Maxwell Planck opened the eLearning Guild’s Realities 360 conference with a thoughtful and thought-provoking talk on VR. Reflecting on his experience in the industry, he described the transition from story telling to where he thinks we should go: social adventure. (I want to call it “adventure together”. :). A nice start to the event.
Just what is the Future of Work about? Is it about new technology, or is it about how we work with people? We’re seeing amazing new technologies: collaboration platforms, analytics, and deep learning. We’re also hearing about new work practices such as teams, working (or reflecting) out loud, and more. Which is it? And/or how do they relate?
It’s very clear technology is changing the way we work. We now work digitally, communicating and collaborating. But there’re more fundamental transitions happening. We’re integrating data across silos, and mining that data for new insights. We can consolidate platforms into single digital environments, facilitating the work. And we’re getting smart systems that do things our brains quite literally can’t, whether it’s complex calculations or reliable rote execution at scale. Plus we have technology-augmented design and prototyping tools that are shortening the time to develop and test ideas. It’s a whole new world.
Similarly, we’re seeing a growing understanding of work practices that lead to new outcomes. We’re finding out that people work better when we create environments that are psychologically safe, when we tap into diversity, when we are open to new ideas, and when we have time for reflection. We find that working in teams, sharing and annotating our work, and developing learning and personal knowledge mastery skills all contribute. And we even have new practices such as agile and design thinking that bring us closer to the actual problem. In short, we’re aligning practices more closely with how we think, work, and learn.
Thus, either could be seen as ‘the Future of Work’. Which is it? Is there a reconciliation? There’s a useful way to think about it that answers the question. What if we do either without the other?
If we use the new technologies in old ways, we’ll get incremental improvements. Command and control, silos, and transaction-based management can be supported, and even improved, but will still limit the possibilities. We can track closer. But we’re not going to be fundamentally transformative.
On the other hand, if we change the work practices, creating an environment where trust allows both safety and accountability, we can get improvements whether we use technology or not. People have the capability to work together using old technology. You won’t get the benefits of some of the improvements, but you’ll get a fundamentally different level of engagement and outcomes than with an old approach.
Together, of course, is where we really want to be. Technology can have a transformative amplification to those practices. Together, as they say, the whole is greater than the some of the parts.
I’ve argued that using new technologies like virtual reality and adaptive learning only make sense after you first implement good design (otherwise you’re putting lipstick on a pig, as the saying goes). The same is true here. Implementing radical new technologies on top of old practices that don’t reflect what we know about people, is a recipe for stagnation. Thus, to me, the Future of Work starts with practices that align with how we think, work, and learn, and are augmented with technology, not the other way around. Does that make sense to you?
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.
If you follow this blog (and you should :), it was pretty obvious that I was at the FocusOn Learning conference in San Diego last week (previous 2 posts were mindmaps of the keynotes). And it was fun as always. Here are my reflections on what happened a bit more, as an exercise in meta-learning.
There were three themes to the conference: mobile, games, and video. I’m pretty active in the first two (two books on the former, one on the latter), and the last is related to things I care and talk about. The focus led to some interesting outcomes: some folks were very interested in just one of the topics, while others were looking a bit more broadly. Whether that’s good or not depends on your perspective, I guess.
Mobile was present, happily, and continues to evolve. People are still talking about courses on a phone, but more folks were talking about extending the learning. Some of it was pretty dumb – just content or flash cards as learning augmentation – but there were interesting applications. Importantly, there was a growing awareness about performance support as a sensible approach. It’s nice to see the field mature.
For games, there were positive and negative signs. The good news is that games are being more fully understood in terms of their role in learning, e.g. deep practice. The bad news is that there’s still a lot of interest in gamification without a concomitant awareness of the important distinctions. Tarting up drill-and-kill with PBL (points, badges, and leaderboards; the new acronym apparently) isn’t worth significant interest! We know how to drill things that must be, but our focus should be on intrinsic interest.
As a side note, the demise of Flash has left us without a good game development environment. Flash is both a development environment and a delivery platform. As a development environment Flash had a low learning threshold, and yet could be used to build complex games. As a delivery platform, however, it’s woefully insecure (so much so that it’s been proscribed in most browsers). The fact that Adobe couldn’t be bothered to generate acceptable HTML5 out of the development environment, and let it languish, leaves the market open for another accessible tool. And Unity or Unreal provide good support (as I understand it), but still require coding. So we’re not at an easily accessible place. Oh, for HyperCard!
Most of the video interest was either in technical issues (how to get quality and/or on the cheap), but a lot of interest was also in interactive video. I think branching video is a real powerful learning environment for contextualized decision making. As a consequence the advent of tools that make it easier is to be lauded. An interesting session with the wise Joe Ganci (@elearningjoe) and a GoAnimate guy talked about when to use video versus animation, which largely seemed to reflect my view (confirmation bias ;) that it’s about whether you want more context (video) or concept (animation). Of course, it was also about the cost of production and the need for fidelity (video more than animation in both cases).
There was a lot of interest in VR, which crossed over between video and games. Which is interesting because it’s not inherently tied to games or video! In short, it’s a delivery technology. You can do branching scenarios, full game engine delivery, or just video in VR. The visuals can be generated as video or from digital models. There was some awareness, e.g. fun was made of the idea of presenting powerpoint in VR (just like 2nd Life ;).
I did an ecosystem presentation that contextualized all three (video, games, mobile) in the bigger picture, and also drew upon their cognitive and then L&D roles. I also deconstructed the game Fluxx (a really fun game with an interesting ‘twist’). Overall, it was a good conference (and nice to be in San Diego, one of my ‘homes’).
After yesterday’s rant about problems in local schools, I was presented with a recent New York Times article. In it, they talked about how the tech industry was getting involved in schools. And while the initiatives seem largely well-intentioned, they’re off target. There’s a lack of awareness of what meaningful learning is, and what meaningful outcomes could and should be. And so it’s time to shed a little clarity.
Tech in schools is nothing new, from the early days of Apple and Microsoft vying to provide school computers and getting a leg up on learners’ future tech choices. Now, however, the big providers have even more relative leverage. School funds continue to be cut, and the size of the tech companies has grown relative to society. So there’s a lot of potential leverage.
One of the claims in the article is that the tech companies are able to do what they want, and this is a concern. They can dangle dollars and technology as bait and get approval to do some interesting and challenging things.
However, some of the approaches have issues beyond the political:
One approach is to teach computer science to every student. The question is: is this worth it? Understanding what computers do well (and easily), and perhaps more importantly what they don’t, is necessary, no argument. The argument for computer programming is that it teaches you to break down problems and design solutions. But is computer science necessary? Could it be done with, say, design thinking? Again, all for helping learners acquire good problem-solving skills. But I’m not convinced that this is necessarily a good idea (as beneficial as it is to the tech industry ;).
Another initiative is using algorithms, rules like the ones that Facebook uses to choose what ads to show you, to sequence math. A program, ALEKS, already did this, but this one mixes in gamification. And I think it’s patching a bad solution. For one, it appears to be using the existing curriculum, which is broken (too much rote abilities, too little transferable skills). And gamification? Can’t we, please, try to make math intrinsically interesting by making it useful? Abstract problems don’t help. Drilling key skills is good, but there are nuances in the details.
A second approach has students choosing the problems they work on, and teachers being facilitators. Of course, I’m a fan of this; I’ve advocated for gradually handing off control of learning to learners, to facilitate their development of self-learning. And in a recently-misrepresented announcement, Finland is moving to topics with interleaved skills rapped around them (e.g. not one curricula, but you might intersect math and chemistry in studying ecosystems. However, this takes teachers with skills across both domains, and the ability to facilitate discussion around projects. That’s a big ask, and has been a barrier to many worthwhile initiatives. Compounding this is that the end of a unit is assessed by a 10-point multiple choice question. I worry about the design of those assessments.
I’m all for school reform. As Mark Warschauer put it, the only things wrong with American education is the curriculum, the pedagogy, and the way we use technology. I think the pedagogy being funded in the latter description is a good approach, but there are details that need to be worked out to make it a scalable success. And while problem-solving is a good curricular goal, we need to be thoughtful about how we build it in. Further, motivation is an important component about learning, but intrinsic or extrinsic?
We really could stand to have a deeper debate about learning and how technology can facilitate it. The question is: how do we make that happen?
This is a rant, but it’s coupled with lessons.
I’ve been away, and one side effect was a lack of internet bandwidth at the residence. In the first day I’d used up a fifth of the allocation for the whole time (> 5 days)! So, I determined to do all I could to cut my internet usage while away from the office. The consequences of that have been heinous, and on the principle of “it’s ok to lose, but don’t lose the lesson”, I want to share what I learned. I don’t think it was evil, but it well could’ve been, and in other instances it might be.
So, to start, I’m an Apple fan. It started when I followed the developments at Xerox with SmallTalk and the Alto as an outgrowth of Alan Kay‘s Dynabook work. Then the Apple Lisa was announced, and I knew this was the path I was interested in. I did my graduate study in a lab that was focused on usability, and my advisor was consulting to Apple, so when the Mac came out I finally justified a computer to write my PhD thesis on. And over the years, while they’ve made mistakes (canceling HyperCard), I’ve enjoyed their focus on making me more productive. So when I say that they’ve driven me to almost homicidal fury, I want you to understand how extreme that is!
I’d turned on iCloud, Apple’s cloud-based storage. Innocently, I’d ticked the ‘desktop/documents’ syncing (don’t). Now, with every other such system that I know of, it’s stored locally *and* duplicated on the cloud. That is, it’s a backup. That was my mental model. And that model was reinforced: I’d been able to access my files even when offline. So, worried about the bandwidth of syncing to the cloud, I turned it off.
When I did, there was a warning that said something to the effect of: “you’ll lose your desktop/documents”. And, I admit, I didn’t interpret that literally (see: model, above). I figured it would disconnect their syncing. Or I’d lose the cloud version. Because, who would actually steal the files from your hard drive, right?
Well, Apple DID! Gone. With an option to have them transferred, but….
I turned it back on, but didn’t want to not have internet, so I turned it off again but ticked the box that said to copy the files to my hard drive. COPY BACK MY OWN @##$%^& FILES! (See fury, above.) Of course, it started, and then said “finishing”. For 5 days! And I could see that my files weren’t coming back in any meaningful rate. But there was work to do!
The support guy I reached had some suggestion that really didn’t work. I did try to drag my entire documents folder from the iCloud drive to my hard drive, but it said it was making the estimate of how long, and hung on that for a day and a half. Not helpful.
In meantime, I started copying over the files I needed to do work. And continuing to generate the new ones that reflected what I was working on. Which meant that the folders in the cloud, and the ones on my hard drive that I had copied over, weren’t in sync any longer. And I have a lot of folders in my documents folder. Writing, diagrams, client files, lots of important information!
I admit I made some decisions in my panic that weren’t optimal. However, after returning I called Apple again, and they admitted that I’d have to manually copy stuff back. This has taken hours of my time, and hours yet to go!
So, there are several learnings from this. First, this is bad design. It’s frankly evil to take someone’s hard drive files after making it easy to establish the initial relationship. Now, I don’t think Apple’s intention was to hurt me this way, they just made a bad decision (I hope; an argument could be made that this was of the “lock them in and then jack them up” variety, but that’s contrary to most of their policies so I discount it). Others, however, do make these decisions (e.g. providers of internet and cable from whom you can only get a 1 or 2 year price which will then ramp up and unless you remember to check/change, you’ll end up paying them more than you should until you get around to noticing and doing something about it). Caveat emptor.
Second, models are important and can be used for or against you. We do create models about how things work and use evidence to convince ourselves of their validity (with a bit of confirmation bias). The learning lesson is to provide good models. The warning is to check your models when there’s a financial stake that could take advantage of them for someone else’s gain!
And the importance of models for working and performing is clear. Helping people get good models is an important boost to successful performance! They’re not necessarily easy to find (experts don’t have access to 70% of what they do), but there are ways to develop them, and you’ll be improving your outcomes if you do.
Finally, until Apple changes their policy, if you’re a Mac and iCloud user I strongly recommend you avoid the iCloud option to include Desktop and Documents in the cloud unless you can guarantee that you won’t have a bandwidth blockage. I like the idea of backing my documents to the cloud, but not when I can’t turn it off without losing files. It’s a bad policy that has unexpected consequences to user expectations, and frankly violates my rights to my data.
We now return you to our regularly scheduled blog topics.
As I continue to track what’s happening, I get the opportunity to review a wide number of products and services. While tracking them all would be a full-time job, occasionally some offer new ideas. Here’s a collection of those that have piqued my interest of late:
Sisters eLearning: these folks are taking a kinder, gentler approach to their products and marketing their services. Their signature offering is a suite of templates for your elearning featuring cooperative play. Their approach in their custom development is quiet and classy. This is reflected in the way they promote themselves at conferences: they all wear mauve polos and sing beautiful a capella. Instead of giveaways, they quietly provide free home-baked mini-muffins for all.
Yalms: these folks are offering the ‘post-LMS’. It’s not an LMS, and instead offers course management, hosting, and tracking. It addresses compliance, and checks a whole suite of boxes such as media portals, social, and many non-LMS things including xAPI. Don’t confuse them with an LMS; they’re beyond that!
MicroBrain: this company has developed a system that makes it easy to take your existing courses and chunk them up into little bits. Then it pushes them out on a schedule. It’s a serendipity model, where there’s a chance it just might be the right bit at the right time, which is certainly better than your existing elearning. Most importantly, it’s mobile!
OffDevPeeps: these folks a full suite of technology development services including mobile, AR, VR, micro, macro, long, short, and anything else you want, all done at a competitive cost. If you are focused on the ‘fast’ and ‘cheap’ side of the trilogy, these are the folks to talk to. Coming soon to an inbox near you!
DanceDanceLearn: provides a completely unique offering. They have developed an authoring tool that makes it easy for you to animate dancers moving in precise formations that spell out content. They also have a synchronized swimming version. Your content can be even more engaging!
There, I hope you’ll find these of interest, and consider checking them out.
Any relation between the companies portrayed and real entities is purely coincidental. #couldntstopmyself #allinfun
I recently came across a document (PDF) about disruptive innovation based upon Clayton Christensen’s models, which I’d heard about but hadn’t really penetrated. This one was presented around higher education innovation (a topic I’ve some familiarity with ;), so it provided a good basis for me to explore the story. It had some interesting features that are worth portraying, and then some implications for my thoughts on innovation, so I thought I’d share.
The model’s premise is that disruption requires two major things: a technology enabler and a business model innovation. That is, there has to be a way to deliver this new advance, and it has to be coupled with a way to capitalize on the benefits. It can’t just be a new technology in an existing business model, as that’s merely the traditional competitive innovation. Similarly, a new business model around existing technology is still within competitive advancement.
A related requirement is to have a new entity ready to capitalize. This quote captured me: “In those few instances in which the leader in one generation became the leader in the next disruptive one, the company did so by setting up a completely autonomous business unit…” You can’t do disruption from inside the game. Even if you’re a player, you have to liberate resources to start anew.
Which is quite different than most innovation. Typical innovation is ‘within the box’. This comes from having an environment where people can experiment, share, be exposed to new ideas, and allowing it to incubate (ferment/percolate) over time. And this is a good thing. Disruptive innovation makes new industries, new companies, etc. And that’s also good (except, perhaps, for the disrupted). The point being that both innovations are valuable, but different.
It’s not clear to me what happens when an internal innovation comes up with an idea that’s really disruptive. Clearly, if the idea clears the hurdles of complacency and inertia, you’d probably want to spin it off. But most innovations just need a fair airing and trialing to get traction (though depending on scope, a bit of change management might be useful).
I encourage innovation, and creating the environment where it can happen. It’s valuable even in established businesses, and a fair bit is known about how to create an environment where it can flourish. So, what can we innovate about innovation?
A colleague recently asked (in general, not me specifically) whether there’s a role for LMS functions. Her query was about the value of having a place to see (recommended) courses, to track your development, etc. And that led me to ponder, and here’s my thinking:
My question is where to draw the line. Should you do social learning in the LMS version of that, or have a separate system? If using the LMS for social around courses (a good thing), how do you handle the handoff to the social tool used for teams and communities? It would seem to make sense to use the regular tool in the courses as well, to make it part of the habit.
Similarly, should you host non-course resources in the LMS or out in a portal (which is employee-focused, not siloed)? Maybe the courses also make more sense in the portal, tracked with xAPI? I think I’d like to track self-learning, via accessing videos and documents the same as I would formal learning with courses: I want to be able to correlate them with business to test the outputs of experiments in changes.
Again, how should I be handling signups for things? I handle signups for all sorts of things via tools like Eventbrite. Is asking to signup for a training, with a waiting list, different than other events such as a team party?
Now, for representing your learning, is that an LMS role, or an LRS dashboard, or…? From a broader perspective, is it talent management or performance management or…?
I’m not saying an LMS doesn’t make sense, but it seems like it’s a minor tool at best, not the central organizing function. I get that it’s not a learning management system, but a course management system, but is that the right metaphor? Do we want a learning tracking system instead, and is that what an LMS if or could be for?
When we start making a continuum between formal and informal learning, what’s the right suite of tools? I want to find courses and other things through a federated search of *all* resources. And I want to track many things besides course completions, because those courses should have real world-related assignments, so they’re tracked as work, not learning. Or both. And I want to track things that we’re developing through coaching, or continuing development through coaching and stretch assignments. Is that an LMS, or…?
I have no agenda to put the LMS out of business, as long as it makes sense in modern workplace learning. However, we want to use the right tool for the right job, and create an ecosystem that supports us doing the right thing. I don’t have an obvious answer, I’m just trying on a rethink (yes, thinking out loud ;), and wondering what your thoughts are. So, what is the right way to think about this? Do you see a uniquely valuable aggregation of services that makes sense? (And I may have to dig in deeper and think about the essential components and map them out, then we can determine what the right suites of functions are to fulfill those needs.)
In my inbox was an announcement about a new white paper with the intriguing title Human Learning is About to Change Forever. So naturally I gave up my personal details to download a copy. There are nine claims in the paper, from the obvious to the ridiculous. So I thought I’d have some fun.
First, let’s get clear. Our learning runs on our brain, our wetware. And that’s not changing in any fundamental way in the near future. As a famous article once had it: phenotypic plasticity triumphs over genotypic plasticity (in short, our human advantage has gained via our ability to adapt individually and learn from each other, not through species evolution). The latter takes a long time!
And as a starting premise, the “about to” bit implies these things are around the corner, so that’s going to be a bit of my critique. But nowhere near all of it. So here’s a digest of the nine claims and my comments:
Overall, this is reads like more a sci-fi fan’s dreams than a realistic assessment of what we should be preparing for. No, human learning isn’t going to change forever. The ways we learn, e.g. the tools we learn with are changing, and we’re rediscovering how we really learn.
There are better guides available to what’s coming in the near term that we should prepare for. Again, we need to focus on good learning design, and leveraging technology in ways that align with how our brains work, not trying to meld the two. So, there’re my opinions, I welcome yours.