Graham Roberts kicked off the 2nd day of the Realities 360 conference talking about the Future of Immersive Storytelling. He told about their experiences and lessons building an ongoing suite of experiences. From the first efforts through to the most recent it was insightful. The examples were vibrant inspirations.
Stephanie Llamas kicked off the Realities 360 conference by providing an overview of VR & AR industry. As a market researcher, she made the case for both VR and AR/MR. With trend data and analysis she made a case for growth and real uses. She also suggested that you need to use it correctly. (Hence my talk later this day.)
So, I just finished teaching a mobile learning course online for a university. My goal was not to ‘teach’ mobile so much as develop a mobile mindset. You have to think differently than what the phrase ‘mobile learning’ might lead you to think. And, not surprisingly, some things went well, and some thing didn’t. I thought I’d share the learning lessons, both for my own reflection, and for others.
As a fan of Nilson’s Specifications Grading, I created a plan for how the assessment would go. I want lots of practice, less content. And I do believe in checking knowledge up front, then having social learning, and a work product. Thus, each week had a repeated structure of each element. It was competency based, so you either did it or not. No aggregation of points, but instead: you get this grade if you do: this many assignments correct, and write a substantive comment in a discussion board and comment on someone else’s this many times, and complete this level on this many knowledge checks. And I staggered the deadlines through the week, so there’d be reactivation. I’ve recommended this scheme on principle, and think it worked out good in practice, and I’d do it again.
In many ways it ‘teacher proofs’ the class. For one, the students are giving each other feedback in the discussion question. The choice of discussion question and assignment both were designed to elicit the necessary thinking, which makes the marking of the assignment relatively easy. And the knowledge checks set a baseline background. Designing them all as scenario challenges was critical as well.
And I was really glad I mixed things up. In early weeks, I had them look at apps or evaluated ones that they liked. For the social week, I had them collaborate in pairs. In the contextual week, they submitted a video of themselves. They had to submit an information architecture for the design week. And for the development week, they tested it. Thus, each assignment was tied to mobile.
It was undermined by a couple of things. First, the LMS interfered. I wrote careful feedback for each wrong answer for each question on the knowledge checks. And, it turns out, the students weren’t seeing it! (And they didn’t let me know ’til the 2nd half of the abbreviated semester!) There’s a flag I wasn’t setting, but it wasn’t the default! (Which was a point I then emphasized in the design week: start with good defaults!)
And, I missed making the discussions ‘gradeable’ until late because of another flag. That’s at least partly on me. Which meant again they weren’t getting feedback, and that’s not good. And, of course, it wasn’t obvious ’til I remedied it. Also, my grading scheme doesn’t fit into the default grading schema of the LMS anyways, so it wasn’t automatically doable anyways. Next time, I would investigate that and see if I could make it more obvious. And learn about the LMS earlier. (Ok, so I had some LMS anxiety and put it off…)
With 8 weeks, I broke it up like this:
And I think this was the right structure. It naturally reactivated prior concepts, and developed the thinking before elaborating.
For the content, I had a small set of readings. Because of a late start, I only found out that I couldn’t use my own mLearning book when the bookstore told me it was out of print (!). That required scrambling and getting approval to use some other writings I’d done. And the late start precluded me from organizing other writings. No worries, minimal was good. And I wrote a script that covered the material, and filmed myself giving a lecture for each week. Then I also provided the transcript.
The university itself was pretty good. They capped the attendance at 20. This worked really well. (Anything else would’ve been a deal breaker after a disaster many years ago when an institution promised to keep it under 32 and then gave me 64 students.) And there was good support, at least during the week, and some support was available even over the weekend.
Overall, despite some hiccups and some stress, I think it worked out (particularly under the constraints). Of course, I’ll have to see what the students say. One other thing I’d do that I didn’t do a good job of generally (I did with a few students) was explain the pedagogy. I’ve learned this in the past, and I should’ve done so, but in the rush to wrestle with the systems, it slipped through the cracks.
Those are my learning lessons. I welcome your feedback and lessons!
Is this YAMMMP? I suppose I can’t address every one, but I think picking a few here and there are perhaps instructive. And, maybe, a bit fun. So there was a post on 5 mobile learning strategies. I’m a wee bit opinionated on mobile learning, so I thought I’d have a look. And, of course, it seems to be a random selection. I guess there’s a requirement to regularly put out stuff, but it seems they get someone to make stuff up scattershot, for the sake of marketing. And while the advice isn’t bad, it’s just random bits of advice trying to create the appearance of expertise. Worse, it’s really not specific to mobile, and, therefore,…misleading.
Look, I’m a fan of mobile, obviously. But while mobile’s niche is performance support, what’s unique to mobile is context. Do something because of when and where you are. And this article has entirely missed it. And the other critical element is to think of mobile as a platform. It’s not a device, it’s not an app, it’s a unique delivery channel for many possibilities. Your initial exploration can be either of the microlearning components, but recognize that as soon as you use it, you’ll be expected to do more. And thinking platform is the key strategy here.
I understand that their intention is self-serving, these are things they can do. But pretending these are core strategies is misleading. And that’s the problem I’d like you to learn to detect. Go to the core affordances, and then drill down. I’ve talked about my own five mobile approaches, for instance. Don’t work up from what you can do until you know what that is doing to advance your capabilities as well. That is what’s strategic.
I was called out on a tweet pointing to an article on mobile. And, I have to say, I thought it was pretty underwhelming. It was the ‘old school’ view of mlearning, and I think that the post largely missed the point. So I thought it’d be valuable to walk through the claims. What I’m trying to accomplish is share how my thinking works, and perhaps contaminate you with a wee bit of it too ;). We need to get better at cutting through the hype (part of the debunking skills), and that includes microlearning and mobile malarkey as well.
The post makes four claims for why mobile is on the rise:
So let’s go through these. However, first I’m going to challenge the assumption!
Mobile is not ‘on the rise’. That’s so 2012. Mobile is well past the ‘new’ stage. Heck, Google was arguing ‘mobile first’ back in 2010! Even here in the US, it’s mainstream, and it’s been the ‘goto’ mode in other countries for much longer.
Now, the advancements in mobile technology are continuing, and impressive. Things like sensors for contextual information, networking for social connections, new interaction capabilities like pressure-sensitivity, and higher resolution screens and faster processors mean new capabilities. What the article is talking about, is cutting edge content. Yes, video can be useful ‘on demand’, and interactivity can be powerful. In context. But they’re not picking up on that. This is still the ‘get training wherever you are’ mentality. Mobile is really not about courses! But aybe they’ll get better..
Next is the chunks. Ok, so I’ve already weighed in on ‘microlearning’. Yes, small is better. It does matter whether you’re talking performance support or spaced learning, but small is good. However, this article touts that we prefer smaller chunks (er, yes, and that’s not a good indicator). And that we benefit from smaller. Yes, but this is still about ‘content consumption’. Mobile can, and should be more than that.
On to engagement. Here the claim is that these small bits are more engaging, but that we can do interactive things as well. And this is good: mini-scenarios (better written multiple choice), even branching scenarios can lead to better. However, here they’re talking quizzes and infographics. Again, mostly content, and also focused on knowledge, not skills. This isn’t where the emphasis should be. Spaced learning yes, but reactivation – reconceptualization, recontextualization, and reapplication – not content dump and knowledge test.
Finally, it’s about remote workers. Yes, again, contextualization to give the right thing, to the right person, at the right time and place. But no, they’re talking about accessing training where/when/ever. Yes, that’s nice. But not intrinsically exciting, and definitely not really capitalizing on mobile’s promise.
Look, the real mobile opportunity is about performance support and contextualized learning. Spaced learning is good (though not unique to mobile). But to argue mobile’s on the rise, and it’s about content, is to misconstrue the state of the industry and the opportunity. This is obviously a sales pitch for their mobile content delivery, but get clear about what you want from mobile. It’s a platform, so once you start people will expect more. It’s best if you need to think strategically about all that you can do and ensure you’ve seen the full picture before you settle on any one solution.
I’ll be giving an upcoming webinar where I make my case for defining microlearning. And, as part of my usual wrestling with clarity, I created a diagram. I thought I’d share it with you.
What, you want me to walk you through it? :)
Microlearning is a portmanteau (technical term: mashup) of micro and learning. Thus, it implies small bits of learning. Here I’m mapping it out in several ways. I’ve previously argued that there are three main ways, but let’s map the first two out. It’s either
And there are problems with both. Too often, folks talk about breaking an existing course down into small chunks, and I suggest that won’t work without some significant (!) effort. Just breaking it up means something seen earlier can be forgotten, so you need to worry about knowledge atrophy and plan reactivation. And that’s just spaced learning!
And I think it’s unlikely that you can have a single object lead to any meaningful learning. However, such an object can serve as support to succeed in the moment. How-to videos, job aids, and the like all can be used to achieve an outcome. And that’s just performance support!
What I think is the real untapped opportunity that could (and I say should) capture the moniker would be contextualized learning. Layering on a bit of learning because of when and where you are that develops you over time. It’s combining the two, potentially, so you help someone in the moment but add in the bit that also makes it a learning experience. There’s much more to this, but that’s the core idea.
My main issue here is that people are fast and loose with the term microlearning, and I’d like to make sure people are either talking about spaced learning or performance support (both good). And not talking about just breaking up a course into chunks that are nice to consume but not engineered to lead to retention and transfer (not so good). Of course, better yet if we converge on contextualized learning!
Last week, I gave a presentation to the local chapter of ATD. And I was surprised that their request was for mobile learning. Now that is something I can speak to, but given that my book on the topic came out seven years ago now, it seemed like a dated topic. And I was wrong. And the difference is between what’s possible and what’s practical.
Ok, so I am somewhat out ahead of the curve. My games book came out in 2005, but the market wasn’t quite ready. I similarly think my L&D revolution book, in 2014, was ahead of the market (the topic is finally getting more traction, close to four years later), though closer. But I thought the mlearning book was timely (not least because my publisher asked for it more than it was my initiative ;).
However, the audience was eager. And it was relatively large for the group. And it took a comment from the organizer to raise my awareness. He said (and I paraphrase): “you think that it’s old, but it’s not old for everyone”. And that was indeed a wakeup call. Because while mobile to me is very practical, for many it’s still possible.
I do tend to move on once I reckon I’ve figured something out. I’m interested when it’s still something to be understood or solved. Once I have my mind around it, my restless brain is on to something new. That’s why I have this blog, for instance, to wrestle with new thoughts. If they get organized enough, it becomes a presentation or even a book. (Though sometimes I do ones that are requested, e.g. my forthcoming one on myths, and I’m supposed to be reviewing the second round of proofs!)
But the interesting thing to me is to look beyond my own bubble (and what my colleagues are talking about). We’re looking at what’s possible but not yet done, or what’s on the horizon. Yet I need to remember to continue to tout what’s now on the menu, and recognize not everyone’s yet started moving. The things that I think are already practical to implement are still on the ‘possible’ list for others.
If you’re reading this blog, you’re probably with me, but feel free to let others know that the things in my past I’m still happy to help with! In any way: consulting or workshops or even speaking. For instance, I’ll be talking engagement for the Guild at Learning Solutions, and in a webinar for AECT’s Learner Engagement group. Just as I talk new things, like myths. What goes around comes around, I guess, and what’s been possible is now practical. Ask me how!
So, at the recent AECT 2017 conference, I participated in three ways that are worth noting. I had the honor of participating in two sessions based upon writings I’d contributed, and one based upon my own cogitations. I thought I’d share the thinking.
For my own presentation, I shared my efforts to move ‘rapid elearning’ forward. I put Van Merrienboer’s 4 Component ID and Guy Wallace’s Lean ISD as a goal, but recognized the need for intermediate steps like Michael Allen’s SAM, David Merrill’s ‘Pebble in a Pond‘, and Cathy Moore’s Action Mapping. I suggested that these might be too far, and want steps that might be slight improvements on their existing processes. These included three thing: heuristics, tools, and collaboration. Here I was indicating specifics for each that could move from well-produced to well-designed.
In short, I suggest that while collaboration is good, many corporate situations want to minimize staff. Consequently, I suggest identifying those critical points where collaboration will be useful. Then, I suggest short cuts in processes to the full approach. So, for instance, when working with SMEs focus on decisions to keep the discussion away from unnecessary knowledge. Finally, I suggest the use of tools to support the gaps our brain architectures create. Unfortunately, the audience was small (27 parallel sessions and at the end of the conference) so there wasn’t a lot of feedback. Still, I did have some good discussion with attendees.
Then, for one of the two participation session, the book I contributed to solicited a wide variety of position papers from respected ed tech individuals, and then solicited responses to same. I had responded to a paper suggesting three trends in learning: a lifelong learning record system, a highly personalized learning environment, and expanded learner control of time, place and pace of instruction. To those 3 points I added two more: the integration of meta-learning skills and the breakdown of the barrier between formal learning and lifelong learning. I believe both are going to be important, the former because of the decreasing half-life of knowledge, the latter because of the ubiquity of technology.
Because the original author wasn’t present, I was paired for discussion with another author who shares my passion for engaging learning, and that was the topic of our discussion table. The format was fun; we were distributed in pairs around tables, and attendees chose where to sit. We had an eager group who were interested in games, and my colleague and I took turns answering and commenting on each other’s comments. It was a nice combination. We talked about the processes for design, selling the concept, and more.
For the other participation session, the book was a series of monographs on important topics. The discussion chose a subset of four topics: MOOCs, Social Media, Open Resources, and mLearning. I had written the mLearning chapter. The chapter format included ‘take home’ lessons, and the editor wanted our presentations to focus on these. I posited the basic mindshifts necessary to take advantage of mlearning. These included five basic principles:
The sessions were fun, and the feedback was valuable.
Perhaps inspired by Apple’s focus on Augmented Reality (AR), I thought I’d take a stab at conveying the types of things that could be done to support both learning and performance. I took a sample of some of my photos and marked them up. I’m sure there’s lots more that could be done (there were some great games), but I’m focusing on simple information that I would like to see. It’s mocked up (so the arrows are hand drawn), so understand I’m talking concept here, not execution!
Here, I’m starting small. This is a photo I took of a flower on a walk. This is the type of information I might want while viewing the flower through the screen (or glasses). The system could tell me it’s a tree, not a bush, technically (thanks to my flora-wise better half). It could also illustrate how large it is. Finally, the view could indicate that what I’m viewing is a magnolia (which I wouldn’t have known), and show me off to the right the flower bud stage.
The point is that we can get information around the particular thing we’re viewing. I might not actually care about the flower bud, so that might be filtered out, and it might instead talk about any medicinal uses. Also, it could be dynamic, animating the process of going from bud to flower and falling off. It could also talk about the types of animals (bees, hummingbirds, ?) that interact with it, and how. It would be dependent on what I want to learn. And, perhaps, with some additional incidental information on the periphery of my interests, for serendipity.
Going wider, here I’m looking out at a landscape, and the overlay is providing directions. Downtown is straight ahead, my house is over that ridge, and infamous Mt. Diablo is off to the left of the picture. It could do more, pointing out that the green ridges are grapes, provide the name of the neighborhood that’s in the foreground (I call it Stepford Downs, after the movie ;).
Dynamically, of course, if I moved the camera to the left, Mt. Diablo would get identified when it sprung into view. As we moved around, we’d point to the neighboring towns in view, and in the direction of further towns blocked by mountain ranges. We should or could also identify the river flowing past to the north. And we could instead focus on other information: infrastructure (pipes and electricity), government boundaries, whatever’s relevant could be filtered in or out.
And in this final example, taken from the car on a trip, AR might indicate some natural features. Here I’ve pointed to the clouds (and indicated the likelihood of rain). Similarly, I’ve identified the rock and the mechanism of shaping. (These are all made up, they could be wrong; Mt Faux definitely is!) We might even be able to touch on a label and have it expand.
Similarly, as we moved, information would change as we viewed different areas. We might even animate what the area looked like hundreds of thousands of years ago and how it’s changed. Or we could illustrate coming changes. It could instead show boundaries of counties or parks, types of animals, or other relevant information.
The point here is that annotating the world, a capability AR has, can be an amazing learning tool. If I can specify my interests, we can capitalize on them to develop. And this is as an adult. Think about doing this for kids, layering on information in their Zone of Proximal Development and interests! I know VR’s cool, and has real learning potential, but there you have to create the context. Here we’re taking advantage of it. That may be harder, but it’s going to have some real upsides when it can be done ubiquitously.
Augmented Reality (AR) is on the upswing, and I think this is a good thing. I think AR makes sense, and it’s nice to see both solid tool support and real use cases emerging. Here’s the news, but first, a brief overview of why I like AR.
As I’ve noted before, our brains are powerful, but flawed. As with any architecture, any one choice will end up with tradeoffs. And we’ve traded off detail for pattern-matching. And, technology is the opposite: it’s hard to get technology to do pattern matching, but it’s really good at rote. Together, they’re even more powerful. The goal is to most appropriately augment our intellect with technology to create a symbiosis where the whole is greater than the sum of the parts.
Which is why I like AR: it’s about annotating the world with information, which augments it to our benefit. It’s contextual, that is, doing things because of when and where we are. AR augments sensorily, either auditory or visual (or kinesthetic, e.g. vibration). Auditory and kinesthetic annotation is relatively easy; devices generate sounds or vibrations (think GPS: “turn left here”). Non-coordinated visual information, information that’s not overlaid visually, is presented as either graphics or text (think Yelp: maps and distances to nearby options). Tools already exist to do this, e.g. ARIS. However, arguably the most compelling and interesting is the aligned visuals.
Google Glass was a really interesting experiment, and it’s back. The devices – glasses with camera and projector that can present information on the glass – were available, but didn’t do much because of where you were looking. There were generic heads-up displays and camera, but little alignment between what was seen and what was consequently presented to the user with additional information. That’s changed. Google Glass has a new Enterprise Edition, and it’s being used to meet real needs and generate real outcomes. Glasses are supporting accurate placement in manufacturing situations requiring careful placement. The necessary components and steps are being highlighted on screen, and reducing errors and speeding up outcomes.
And Apple has released it’s Augmented Reality software toolkit, ARKit, with features to make AR easy. One interesting aspect is built-in machine learning, which could make aligning with objects in the world easy! Incompatible platforms and standards impede progress, but with Google and Apple creating tools for each of their platforms, development can be accelerated. (I hope to find out more at the eLearning Guild’s Realities 360 conference.)
While I think Virtual Reality (VR) has an important role to play for deep learning, I think contextual support can be a great support for extending learning (particularly personalization), as well as performance support. That’s why I’m excited about AR. My vision has been that we’ll have a personal coaching system that will know where and when we are and what our goals are, and be able to facilitate our learning and success. Tools like these will make it easier than ever.