helped me rediscover and expand my understanding of research and cognition, particularly the application thereof. Don is also a great role model for top-notch critical and innovative thinking. At the Learning Research & Development Center at the University of Pittsburgh, Leona Schauble furthered my understanding of detailed research and development while guiding my post-doctoral fellowship.
At the University of New South Wales, where I took up an academic position, Paul Compton served to model what a wise leader really looks like. When I stepped away from the University, first Ron Watts at Open Net and then Rim Keris at Access CMC helped me take steps in understanding a strategic approach to business.
Jim Schuyler brought me back to the US, where he again mentored me on team leadership. He also introduced me to Joe Miller, who has served to really help me understand the next level of organizational strategy.
Since then, my business partners, Charlie Gillette at Knowledge Anywhere and Mohit Bhargava at LearningMate, have helped me learn much about business models and the art of the deal. And my colleagues in the Internet Time Alliance – Jay Cross, Jane Hart, Harold Jarche, and Charles Jennings – have taught me a lot about working as an independent and together.
These are the ones where I had an extended period of time with, but many other folks have served as models and provided assistance: Ellen Wagner and Marcia Conner are two that come to mind, and many more I’m forgetting, as well as many friends who’ve shared good times (and bad). Naturally, my parents had a wee bit of influence as well. And I’ve been doubly fortunate that many of these folks have remained in touch.
There certainly is an art to mentoring, though it can be developed, and I reckon there’re also some skills to being a good mentee. I hope I’ve been able to do some of the former, and not do the latter too badly.
I certainly still have lots to learn, but I’m exceptionally grateful to these folks. Many kudos to them, but of course all faults of the end product remain with the author ;). I think increasingly we can and should be continually mentoring those we care about, and mutually mentoring each other. Here’s to learning!
Thinking well and, well, not so well
A number of books have crossed my path for a variety of reasons, and there’re some lessons to be extracted from three of them. All have to do with looking at how our brains work, and some lessons therefrom. There have been quite a bit of kerfuffle about ‘brain-based learning’, of which too much is inappropriate inferences from neuroscience to learning. What I’m doing here is not that, but instead reporting on three books, only one of which has an explicit discussion of implications for both education and work. Still, valuable insight comes from all three.
Let me get the negative stuff out of the way first, a book that a number of folks have been excited about, Joshua Foer’s Moonwalking with Einstein, just did nothing for me. It’s a great tale well told, but the lessons were only cautionary. In it, a journalist gets intrigued enough with remembering to train sufficiently to win the US memory championships (apparently, globally, a relatively minor accomplishment). He reveals many memory tools to accomplish this, and points out some potential fraud along the way. He also concludes that despite this heightened ability, there is little relevance in the real world. We have devices that can be our memory now, and the need for these skills is questionable at best. All in all, little benefit except to be skeptical.
A second book, Daniel Kahnemann’s Thinking Fast and Slow, is a different story. Kahnemann, and his late long-time collaborator Amos Tversky, conducted some seminal research in how we make decisions (essential reading in my grad school career). And the best way to convey how we do this, as Kahnemann tells us, is to postulate two separate systems. Not surprisingly one is fast, and one is slow. The book is quite long, as Kahnemann goes through every phenomenon of these outcomes that they’ve discovered (often with collaborators), but each chapter closes with some statements that capture the ways your thinking might be wrong, and ways to compensate. It could use more prescriptions and less description (I started skimming, I confess), but understand the two systems and the implications are important. It’s a well-written and engaging book, I just wish there was a ‘take home’ version.
The fast system is, essentially, intuition. This comes in many ways from your experience, and experts in a field should trust their intuition (there’s a strong argument here for hiring someone with lots of experience) in their area. In areas where expertise is needed, and you don’t have it, you should go to the slow system, conscious rational thought. Which is very vulnerable to fatigue (it taxes your brain), so complex decisions late in a day of decision are suspect. If your decision is commonplace, you can trust the fast system, and many times you’ll be using the slow system just to explain the decision the fast system came up with, but we’re prone to many forms of bias. It’s a worthwhile read, and tells us a lot about how we might adapt our learning to develop the fast system when necessary, and when to look to the slow system.
Finally, Cathy Davidson’s written Now You See It, a book that takes an attentional phenomena and builds a strong case for more closely matching learning and work to how we really think. (I was pointed to it by a colleague who complained that my learning theory references are old; I still take my integration of learning theory as appropriate but nice to see that more recent work reflects my take on the best from the past. :) The phenomena is related to how our attention is limited and we need help focusing it. For a dramatic demonstration of this phenomena, view this video and follow the instructions. Her point is that what and how we pay attention does not reflect our current schooling systems nor our traditional work environments. She uses this and myriad examples to make a compelling case for change in both. On the learning side, she argues strongly for making learning active and meaningful (a view I strongly support), and start using the technology. On the other side, she talks about the new ways of working consonant with our Internet Time Alliance views. It’s very readable, as it’s funny, poignant, apt, and more.
I highly recommend Cathy Davidson’s book as something everyone should understand. Like I said, I wish there were a ‘Readers Digest Condensed‘ version of Kahnemann’s book. It’s worth having a look at if you’re responsible for decisions by folks, however, and at least the first few chapters if you’re at all responsible for helping people make better decisions.
Style-ish
I’m a real fan of styles, ala Microsoft Word. If you don’t get this concept, I wish you would. Let me explain.
The concept is fairly simple. Instead of hand-formatting a document by manually adding in bold, font sizes, italics, indents, extra paragraph returns, you define a paragraph as a ‘style’. That is, you say this paragraph is a heading 1, that paragraph is normal or body text, this other one is a figure, etc. Then you define what a heading one looks like: bold, font size 14, with space before of 6 pts, and space after of 6 pts, etc.
Why use styles? Several reasons. First, I can then use the outline feature to organize my writing, and then automatically have the right headings. Second, if I add in content, I don’t have to hand-reformat the way returns have been used to force page breaks (really). Third, and most importantly, if someone wants there to be a different look and feel to the document, I just change the definition of styles, I don’t have to manually reformat the document.
If you use styles correctly, the document automatically handles things like page breaks and formatting, so the document looks great no matter how you change and edit it. Which is why, when someone sends me a document to edit that is hand formatted, I’ll often redo the whole (darn) thing in styles, just to make my life easier. And grumble, with less than complimentary thoughts about the author.
Now, styles are not just in Microsoft Word, they’re in Pages, Powerpoint, Keynote, and other places where you end up having repeated formats. They may have a different title, but the idea plays a role in templates, or themes, or masters, or other terms, but the concept is about separating out what it says from how it looks, and having the description of how it looks separately editable from what it says. It’s the point behind CSS and XML, but it manifests increasingly in smart content.
And I admit, I’m really good with styles in Word, I’m pretty good in Pages, and still wrestle with Keynote, and I don’t know about other tools like Excel, but I reckon the concept is important enough that it should start showing up everywhere.
Please, please, use styles. At least in anything you send to me ;).
X-based learning: sorting out pedagogies and design
It’s come up in a couple of ways how my (in progress) activity-based framework for learning is related to other models, e.g. performance-based learning. And, looking around, I am reminded that there’s a plethora of models that have overlap. I’ll try to sort them out. This will undoubtedly be an ever-growing list, as there seems to be X-based learning where X = anything, and I’m sure folks supportive of their approach will let me know ;). Recognize that these are very sketchy descriptions, intended to communicate similarities, not tease apart deep nuances.
At core is the reasoning that meaningful activities have myriad benefits. Learners are engaged in working on real things, and the contextualization facilitates transfer to the extent that you’ve designed the activity to require the types of performance they’ll need in the world. There’s the opportunity to layer on multiple learning goals from different domain, and 21st century skills like media communications, and if it’s social (which is a recurring theme in these models) you get things like leadership and teamwork as well. Better engagement and learning outcomes are the big win.
First, there’s already an activity-based learning out of India! It seems to focus on having learners do meaningful things, which very much is at core here. There’s also an activity-based curriculum, by the way, which is also the way I’m thinking of it: a sequence of activities is a curriculum. This fits within active learning, arguably, in that there’s a desire for the learner to be actually doing something as the basis of learning, though the types of classroom activities of debates and discussions seem not as powerful as others cited below.
So, performance-based learning seems to be focused on assessment, having the students actively demonstrate their ability. This is, to me, an important aspect, as cognitive science recognizes that passing a knowledge test about something is not likely to transfer to the ability to do (we call it ‘inert knowledge’). That’s the point of having products of activities, at least reflection , so it sounds very much is in synergy. This also appears to be the focus of outcomes-based learning, which also emphasizes actual production, but while touting constructivism seems to end up being more a tool of the status quo. This can also be similar (and ideally should be) to competency-based learning, where there are explicit performance outcomes expected, rather than grading on the curve.
And there is problem-based learning and project-based learning. Both focus on having learners engage in meaningful activity, with the distinction between the two having to do with whether the problem is set by the instructor, or whether the project is decided is decided by the students. There are arguments for both, of course; for me, problems are easier to specify, it takes a special teacher to help shape a project and wrap the learning goals around it. I reckon serious games are problem-based learning, by the way.
Service learning is another related idea, that has learners doing meaningful projects out in the community. This is activity-based and expands upon the meaningfulness by connecting it to the community. I’ve been a fan of the Center for Civic Education’s Project Citizen as an example of this, having students try to pass legislation to improve things in their area, and consequently learning about law-making.
Inquiry-based learning shares the focus on activities of information gathering, but has primarily been based in science. It seems to not have a goal other than exploration and understanding, with an even more extreme view of learner control. This seems good with a self-motivated learner, and as long as the learner is either a self-capable learner, or there’s a facilitator, it could work. This seems very similar to the MOOC approach of Siemens & Downes. It also seems to be almost identical to the community of inquiry approach.
I frankly want an activity-based pedagogy and curriculum to support all of these models. The benefits, and the resistance to knowledge dump and fact test forms of learning, drive this perspective. Getting there requires a different type of learning design that one focused on standards. You need to shift, focusing on what do the students need to be able to do afterwards, and working backward from there. Understanding by design is a design approach that works backwards from goals, and if you set your outcomes on performance, and then align activities to require that performance, you have a good chance of impacting pedagogy, and learning, in meaningful ways. I admit it surprises me that this needs to be pointed out, but I see the consequences of content-driven (forward) design too often to argue.
The point is to find an umbrella that holds a suite of appropriate pedagogies and makes it difficult to do inappropriate ones. As Les Foltos tweeted: “We need to fan the fires for these instructional strategies. They don’t align well with standardized tests”. Exactly.
Reimagined Learning: Content & Portfolio elaborated
In a previous post I laid out the initial framework for rethinking learning design, and in a subsequent post I elaborated the activity component. I want to elaborate the rest a wee bit here. Two additional components of the model around the activities were content and then products coupled with reflection.
One of the driving points behind the model was to move away from content-driven learning, and start focusing on learning experience. As a consequence, the activities were central, but content was there to be driven to from the activities. So, the activity would both motivate and contextualize the need to comprehend some concept or to access an example, and then there would be access paths to the content within the activity. Or not, in that there might be a selection of content, or even the opportunity or need for the learner to choose relevant content. As with the activity, you gradually want to release responsibility to the learner for selecting content, initially modeling and increasingly devolving the locus of control.
A second component is the output of the activity. It was suggested that activities should generate products, such as solutions to problems, proposals for action, and more. The activity would be structured to generate this product, and the product could either be a reflection itself (e.g. an event review) or tangible output. It could be a document, audio, or even video. If the product itself is not a reflection, there should be one as well, a reflection. Eventually, the product choice and reflection piece will be the responsibility of the learner, and consequently there will be a scaffolding and fading process here too.
Note that the product of learner activity could then become content for future activities. The product could similarly be the basis for a subsequent activity.
The reflection itself is a self-evaluation mechanism, that is the learner should be looking at their own work as well as sharing the underlying thinking that led to the resulting product. Peers could and should evaluate other’s products and reflections as an activity as well (getting just a wee bit recursive, but not problematically so). And, of course, the products and reflections are there for mentor evaluation. And, as activities can be social, so too can the products be, and the reflections.
While digital tools aren’t required for this to work, it would certainly make sense from a wide-variety of perspectives to take advantage of digital tools. Rich media would make sense as content, and this could include augmented reality in contexts. Further, creation tools could and should be used to create products and or reflections. Of course, activities too could be digitally based such as simulations, whether desktop or digitally delivered, e.g. simulations or alternate reality games.
The notion is to try to reframe learning as a series of designed activities with guided reflections, and a gradual segue from mentor-designed to learner-owned. Does this resonate?