Tom Wujec gave a discursive and well illustrated talk about how changes in technology were changing industry, ultimately homing in on creativity. Despite a misstep mentioning Kolb’s invalid learning styles instrument, it was entertaining and intriguing.
A couple of times last year, firms with some exciting learning tools approached me to talk about the market. And in both cases, I had to advise them that there were some barriers they’d have to address. That was brought home to me in another conversation, and it makes me worry about the state of our industry.
So the first tool is based upon a really sound pedagogy that is consonant with my activity-based learning approach. The basis is giving learners assignments very much like the assignments they’ll need to accomplish in the workplace, and then resourcing them to succeed. They wanted to make it easy for others to create these better learning designs (as part of a campaign for better learning). The only problem was, you had to learn the design approach as well as the tool. Their interface wasn’t ready for prime time, but the real barrier was getting people to be able to use a new tool. I indicated some of the barriers, and they’re reconsidering (while continuing to develop content against this model as a service).
The second tool supports virtual role plays in a powerful way, having smart agents that react in authentic ways. And they, too, wanted to provide an authoring tool to create them. And again my realistic assessment of the market was that people would have trouble understanding the tool. They decided to continue to develop the experiences as a service.
Now, these are somewhat esoteric designs, though the former should be the basis of our learning experiences, and the latter would be a powerful addition to support a very common and important type of interaction. The more surprising, and disappointing, issue came up with a conversation earlier this year with a proponent of a more familiar tool.
Without being specific (I’ve not received permission to disclose the details in all of the above), this person indicated that when training a popular and fairly straightforward tool, that the biggest barrier wasn’t the underlying software model. I was expecting that too much of training was based upon rote assignments without an underlying model, and that is the case, but instead there was a more fundamental barrier: too many potential users just didn’t have sufficient computer skills! And I’m not talking about programming code, but instead fundamental understandings of files and ‘styles‘ and other core computing elements just were not present in sufficient quantities in these would-be authors. Seriously!
Now I’ve complained before that we’re not taking learning design seriously, but obviously we’re compounded by a lack of fundamental computer skills. Folks, this is elearning, not chalk learning, not chalk talk, not edoing, etc. If you struggle to add new apps on your computer, or find files, you’re not ready to be an elearning developer.
I admit that I struggle to see how folks can assume that without knowledge of design, nor knowledge of technology, that they can still be elearning designers and developers. These tools are scaffolding to allow your designs to be developed. They don’t do design, nor will they magically cover up for lacks of tech literacy.
So, let’s get realistic. Learn about learning design, and get comfortable with tech, or please, please, don’t do elearning. And I promise not to do music, architecture, finance, and everything else I’m not qualified to. Fair enough?
The other day, I was wondering about the possibilities of removing mandatory courses. Ok, maybe not mandated compliance, but any others. And then a colleague took it further, and I like it. So what are we talking about?
I was thinking that, if you give people a meaningful mission (ala Dan Pink’s Drive), the learner (assuming reasonable self-learning skills, a separate topic), they would take responsibility for the learning they needed. We could have courses around, or maybe await their desires and point them to outside resources, etc, unless it’s specifically internal. That is, we become much more pull (from the user) than push (from us).
However, my colleague Mark Britz took it further. He argued that instead of not making them go, instead we’d charge them what it cost to provide the learning! That is, if folks wanted training or webinars or…, they’d pay for the privilege. As he put it, if requests for elearning, being cautious about signing up, etc happened: “I couldn’t be happier!”
His point is that it would drive people to more workflow learning, more social and shared learning, etc. And that’s a good thing. I might couple that with some way to make sure they knew how to work, play, and learn well together, but it’s the different view that’s a needed jumpstart.
It’s a refreshing twist on the ‘if we build it it is good’ sort of mentality, and really helps focus the L&D unit on doing things that will significantly improve outcomes for others. If you can make a meaningful impact, people will have to pay for your assistance. You want change? You’ll pay but it’ll be worth it.
If we’re going to kick off a revolution, we need to rethink what we’re about and how we’re doing it. Mark’s upended view is a necessary kick in the status quo to get us to think anew about what we’re doing and why.
I recommend you read his original post.
A couple of weeks ago, I was riffing on sensors: how mobile devices are getting equipped with all sorts of new sensors and the potential for more and what they might bring. As part of that discussion was a brief mention of sensor nets, how aggregating all this data could be of interest too. And low and behold, a massive example was revealed last week.
The context was the ‘spring forward’ event Apple held where they announced their new products. The most anticipated one was the Apple Watch (which was part of the driving behind my post on wearables), the new iConnected device for your wrist. The second major announcement was their new Macbook, a phenomenally thin new laptop with some amazing specs on weight and screen display, as well as some challenging tradeoffs.
One announcement that was less noticed was the announcement of a new research endeavor, but I wonder if it isn’t the most game-changing element of them all. The announcement was ResearchKit, and it’s about sensor nets.
So, smartphones have lots of sensors. And the watch will have more. They can already track a number of parameters about you automatically, such as your walking. There can be more, with apps that can ask about your eating, weight, or other health measurements. As I pointed out, aggregating data from sensors could do things like identify traffic jams (Google Maps already does this), or collect data like restaurant ratings.
What Apple has done is to focus specifically on health data from their HealthKit, and partner with research hospitals. What they’re saying to scientists is “we’ll give you anonymized health data, you put it to good use”. A number of research centers are on board, and already collecting data about asthma and more. The possibility is to use analytics that combine the power of large numbers with a bunch of other descriptive data to be able to investigate things at scale. In general, research like this is hard since it’s hard to get large numbers of subjects, but large numbers of subjects is a much better basis for study (for example, the China-Cornell-Oxford Project that was able to look at a vast breadth of diet to make innovative insights into nutrition and health).
And this could be just the beginning: collecting data en masse (while successfully addressing privacy concerns) can be a source of great insight if it’d done right. Having devices that are with you and capable of capturing a variety of information gives the opportunity to mine that data for expected, and unexpected, outcomes.
A new iDevice is always cool, and while it’s not the first smart watch (nor was the iPhone the first smartphone, the iPad not the first tablet, nor the iPod the first music play), Apple has a way of making the experience compelling. Like with the iPad, I haven’t yet seen the personal value proposition, so I’m on the fence. But the ability to collect data in a massive way that could support ground-breaking insights and innovations in medicine? That has the potential for affecting millions of people around the world. Now that is impact.
There’s been quite a bit of flurry about Design Thinking of late (including the most recent #lrnchat), and I’m trying to get my around what’s unique about it. The wikipedia entry linked above helps clarify the intent, but is there any there there?
It helps to understand that I’ve been steeped in design approaches since at least the 80’s. Herb Simon’s Sciences of the Artificial argued, essentially, that design is the quintessential human activity. And my grad school experience was in a research lab focused on interface design. Process was critical, and when I was subsequently teaching interface design, I was tracking new initiatives like situated design and participatory design, anthropological efforts designed to get closer to the ‘customer’.
In addition to being somewhat obsessive about learning how people learn, and as a confirmed geek continually exploring new technology, I also got interested in design processes beyond interface design. As my passion was designing learning technology solutions to meet real needs, I explored other design approaches to look for universals. Along the way I looked at industrial, graphic, architectural, software, and other design disciplines. I also read the psychological research on our cognitive limitations and design approaches. (I made a small bit of my career on bringing the advances in HCI, which was more advanced in process, to ed tech.)
The reason I mention this is that the elements of Design Thinking: being open minded, diverging before converging, using teams, empathy for the customer, etc, all strike me as just good design. It’s not obvious to me whether it gets into the nuances (e.g. the steps in the Wikipedia article don’t allow me to see whether they do things like ensure that everyone takes time to brainstorm on their own before coming together; an important step to prevent groupthink), but at the granularity I’ve seen, it seems to be quite good. You mean everyone isn’t already both aware of and using this? Apparently not.
So in that respect, Design Thinking is a win. If adding a label to a systematized compendium of good practices will raise awareness, I’m all for it. And I’m willing to have my consciousness raised that there’s more to it, because as a proponent of design, I’m glad to see that folks are taking steps to help design get better and will be thrilled if it adds something new.
Well, some more travels are imminent, so I thought I’d update you on where the Quinnovation road show would be on tour this spring:
So, if you’re at one of these, do come up and introduce yourself and say hello!
I’m a big fan of the mantras of (variously) ‘show your work‘ or ‘working out loud‘. I think that the notion of showing what you’re doing helps other work with you to make it better, or learn from you if you do well. This contributes to the success of the ‘coherent organization‘, where information flows in ways that are aligned with the goals of the organization. But I want to extend it a bit.
Let me use an analogy: remember when your teacher asked you to ‘show your work’? It wasn’t just the product, but the intermediate steps, and I’m sure that’s what Jane Bozarth is implying. But it’s too easy for people to think it’s about making your work product available instead of one that’s marked up with the underlying thinking. In user interface work it was known as ‘design rationale’, where you kept a track of the assumptions and decisions along the way.
I’ve termed this ‘cognitive annotation’ at various points (what, me create new phrases?). And it’s really important for a number of reasons:
I have a couple of guilty pleasures that make this point quite clearly. Lee Child is a writer who has a character called Jack Reacher (hence the movie, pretty entertaining despite the wrong physical type to play the lead role). This character is ex-military police and quite capable in challenging situations. What makes this series more than usually interesting is that the character regularly outlines the situation, the thinking behind it, and the resulting actions taken. In doing so, it’s often a format like “most people think X, but because of Y, Z is a better choice”.
Another place this shows up is the recently finished television series Burn Notice. In this case, a ‘burned’ spy is forced to freelance, and regularly gets in situations where again, the conventional wisdom is debunked. With a regular approach of a ‘sting’, along with a dry humor and some larger-than-life characters, it’s fun, and interesting because of the underlying thinking that explains the choices made.
Granted, neither of these are situations I have any interest in being in, but it’s a nice twist and makes the stories more interesting.
In the real world, it can be hard to share underlying thinking if it’s a Miranda organization, but the benefits suggest that the effort to achieve a culture where such openness is ‘safe’ is a worthwhile endeavor. At least, that’s my thinking.
#itashare
Someone tweeted about their mobile learning credo, and mentioned the typical ‘mlearning is elearning, extended’ view. Which I rejected, as I believe mlearning is much more (and so should elearning be). And then I thought about it some more. So I’ll lay out my thinking, and see what you think.
I have been touting that mLearning could and should be focused, as should P&D, on anything that helps us achieve our goals better. Mobile, paper, computers, voodoo, whatever technology works. Certainly in organizations. And this yields some interesting implications.
So, for instance, this would include performance support and social networks. Anything that requires understanding how people work and learn would be fair game. I was worried about whether that fit some operational aspects like IT and manufacturing processes, but I think I’ve got that sorted. UI folks would work on external products, and any internal software development, but around that, helping folks use tools and processes belongs to those of us who facilitate organizational performance and development. So we, and mlearning, are about any of those uses.
But the person, despite seeming to come from an vendor to orgs, not schools, could be talking about schools instead, and I wondered whether mLearning for schools, definitionally, really is about only supporting learning. And I can see the case for that; that mlearning in education is about using mobile to help people learn, not perform. It’s about collaboration, for sure, and tools to assist.
Note I’m not making the case for schools as they are, a curriculum rethink definitely needs to accompany using technology in schools in many ways. Koreen Pagano wrote this nice post separating Common Core teaching versus assessment, which goes along with my beliefs about the value of problem solving. And I also laud Roger Schank‘s views, such as the value (or not) of the binomial theorem as a classic example.
But then, mobile should be a tool in learning, so it can work as a channel for content, but also for communication, and capture, and compute (e.g. the 4C’s of mlearning). And the emergent capability of contextual support (the 5th C, e.g. combinations of the first four). So this view would argue that mlearning can be used for performance support in accomplishing a meaningful task that’s part of an learning experience.
That would take me back to mlearning being more than just mobile elearning, as Jason Haag has aptly separated. Sure, mobile elearning can be a subset of mlearning, but not the whole picture. Does this make sense to you?
I recently wrote about wearables, where I focused on form factor and information channels. An article I recently read talked about a guy who builds spy gear, and near the end he talked about some things that started me thinking about an extension of that for all mobile, not just wearables. The topic is sensors.
In the article, he talks about how, in the future, glasses could detect whether you’ve been around bomb-making materials:
“You can literally see residue on someone if your glasses emit a dozen different wavelengths of microlasers that illuminate clothing in real time and give off a signature of what was absorbed or reflected.”
That’s pretty amazing, chemical spectrometry on the fly. He goes on to talk about distance vision:
“Imagine you have a pair of glasses, and you can just look at a building 50 feet away, 100 feet away, and look right through the building and see someone moving around.”
Now, you might nor might not like what he’s doing with that, but imagine applying it elsewhere: identifying where people are for rescue, or identifying materials for quality control.
Heck, I’d find it interesting just to augment the camera with infrared and ultraviolet: imagine being able to use the camera on your phone or glasses to see what’s happening at night, e.g. wildlife (tracking coyotes or raccoons, and managing to avoid skunks!). Night vision, and seeing things that fluoresce under UV would both be really cool additions.
I’d be interested too in having them able to work to enlarge as well, bring small things to light like a magnifying glass or microscope.
It made me think about all the senses we could augment. I was thinking about walking our dogs, and how their olfactory life is much richer than ours. They are clearly sensing things beyond our olfactory capabilities, and it would be interesting to have some microscent detectors that could track faint traces to track animals (or know which owner is not adequately controlling a dog, ahem). They could potentially serve as smoke or carbon monoxide detectors also.
Similarly, auditory enhancement: could we hear things fainter than our ears detect, or have them serve as a stethoscope? Could we detect far off cries for help that our ears can’t? Of course, that could be misused, too, to eavesdrop on conversations. Interesting ethical issues come in.
And we’ve already heard about the potential to measure one’s movement, blood pressure, pulse, temperature, and maybe even blood sugar, to track one’s health. The fit bands are getting smarter and more capable.
There is the possibility for other things we personally can’t directly track: measuring ambient temperatures quantitatively, and air pressure are both already possible and in some devices. The thermometer could be a health and weather guide, and a barometer/altimeter would be valuable for hiking in addition to weather.
The combination of reporting these could be valuable too. Sensor nets, where the data from many micro sensors are aggregated have interesting possibilities. Either with known combinations, such as aggregating temperature and air pressure help with weather, or machine learning where for example we include sensitive motion detectors, and might be able to learn to predict earthquakes like supposedly animals can. Sounds too could be used to triangulate on cries for help, and material detectors could help locate sources of pollution.
We’ve done amazing things with technology, and sensors are both shrinking and getting more powerful. Imagine having sensors scattered about your body in various wearables and integrating that data in known ways, and agreeing for anonymous aggregation for data mining. Yes, there are concerns, but benefits too.
We can put these together in interesting ways, notifications of things we should pay attention to, or just curiosity to observe things our natural senses can’t detect. We can open up the world in powerful ways to support being more informed and more productive. It’s up to us to harness it in worthwhile ways.
In a recent chat, a colleague I respect said the word ‘engagement’ was anathema. This surprised me, as I’ve been quite outspoken about the need for engagement (for one small example, writing a book about it!). It may be that the conflict is definitional, for it appeared that my colleague and another respondent viewed engagement as bloating the content, and that’s not what I mean at all. So I thought I lay out what I mean when I say engaging, and why I think it’s crucial.
Let’s be clear what I don’t mean. If you think by engagement it’s adding in extra stuff, we’re using a very different definition of engagement. It’s not about tarting up uninteresting stuff with ‘fun’ (e.g. racing themed window dressing on knowledge test). It’s not about putting in unnecessary unrelated imagery, sounds, or anything else. Heck, the research of Dick Mayer at UCSB shows this actually hinders learning!
So what do I mean? For one thing, stripping away any ‘nice to have’ or unnecessary info. Lean is engaging! You have to focus on what really will help the learners, and in ways that they get. And they do. And then help them in the ‘in the ways they get’ bit.
You need contextualized practice. Engaging is making the context meaningful to the learners. You need contextualization (e.g research by John Bransford on anchored cognition), but arbitrary contextualization isn’t as good as intrinsically interesting contexts. This isn’t window dressing, since you need to be doing it anyway, but do it. And in a minimal style (as de Saint-Exupery said: “Perfection is finally attained not when there is no longer anything to add but when there is no longer anything to take away…”).
You want compelling examples. We know that examples lead to better learning (ala, for instance John Sweller’s work on cognitive load), but again, making them meaningful to the learners is critical. This isn’t window dressing, as we need them, but they’re better if they’re well told as intrinsically interesting stories.
Finally, we need to introduce the learning. Too often we do this in ways that the learner doesn’t get the WIIFM (What’s In It For Me). Learners learn better when they’re emotionally open to the content instead of uninterested. This may be a wee bit more, but we can account for this by getting rid of the usual introductory stuff. And it’s worth it.
Now, let’s be clear, this is for when we’ve deemed formal learning as necessary. When the audience is practitioners who know what they need and why it’s important, then giving them ‘just the facts’, performance support, is sufficient. But if it’s new skills they need, when you need a learning experience, then you want to make it engaging. Not extrinsically, but intrinsically. And that’s not more in quantity, it’s not bloated, it’s more in quality, in minimalism for content and maximal for immersion.
Engaging learning is a good thing, a better thing than not, the right thing. I’m hoping it’s just definitional, because I can’t see the contrary argument unless there’s confusion over what I mean. Anyone?