Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

Yesterday I wrote about some products, and I thought I should also own up to the mobile apps I use while traveling (at least domestically, international is still a bloody headache).  It’s something I do a fair bit, and is a natural opportunity for mobile to make your life easier and more effective.

First, the natural functions of basic apps are helpful.  I put my flight details and a reminder into my calendar.  3 hours before the flight, unless it’s a connection, then 40 minutes to alert me to get to the gate (United used to have an option to automatically download it to your calendar, but that changed with the software switch on the integration with the proud bird).  I also put in reservations for cars and hotels. I keep track of the confirmation number that way and don’t have to carry around an extra piece of paper.  The camera is useful too, when I need to remember my parking space.  Easier than entering into the calendar!  And I have a password app (I use SplashID since I had it before on my Treo) where I store all my membership numbers for the loyalty programs. May as well get the benefits if you have to travel.  And Google Search gets used for lots of things.

A I mentioned yesterday, Navigon is GPS software that I’ve used many a time to get from place a to place B.  I try to avoid driving if at all possible (such a waste of time, give me a train any time), but when I need to in or to an unfamiliar destination, GPS is the go. These days Google Maps does a very good job too, but if you’re going somewhere with dodgy cell coverage, having maps local is nice (if battery abusive: keep a charger).  Google maps in particular is very useful for walking directions and times, too.

I use the iBart app to check train schedules to and from the airport.  There are lots of apps out there to facilitate using particular train systems, and I’d use Metro in other towns if I were using public transit, e.g. Boston or DC.  If you live in a particular location, check and see if there’s an app for your system.

On occasions, I use SuperShuttle (I try to be frugal when time allows), and their app lets you book the trip, check on your van, etc.  When needed, it’s quite useful.  TaxiMagic would be used sometimes if I had trouble getting a cab (I can recall one time in Philly where it would’ve been very handy).

When I do have to drive, CheapGas helps you find the prices of petrol near you and find a provider with the best deal. Other special purpose driving apps are RoadAhead (finding things at turnouts ahead; but it would require someone else in the car with you) and the AAA and Roadside apps, which can help you find accommodation or help you with car trouble.  Thankfully haven’t needed them, but nice to have.

At airports, I love GateGuru.  I try to get to the airport early (I’d rather be cooling my heels with a book or an app than sweating whether I’ll make it thru security on time), and if I have time to kill or need to grab a meal or a drink, GateGuru finds the opportunities nearby and has ratings.  Very helpful.

I’ve the SeatGuru app, but I tend to use the website, as it can be helpful for choosing the best seating position, particularly when you’ve got a choice and the extra considerations aren’t obvious (loud, limited recline, etc).

When I’m looking for a place to eat, Yelp can be very helpful (in fact, finding us the nice Twin Cities Grill in Minneapolis just last week).  You can indicate where you are and look for what’s around. Google Maps can do this too, but Yelp’s somehow a little better, optimized as it is for this purpose.  On occasion I’ll use or coordinate with UrbanSpoon.

Finally, a shoutout to United.  I’ve been sucked in for years (long story, started when they were the last option when I lived in Sydney), but whether you like the service or airline or not, their app is a great example of mobile support. You can review your flights, get your boarding pass, check flight status, get your mobile QR code boarding pass, and even book a flight. Really nice job of matching user need to functionality.

So, what apps have made your life easier when you travel?

I don’t usually talk about products, particularly ones I’ve received as opposed to have chosen.  However, there are a couple of mentions worth making:

GOOD

I won a copy of Navigon. I’d always wanted a GPS, but didn’t want to buy one, figuring they’d get outdated. I was glad to get it, as Google Maps wasn’t allowed to do turn-by-turn on the iPhone.  I’ve used it a number of times, and have been very satisfied. The nice thing as opposed to the apps is that it works where there isn’t cellphone connectivity. The interface generally maps well to my goals, and I can usually figure out how to do the unusual things. Note that I don’t usually try to put in extra stops or anything.  It won’t seem to use my bluetooth headphone, unlike Google Maps, which now does turn-by-turn, so these days I may alternate.  Note: the processing required for Navigon does mean using a car-charger, or seriously depleting your batter, but I can’t see how that could be worked around, it is a processing intensive task.  It’s been a keeper, and gratefully used a number of times over the past few years.  Nice to have it as an app that travels with my phone so no extra hardware needed, and they can upgrade the software and it migrates to new phones.

I also earned a pair of Sony Walkman headphones. These are digital, so you can load up your playlist, and then wear them.  They’re very minimalist: two ear pieces and a cable that joins them that goes behind your head.  As you might expect, they’re oriented towards Windows, with no information for a Mac user provided, but their website shows how to load music on them.  I don’t listen to music via headphones much, but for working out these seemed like a great solution, better than figuring out where to carry an iPhone and having the cord dangling. It’s got decent storage; my workout playlist fits with plenty of room. One problem for a Mac is that there’s no obvious information about how to have different playlists, though your supposed to be able to shuffle between lists. Regardless, I am only using for working out at this point so my ‘rowdy’ music is just fine.  Another nice point is that the USB cable that connects to the computer is also how you charge them. They fit easily in my luggage and are now a travel partner.

BAD

I didn’t win, but paid an expo price (or so I thought) for a HyperShield stylus for my iPad. I liked the two-tone silver/gold look and the pen form-factor  I got it over a year a year ago, and in the past couple of months started using it occasionally to try taking handwritten notes (contemplating an app that allows both handwriting and tapping, because I like to take diagrams).  The stylus is far better than my finger for such purposes, and though my writing makes a doctor’s prescription look legible, I liked changing inks, drawing pictures, etc.  I am in awe and jealous of my colleague’s abilities to do the same and make excellent drawings and elegant writing, but it was good enough. Until, after not many hours of use, suddenly it started grabbing at the screen, not dragging smoothly but chattering across.  I looked carefully at the nub, and saw that it was peeling. What was apparently peeling off is the smooth surface.  Of course, there was only a 90 day warranty, and I didn’t really expect to get it replaced, but I am dismayed that it could fail after such a short period of time.  Caveat emptor.

And a rude noise in the general direction of any app with a free teaser and a premium version that decides to increase the annoyance factor to get you to pay.  Make a clear value proposition to upgrade that is on virtue of better capability.  Don’t have an initial choice and then decide to pester people more.  Ahem, Sol Free.

Harold Jarche reviews Marina Gorbis’ new book The Nature of the Future, finding value in it. I was intrigued by one comment which I thought was relevant to organizations.  It has to do with the nature of thinking.

In it, this quote struck a nerve: “Gorbis identifies unique human skills”.  The list of them intrigued me:

• Sensemaking
• Social and emotional intelligence
• Novel and adaptive thinking
• Moral and ethical reasoning

While all are intriguing and important, the first and third really struck me.  When I talk about digital technology (which I do a lot :), I mention how it perfectly augments our cognitive architecture. Our brains are pattern-matchers and meaning extractors.  They’re really good at seeing insights.  And they’re really bad at rote memory, and complex calculations.

Digital technology is exactly the reverse: it’s great at remembering rote information and in doing complex calculations. It’s extremely hard to get computers to do good pattern-matching or meaning making.

For the purposes of achieving meaningful outcomes, coupling our capabilities with digital technology makes a lot of sense.  That’s why mobile makes so much sense: it decouples that complementary capability from the desktop, and untethers our outboard brain.

From an organizational point of view, you want to be empowering your people with digital augmentation. From a societal point of view, you want to have people doing meaningful tasks where they tap into human capability, and not doing rote tasks. They’re going to be bad at it!  And, you can infer, it’s also the case that you’re going to want education to focus on how to do problem-solving and using digital technology as an augment, not on doing rote things and memory tasks.  Ahem.

Twitter’s been an integral part of my social media existence for more than four years n0w, and owing to things like #lrnchat, I need to have good tools.  I’ve played around with a number, but TweetDeck swept my enthusiasm for quite a while.  And now it’s going, and I’m mad and sad.

To understand, you have to understand several things:

• When you’re across platforms, sometimes on my Mac, sometimes on my iPad, and sometimes on my iPhone, it’s a major benefit to have one tool that is across the platforms
• If you’re doing something like monitoring a conference backchannel over several days, you have to have columns
• If you’re engaged in a 60 minute chat, you have to have quick updates
• And if you have to log in some of the times you want to use it, you’ll be less likely to participate

TweetDeck met all of these. Barely, it was across platforms, but not well: TweetDeck on the iPad had degraded to pretty pathetic. It surprised me how it could be so good on the iPhone, and so bad on the iPad.  Of course, they haven’t updated the iPad version in forever.  I used to regularly harass them about it via tweets.

Twitter bought TweetDeck, which seemed like it could be a good thing, but it seemed to hamstring the teams, having them focus on the web version.  And now they’re getting rid of the apps completely.  That’s why I’m sad.

What’s worse, the reasons TweetDeck is supposedly going away is that they find that more and more people are using the Twitter app on iOS. Um, hello, the TweetDeck on the iPad is broken!  Of course they aren’t using it! And columns on the iPhone just don’t make a lot of difference.  That’s why I’m mad, it’s not that it’s not in demand, they’ve killed it!

There had been no other cross-platform solution that meets all the needs above.  None.  HootSuite came close, but it didn’t update fast, last I checked. TweetBot was supposedly industrial strength, but it was only iOS.   And Twitter’s own solution doesn’t support columns.  There literally wasn’t an alternate.  Even TweetDeck on the web will ‘time out’ and you need to login again.  It’s a barrier to go into your password keeper, enter ID app password, navigate to entry, get twitter password, and go back and log in. Particularly when you’re dashing to join a chat.

It appears TweetBot now has a Mac solution, so I’ll be checking that out.  Fingers crossed.

The API formerly known as Tin Can provides a consistent way to report individual activity. With the simple syntax of <who> <did> <this> (e.g. <Clark Quinn> <wrote> <a blog post>), systems can generate records across a wide variety of activity, creating a rich base of data to mine for contingencies that lead to success. While machine learning and analytics is one opportunity, there’s another, which is having people look at the data.  And one person in particular.

As background, I was fortunate back in 1989 to get a post-doctoral fellowship to study at the Learning Research & Development Center at the University of Pittsburgh.  One of the projects that had been developed was a series of intelligent tutoring systems (ITS) that shared an unusual characteristic.  Unlike most ITS, which tutor on the domain, these three systems crossed domains (geometric optics, microeconomics, and electrical circuits, if memory serves) but the tutoring was about the systematicity in exploration. That is, the system tracked and intervened on whether you were varying one variable at a time, ensuring your data sampling was across a broad enough range of data points, etc.  This reflected work done by the Valerie Shute and Jeffery Bonar some years before on your learning strategies.

I had the further benefit to work under the guidance of Leona Schauble, a very insightful researcher.  One of her projects was with Kalyani Raghavan on working to make the learners’ paths in these systems visible and comprehensible to the learner, and they created the Dynamic And Reflective Notation (DARN, heh!) to capture and represent those paths.

Fast forward to today, and one of the big opportunities I see is for performers to reflect on their own paths of action. The granularity at which Tin Can can capture data, and systems might be instrumented to generate data, could be too small to be useful, so some way of aggregating activity to a reasonable level would be necessary, but looking at one’s own paths, and perhaps others, would be a useful way to reflect on process and look for opportunities to improve.

Reflection on action is a powerful learning and improvement process, but recollection isn’t as good as actual recording.  The power of working out loud is really seen when those tracks are left for examination.  The API has the opportunity to support more than system mining (“oh look, everyone who has this responsibility who touches this resource does way better than those who don’t”). Not that there’s anything wrong  with that, but having performers do it too is a great opportunity not to be missed. As the work on protein folding has found, some patterns are better for computer solution, and others for human. We’d be remiss if we didn’t explore the opportunities to be found.

“Education over the Internet is going to be so big it is going to make email usage look like a rounding error.” – John Chambers, CEO of Cisco

This bold pronouncement of John Chambers a number of years ago hasn’t really played out as promised.  I would argue that elearning has begun to grow, what with the rise of online education and the recent interest in MOOCs.  And if we take a performance ecosystem view of elearning, including performance support and social, we can begin to think much more broadly about the relationship.  I don’t think John thought of self-learning via Google or YouTube, or learning together via LinkedIn and Twitter, but if we give him the benefit of the doubt, we can begin to think that elearning may be of a substantial bulk in proportion to email, though not yet rounding error size.

However, I want to consider another elearning view that could propose such a relationship.  If we take a performance ecosystem view of mobile, we may well have that sort of ratio.  Think about it, mobile can claim large numbers around:

• people with mobile phones who have no email or real internet, but voice and text messages give them reach
• using and/or sharing photos or videos for help
• accessing the internet through their phones to learn and perform
• using apps to help them do things, calculating things, supporting their performance
• connecting to social networks on a variety of platforms: FaceBook, Twitter, LinkedIn, …
• people using context-sensitive apps to solve problems where they are and tell them what’s around
• the growth in all the above

If we consider all those (and using mobile devices for email :) we actually come up with a pretty big number!  We use mobile personally to learn and perform better in increasing ways, and we’ll start doing it more and more for work as well.  In this way, mobile learning performance is becoming the massive shift that will make email seem like a rounding error. And that is big.

Robert Ballard gave a personal and inspiring tale of exploring the world’s oceans and using technology to broaden reach.

Donald Norman’s book, The Design of Everyday Things is a must-read for anyone who creates artifacts or interfaces for humans.  This one goes forward in the same vein, but talking about how new tech in the roughly 20 years since that book came out, and the implications.  There are some interesting thoughts, though few hints for learning.

In the book, Don talks about how new technologies are increasingly smart, e.g. cars are almost self-driving (and since the book was published back in 2007, they’re now already on the cusp).  As a consequence, we have to start thinking deeply about when and where to automate, having technologies make decisions, versus when we’re in the loop.  And, in the latter case, when and how we’re kept alert (pilots lose attention trying to monitor an auto-pilot, even falling asleep).

The issue, he proposes, is that tenuous relationship between an aware partner and the human.  He uses the relationship between a horse and rider as an example, talking about loose-rein control and close-rein control. Again, there are times the rider can be asleep (I recall a gent in an Irish pub bemoaning the passing of the days when “the horse knew the way home”).

He covers a range of data points from existing circumstances as well as experiments in new approaches.  This ranges from noise to crowd behavior.  For noise, he looks at how the way mechanical things made noises were clues to their state and operation, and that we’re losing those clues as we increasingly make things quiet. Engineers are even building in noise as a feature when it’s disappeared via technical sophistication.  For crowd behavior, one example is how the removal of street signs in a couple of cities have reduced accidents.

At the end, he comes up with a set of design principles:

1. Provide rich, complex, and natural signals
2. Be predictable
3. Provide a good conceptual model
4. Make the output understandable
5. Provide continual awareness, without annoyance
6. Exploit natural mapping to make interaction understandable and effective

For learning, he talks about how robots that teach are one place in which such animated and embodied avatars make sense, whereas in may situations they’re more challenging.  He talks about how they don’t need much mobility, can speak, and can be endearing. Not to replace teachers, but to supplement them. Certainly we have the software capability, but we have to wonder what sort of system makes sense to invest in the actual embodiment versus speaking from a mobile device or computer.

As an exercise, I looked at his design principles to see what might transfer over to the design of learning experiences.  The main issue is that in learning, we want the learner facing problems, focusing on the task of creating a solution with overt cognitive awareness, as opposed to an elegant, almost unconscious, accomplishment of a goal.  This suggests that rule 2, ‘be predictable’, might be good in non-critical areas of focus, but not in the main area.  The rest seem appropriate for learning experiences as well.

This is a thoughtful book, weaving a number of elements together to capture a notion, not hammer home critical outcomes.  As such, it is not for the casual designer, but for those looking to take their design to the ‘next level’, or consider the directions that will be coming, and how we might prepare people for them. Just as Don proposed that the interface design folks should be part of the product design team in The Invisible Computer, so too should the product support specialists, sales training team, and customer training designers be part of the design team going forward, as the considerations of what people will have to learn to use new systems are increasingly a concern in the design of systems, not just products.

Last week I was on a panel about the API previously known as Tin Can at #DevLearn, and some thoughts crystallized.  Touted as the successor to SCORM, it’s ridiculously simple: Subject Verb Object: e.g. “I did this”, such as ‘John Doe read Engaging Learning’ but also ‘Jane Doe took this picture’.  And this has interesting implications.

First, the API itself is very simple, and while it can be useful on it’s own, it’ll be really useful when there’re tools around it.  It’s just a foundation upon which things can be done.  There’ll need to be places to record these actions, and ones to pull together sequences of recommendations for learning paths, and more.  You’ll want to build portfolios of what you’ve done (not just what content you’ve touched).

But it’s about more than learning.  These can cross accessing performance support resources, actions in social media systems, and more. This person touched that resource. That person edited this file.  This other person commented.

One big interesting opportunity is to be able to start mining these.  We can start looking at evidence of what folks did and finding good and bad outcomes.  It’s a consistent basis for big data and analytics.  It’s also a basis to start customizing: if the people who touched this resource were better able to solve problem X, other people with that problem maybe should also touch it. If they’ve already tried X and Y, we can next recommend Z.  Personalization/customization.

An audience member asked what they should take back to their org, and who needed to know what.  My short recommendations:

Developers need to start thinking about instrumenting everything.  Everything people touch should report out on their activity.  And then start aggregating this data.  Mobile, systems, any technology touch. People can self report, but it’s better to the extent that it’s automated.

Managers need to recognize that they’re going to have very interesting opportunities to start tracking and mining information as a basis to start understanding what’s happening.  Coupled with rich other models, like of content (hence the need for a content strategy), tasks, learners, we can start doing more things by rules.

And designers need to realize, and then take advantage of, a richer suite of options for learning experiences.  Have folks take a photo of an example of X.  You can ask them to discuss Y.  Have them collaborate to develop a Z.  You could even send your learners out to do a flash mob ;).

Learning is not about content, it’s about experience, and now we have ways to talk about it and track it. It’s just a foundation, just a standard, just plumbing, just a start, but valuable as all that.

Gary Woodill gave a broad reaching keynote covering the past, present, and future of mobile learning. Peppered with great examples and good thinking, it was an illuminating kickoff to the MobiLearnAsia conference.