Making learning fit

People lead increasingly busy lives. With work, family, household maintenance, and a dozen other things, our schedules tend to fill up. In this context, it’s difficult to find time to engage our need for life-long learning. At the end of a day or week of work, it can seem overwhelming to sit for a course. The hours required can be hard to fit into a schedule. But the fact is, there is always time left in the schedule. The challenge is that we need to be creative in getting learning to fit into the schedule.

I’m reminded of an old story that you see every once in a while on Facebook or other social media. I don’t recall the exact context, but it involved a teacher making a demonstration trying to fill a jar. He started with marbles, “filling” the jar to the top until no more marbles would fit. Is the jar “full?” No. There’s plenty of space, just no more marble sized pockets.

So the teacher continues with some small beads. You pour them into the jar, and they settle into much of the spaces between the marbles. The teacher does that until the beads are level with the top of the jar. Is it full yet? No. The teacher proceeds to add sand to the jar. The sand settles into the tinier spaces between the beads.

Finally, the teacher completes the demonstration by pouring water into the jar.

So this is a nice story. What can we take from it?

Well, the fact of the matter is that we probably have hours of time each week that could be used for learning. The problem is the time is split up into little pieces between other things, 5 minutes here, 10 minutes there. As well, there are chunks of time in contexts that would not traditionally have been thought of as opportunities to access training material, for example, sitting on the couch in front of the living room TV, out walking in the street, or driving in the car.

As training designers and developers, we can direct our efforts in two major directions:

  1. Making training in smaller, bite sized chunks that will fit in easily and conveniently in spare cycles between other things
  2. Making training that can be readily accessed in non-traditional learning environments/media, including:
    a. Living room via smart TV and/or internet connected entertainment system such as a modern game system like the Xbox One or PS4
    b. Through an in-car entertainment system
    c. Through wearable computers and augmented reality

This leads to some challenges for us as designers and developers.

The first challenge requires us to think hard about how to break down training into small, focused, self-contained learning pieces that are well-indexed and findable. These will often be accessed individually as informal learning materials. Though it may be possible to prompt learners with suggestions about connected content they might find useful, depending on the Learning Management System through which users browse content.

The second challenge requires us to learn about the tools needed to develop for these other platforms, as well as the unique affordances involved in terms of interaction and navigation of the platforms.
Some of these points I have touched on previously in posts here. The others I hope to speak about in more depth in the weeks to come.

A new hobby project: Exploring with the Kinect

First of all, happy weekend.

Haven’t published any posts in a while; have a lot of drafts on the go, but nothing quite finished yet. In the meantime, I thought I’d make a quick post. It’s been a pretty good week in the Anderson household. At work, got a nice early Xmas present in the form of an offer of a full time staff position at work. (Accepted!) Which was nice. Contracting is interesting, but there’s something to be said for stability.

At home, I was happy to receive a large UPS parcel from Microsoft – a new Xbox One with Kinect.

Xbox One with Kinect Assassin's Creed Unity Bundle

I’ve been interested in the Xbox, and the Kinect in particular, for some time. I’ve written a few articles on this blog talking about the potential of Kinect and sensor technologies like it to expand the possibilities of training, and computing in general. The prospect of predictable horizons on the work front and a sweet holiday sale on the Microsoft web store helped to seal my decision to take the plunge.

So far, I’m quite pleased with the Xbox One as a product. It’s my first time buying a gaming system in about 20 years; the state of the art has definitely advanced since the days of the Sega Genesis 😉

The setup is easy and smooth. The regular controller plus the voice and gesture based interface of the Kinect allow multiple ways to get things done in terms of navigation and interaction.

The voice and gesture controls are introduced via simple tutorials. A fine example of quick, simple tutorial materials.

The voice controls work nicely. My son and I have had no trouble being understood, and the system OS includes visual cues when speech input is activated as to what commands can be made on any particular screen. It doesn’t quite understand my daughter, but she’s a little younger and missing two of her front teeth.

The gesture control is cool too, though it will take a bit of effort to get smooth and precise with it.

I also ordered the optional adapter to plug the Kinect sensor into a USB connector of a Windows computer for Kinect for Windows apps. This is a cool recent development; previously, to play with Kinect on a Windows computer, you had to buy a special $200 Kinect sensor specifically for that purpose. Allowing people to just use the sensor from their Xbox One opens things up another notch.

I’m looking forward to playing around on a hobby basis with the free Kinect For Windows SDK. Basically, if you have an Xbox One with Kinect, and you buy the adapter, the license is open for you to make Windows apps, even commercial apps, for no extra charge. Kudos to Microsoft for being smart and removing barriers to innovation and experimentation

The SDK, along with lots of guidance and tutorial material available on their website:

I’m excited to explore what sorts of interactions can be made with this technology, with an eye to training applications. In particular, the ability of the Kinect to recognize body movements, facial expressions / emotional states, and even heart rate could potentially add a lot to monitoring learners level of engagement and their performance on motor tasks.

Also on the menu is a Udemy course on Web Development I signed up for a number of weeks ago when it was on sale. (Which I hope to finally get started with over the holiday period!) Together, these two hobby projects should take up a good bit of my spare time over the coming months.

I look forward to sharing anything helpful I learn along the way.

On Driver Education

When we’re driving around, I often like to remind my eldest son that by the time he turns 16, in the summer of 2021, driving will probably be, or be in the process of becoming, an obsolete skill. (In the city and on the major highways, at least) Driverless cars are in the workable roadworthy prototype stage, and an array of performance support tools are being rolled out in newer cars. These tools serve to guide drivers, augment their awareness of their surroundings, and improve safety. One of the posts I currently have in draft is on the parallels between aviation and driving in terms of increasing automation and performance support. Experts tend to predict driverless cars as becoming a common reality in the early 2020s.

In the meantime, people will drive, and young people will need to learn to drive. But is it being done well? Or as well as it could. Safety equipment in cars and in the engineering of roads has reduced overall accidents and fatalities, but driving remains a relatively dangerous mode of transportation.

Young people entering into the world of driving at age 16 (and new drivers in general) need solid training to stay safe. When I turned 16 I went through the Young Drivers of Canada program. The basic program is similar to high school driver’s education, but with more emphasis on practical skills of situational awareness, threat monitoring, and collision avoidance. The training consisted of a classroom component of about one week in length, and a number of in car driving lessons. The classroom time was for teaching of theory, and consisted largely of lecture, some discussion, and watching of instructional videos. The road lessons in the car allowed practice of skills with grading and feedback by a trained instructor.

I went through this training close to 20 years ago now. This intervening period has seen a plethora of new information and sensor technologies arrive on the market. Oddly, the domain of driver education does not seem to have evolved appreciably in terms of approach. It still seems to be classroom plus supervised road lesson.

Looking at this through the eyes of an Instructional Designer, I see some gaps here in this training approach that, if filled, could lead to more effective learning, improved safety in early experiences on the road, and improved transfer and retainment of skills after the initial training is completed.

The classroom training and road practice are a good foundation, especially within a framework of defensive driving that includes threat monitoring, preventive measures, and emergency maneuvers / collision avoidance. These are necessary components of a strong foundation for an effective training system, though I’d probably advocate exploring some form of blended approach for teaching theory materials. Having some material delivered as online video or eLearning/mLearning content would allow for better flexibility of the learners, particularly adult learners. But overall, the theory and hands on supervised practice are good components of a foundation.

That said, I see two places where additional training could fill a gap and potentially improve performance.

These gaps are:

  • The need for some intermediate training to bridge the space between classroom (or online) theory and practice on actual roads. There is a wide chasm of experience between the cognitive activity of learning theory material in a classroom and the complex psychomotor skill of driving. Something in between would help to bridge this chasm and soften the transition.
  • After the course is over, there is a need for some level of electronic performance support while the young driver is out on his own. This is needed to scaffold the learner in applying the skills safely while they are still new, until such point that the skills become internalized, and automatic.

In regards to the first gap, let’s take the example of aviation. When an airline pilot is doing type training on a new aircraft, the pilot does not go directly from the classroom to flying the actual plane. First, the pilot spends time training scenarios on a simulator device. Simulation based training offers a lot of benefits. It is completely safe, but feels psychologically real when the different types of fidelity (the sense of realism of the simulation) are high. There are different dimensions of fidelity – (1) sensory perception/look and feel, (2) the process of operation of the simulated equipment versus real, and (3) the dynamics of the simulation, the relation between action and results.  It can be less expensive to operate a simulator than the actual equipment, at least once the initial investment is made to acquire the simulator. You can also control the scenario conditions to have focused training and avoid the problem practical training experiences being ad hoc, depending on the random conditions of the day.

This first gap then could be addressed through some sort of electronic driving simulator, similar to how pilots train on flight simulators. I understand that some driver training programs alresady use these, but it needs to be more universal. At one end of it could be some piece of fixed equipment similar to the flight simulator or fixed based trainer, with a mockup of a real driver’s seat, dashboard, displays/gauges, and steering wheel combined with screens to simulate out the window views, and speakers for sound effects. At the other end of it might be something like a realistic game-like driving simulation on an Xbox with a Kinect sensor and the learner’s hands as controller.

Performance support on the other hand could take the form of some sort of apparatus with cameras/sensors and a built in computer set up inside an actual car. It could collect data about speed, traffic conditions, weather, local speed limit, braking and swerving, and signalling. It could track eye movements to look out the windshield, both toward near objects and far objects, toward rear and side mirrors, and toward the blind spot. It could also monitor hand positions on the wheel (or stick, as relevant). The computer could collect data for later analysis (Syncing to a mobile app, for example).

Ideally, it would also give spoken word support cues / prompts / feedback in response to conditions and what the novice driver is doing:
“Remember to check your mirrors” “Look ahead to spot upcoming problems” “Remember to check your blind spot” “Brake!” “Try not to ride the clutch” “A little more gas” “Slow down a bit for weather/traffic conditions” “Accident ahead. Caution”)

Ideally, this form of performance support could be built into future cars as a “training / support” mode. This mode could be engaged at the push of a button on the dashboard as part of the support/automation systems that are increasingly built into modern cars. For now, though, it would have to be developed as a third party device.

The television as a learning and training space


Recent years have seen the world of training embracing  learning on mobile devices, or mlearning, for short. There are many reasons for this:

  1. Client demand as people more and more browse the internet principally through mobile devices
  2. Clients always having their phones with them, allowing lots of little moments during a day when learning could potentially take place.
  3. Phones having lots of sensors and input methods, allowing for innovative interactions
  4. Phones allowing multiple communciation methods

Designers and developers have been working on designs using mobile learning. At its most basic this has taken the form of  using file formats so that videos or presentations will play on a tablet, or even just an iPad. Or to make the training as an iPad app or playable within some container app.

Others, approaching the matter with some semblance of actual seriousness, have gotten more creative, and tailored training more to the unique affordances of smart phones and tablets. They make learning games that use sensors or activities that use sensors as inputs for motion or touch based interactions. Or they use location information. Others use ideas of informal learning and performance support to break training into small, focused little pieces that can be accessed in a spare moment.

eLearning authoring tool providers advertise their tools as enabling responsive eLearning. They hype the promise of being able to publish content to multiple media and device types, for desktop, tablet, and mobile.

This is good for learning and training. However, in this focus on mobile, we may be losing sight of possibly the next key development of web-based learning and training – the television as a learning and training space.

Television as a new window to Internet content and learning

Sitting on a couch with a tablet is a nice way to watch  a video or presentation. The device is light and comfortable. But, still, it’s a 10 inch screen. It is nice for portability, but it’s still a small screen. The small size is a compromise, trading visibility and real estate for portability.

But across from the couch is what? The TV. Big screen – 30, 40, 50, 60 inches. 1080p HD, easy to see, nice to watch, decent speakers. And you don’t have to hold anything.

Television used to be a box on which we watched traditional television programs, whether delivered over the air, or through cable or satellite broadcast. Then, came VHS players, DVD, Blu-ray, video game consoles. The living room TV became instead the screen in the middle of a home entertainment center.

Now, increasingly, televisions are also becoming just another one of the screens,albeit, much bigger ones, through which to access internet content, whether for entertainment, work, or learning. This takes the form of video, audio, text, and apps. The long promised fusing of internet and television has arrived, with several different options available to make this possible.

Many TVs are now “smart TVs,” combining a TV with a computer. These TVs are WiFi enabled, with built in interfaces and platforms with apps capability. Apps allow straightforward connectivity to content sources like Youtube, Netflix, digital music streaming services, and other streaming media.

Modern TV screens also allow for stereoscopic 3D. While no longer a faddish selling point, most newer TVs are by market standard capable of displaying stereoscopic 3D content, whether accessed over the web or on 3D Blu-rays. TVs stand out notably from the other screens through which we consume content in that many of them today readily allow Stereoscopic 3D media. TVs are the one dependable 3D screen that people commonly own.

TVs are also capable of being connected to gaming systems like PS4 and Xbox One, the second of which includes the Xbox Kinect motion and voice sensor. These systems, while meant primarily for gaming, are also intended more generally for home entertainment, with app platforms and apps like Netflix and Youtube to see internet video content.

As well, set top boxes like Apple TV as well as many WiFi enabled Blu-ray players offer a similar bridge between the television and the internet.

Tablets, phones, and laptops can share screens wirelessly to TVs, either through devices like Apple TV, game systems, or via Miracast / WiDi from enabled devices.

It is easy to get content on the TV. As well, the TV will either be setup with sensors, whether in the TV itself or via something like an Xbox, or the person will be screen sharing from something which has sensors and a touch based control interface. It becomes easier to browse, select, and interact with online content shown on the TV.

Designers, both web designers an instructional designers,  need to think about training and learning possibilities in this space.  just as they should be thinking about that OTHER class of displays that will also be more and more in people’s lives – wearables and augmented/virtual reality tech such as Google Glass and Oculus Rift. (More on this in a future post)


There are a few challenges in this area:


One main challenge is that there are so many different sorts of configurations and ways to connect the internet to the TV:

  • Via game consoles such as XBox One or Sony PS4
  • Smart TVs
  • Set top boxes like Apple TV, Wifi Blu-ray player, or Chromecast
  • Computer connected to the TV to share the screen via HDMI cable
  • Wireless screencast from laptop, tablet, or smartphone to the TV, whether through Apple Airplay or up and coming wireless screencasting standards WiDi (wireless direct) and Miracast.

This makes things difficult for developers, as there is no one clear dominant target for development.

The gaming consoles, which have positioned themselves as not only gaming platforms, but home entertainment hubs, may be one promising avenue, as the multi-billion dollar gaming industry already attracts lots of skilled developers to these platforms. Microsoft’s XBox One in particular runs an operating system related to Windows and uses the same development toolkit. Also, these gaming consoles offer innovative ways to interact with the content on the TV through different types of controller devices. These include body movement and voice based controls. The gaming console option offers interesting possibilities in terms of innovative learning interactions.

A more straightforward, elegant solution may be through smart TVs, where everything is in one box. This would especially be the case if in the future the telvision included sensors that could be turned on for Kinect-like interaction with cameras and microphones. One challenge, however, is attracting developers to different platforms from different manufacturers. Possibly only a company like Samsung, which is involved in manufacturing phones, tablets, computers, and TVs would be in a strong position to carry over advances in interfaces and interactivity from other devices to TVs. Or someone like Apple.

The other challenge would be emotional reactions from consumers. When early press about the Xbox One suggested that the system would require the Kinect sensor – which includes stereo cameras and microphones – to always be on, even when the system is not in use, people became very paranoid, and there was a backlash.

It is possible that TVs will evolve in coming years to become a sort of all-in-one computer, with web connection, innovative web browsing methods (the concept of adaptive web design will also have to adapt and evolve to cater to TV as a screen), app platforms, and built in SSD memory space, possibly supplemented by cloud storage.

Quite possibly the next stage of the Apple OS – Android – Windows – Linux battles will be fought on the battlefield of internet connected TVs. Ubuntu, for example (A variant of the Linux operating system) has actually been positioning itself as a flexible multiplatform, including TV – OS for some time.

Wireless screen sharing may be the simplest approach, making the smartphone, tablet, or PC the central point of control of what appears on the TV screen. Desktop and laptop computers would have limits though in terms of enabling learning interactions.

Tablets and smartphones, could potentially allow for interesting learning interactions through the accelerometer, gyroscope, and touch sensors.

The scene is probably going to be messy for a few years with a lot of options making it hard for developers to pick. This will make it hard to form development communities that will drive things explosively forward.

Interface and Interactivity

The possibilities for learning and training will depend somewhat on the options available for interactivity. One of the challenges in making the TV a hub for learning content is how the user can control and navigate content sitting or standing from across the room. Good eLearning and online training especially requires rich interactions.

But how do you interface with the TV? A computer you sit right there and control it via mouse and keyboard, and to a lesser extent, microphone and camera. A tablet or smartphone you tap it, swipe it,  turn it, talk to it, because again, you’re up close to it and it fits in your hands.

TV is different. You sit back from it, or stand back from it. You’re not going to stand at your TV tapping the screen like those big maps on CNN election night.

There are probably four major options:

  1. Some modification of a traditional TV remote, possibly one with a touchscreen and accelerometer/gyroscope sensors
  2. Some camera and microphone based sensor like the MS Kinect that lets you control via voice and body gesture
  3. Controlling through a laptop computer, tablet, or smartphone, which shares the screen wirelessly via WiDi, Miracast, or Apple Airplay and lets you control things via touchscreen and motion sensors. The TV simply becomes a screen to mirror content on the other device.
  4. A smartphone or tablet is paired with the TV via an app, and serves as a WiFi-connected touch- and motion-based controller.

All of these could probably be made to work, though options 2 and 4 are probably the most plausible options going forward in terms of usability and in terms of building on existing platforms.


Learning and Training Possibilities

The matter then becomes how to harness this emerging new portal to the internet for learning an training.

A few possibilities come to mind.

  • Any passive consumption of video content. Particularly content in HD or stereoscopic 3D format. YouTube contet, for example. A TV would be the most natural and comfortable way to watch. Everything becomes bigger and more lifelike
  • Educational gaming activities using a gaming controller
  • Web content browsing with voice and gesture inputs enabled by something like the Kinect. Say, for example, a view of different documents or different levels of detail making use of different focal planes in a 3D field of view. This allows information and screen elements to be arranged not just along dimensions of horizontal and vertical, but by depth as well.
  • Interaction with stereoscopic 3D models using Kinect sensor. Such as chemical structures, architectural structures, geographic feature models of an area, or components of equipment.
  • Live, synschronous, life-like teleconferencing via TVs and Kinect sensors using apps like Skype or something like it embedded in a virtual classroom application. Virtual classroom would work very well on an HD television with connected camera and microphone. For live, face to face communications, for conversational practice in language learning, or a live virtual tutoring session.
  • Using the Kinect, the learner practices some psychomotor skill. At the same time, the Kinect camera lets a remote instructor watch the performance and comment. The Kinect could also capture data to assist in analyzing biomechanics.

These are a few sample ideas. Maybe readers can think of others.


The past six years have seen dramatic changes with the coming into the mainstream of mobile devices as a new space for online learning, with unique affordances for interactivity. The mobile web and mLearning have expanded our horizons for entertainment and learning. The television, connected to the internet offers a new field on which we can ply our craft as designers and developers. It’s a developing field with a lot of options that will take some time to sort out and settle down. But for those of us tasked with helping our clients and students to learn and develop, it’s a field we would do well not to ignore.


Once again, feel free to share your comments, either below, or via social media.

An idea whose time has come? Reusable Learning Objects.

Introduction: A brief history of learning objects

When I was in school in the early 2000s, one of the trendy ideas in the field of educational technology was reusable learning objects (RLOs). Learning objects were a heavily promoted idea in the 1990s and early 2000s. The idea came out of US military-funded training research, focused on two goals:

  • To standardize multiple, mutually incompatible eLearning formats used by vendors to the armed forces so as to improve inter-operability of training content, and
  • To design materials using small, self-contained, meta-tagged modules to enable reuse and thus reduce development time and cost.

The name “learning object” comes from the computer paradigm of object-oriented programming, where small, self-contained code structures model objects and entities in the real world, their properties and their inner structures, and their interaction between objects and entities. This was a paradigm allowing faster development through modular design, re-usable libraries of code, and encapsulation of object data within the objects.

Learning objects try to carry some of this success from software design and development to the design and development of eLearning.

What is a learning object?

A learning object is a short learning piece, usually digital, from a few minutes up to as much as an hour in length, though usually on the shorter side. The learning piece is focused on one learning objective. It will generally include an introduction, explanation and/or demonstration, activities for the learner for practice and / or consolidation, and an assessment. It is an irreducible element of knowledge, an atomic nugget of learning.

It was expected that eLearning objects would use a standard format such as SCORM for metadata attached to the objects. This would enable the learning object to be interoperable with different delivery platforms (LMS).  The idea was for the object to represent instruction for a small nugget of content related to a specific objective.

The purpose of this was to enable re-use of training materials for faster, more efficient development of future content. Usually, when we want to reuse a body of training content as part of a new course, we need to break apart the old course, extract useful bits, and then assemble what you want back together in a cohesive fashion.

The idea with the learning objects is that they represent some small sort of smallest learning objectives. The related objects are already broken down. All that is left when building a new course is to identify what you need to teach, finding out what is already built, evaluate it, and then either re-use or re-purpose the content.

To maximize this re-usability, the learning object is supposed to be as free of specific context (audience, place, type of organization, etc) as possible. For example, if multiple audiences would want to study toward this objective, media or examples used should not be limited to only one audience.

New courses could, in theory, be built by collecting, and sequencing various learning objects, with an overall introduction and conclusion and some linkages to join it all together.

Critiques of the Learning Object concept

While learning objects were a trendy topic in the -90s and -00s, the idea was not without its critics.

There are several critiques of the learning object concept:

  • The idea of learning objects was pushed primarily by the military and for its own concerns of operational efficiency and cost savings rather than any sense that it would produce more better learning. The concerns are quantity of output and efficiency rather than quality of education
  • The idea mainly focuses on eLearning, and specifically eLearning for one solitary self-paced learner. Where social sorts of learning involving cooperation and collaboration fits within this was not clear
  • If context is removed, it is harder for learners to relate to it on a concrete level. Media and graphics and examples are generic, or some wide range. The media and examples don’t speak closely to their particular reality. As such, you risk losing the attention and motivation of the learner, because they may not see the relevance clearly.
  • If context is removed, it is harder for learners to make meaningful connections between the content and other content unless the developer puts in extra effort to put this connective material back in. Statements like, “as you remember from module 1,” or, “you will learn more about this in the coming module,” or “this is related to these other topics” would be mostly removed from learning objects to maximize reusability. Learning these sorts of connections is an important part of learning new material, and is part of what makes new learning stick together cohesively in the learner’s mind.
  • When assembling courses from smaller learning objects, it is not a matter of just sticking together lego blocks or assembling IKEA furniture. Remember that all that context that serves as a connective tissue of sorts for the objects has been stripped away to allow the reuse. To make it most effective, you need to add contextual glue/mortar in between the pieces to improve flow and relevance. This cancels a lot of the time savings that are advertised.


So up through the early and mid 2000s there was a lot of hype about learning objects, When I was in my Educational Technology program at that time, the concept was talked about, and readings were given, including critiques of the concept. Some large companies, schools, and educational networks did a lot of work in this field, with some of these projects still continuing. But the idea never took off broadly as advertised.

eLearning continued to gain broader acceptance in the academy and in industry. SCORM standards for eLearning content metadata and inter-operability went forward and became commonly used standards supported by authoring tools and Learning Management Systems. eLearning authoring tools became increasingly sophisticated, allowing simple eLearning to be developed more and more efficiently.

But the strict learning object idea did not continue to be top of mind for practitioners, who grew disillusioned by the concept as they experienced the limitations and difficulty, witnessed lots of bad eLearning content, and found the time savings and re-usability to be much less in practice than advertised.

The term learning object faded from common conversation.

In the meantime…

Life went on, technology advanced. Broadband internet became more widespread with faster speeds. This allowed easier upload and download of multimedia content, even video content.

The Web 2.0 era of user generated content came about. PHP discussion boards. Wikipedia. Youtube. Social media like Facebook. Question and answer sites like eHow and Quora. A Web where content could easily be generated by users, tagged for search, and uploaded.

This was furthered with the mainstreaming of mobile internet devices. The iPhone 3G appeared in 2008. The explosion of the smartphone market followed. This led to a proliferation of mobile apps on sophisticated pocket computers with cameras, microphones, and other sensors. Tablet computing went mainstream, with the iPad in 2010. With these mobile devices came touch based computing and context aware computing. The widespread rollout and development of high speed mobile networks enabled voice, audio, and video transmission. Smart, small, lightweight connected mobile devices mean that the user almost always has on hand.

In the field of educational technology and training, there is an increasing emphasis on informal learning such as job aids, performance support systems, and just-in-time learning.

Finally, eLearning authoring tools have become much more user friendly, making it easier for experts to build their own content and distribute it. This broadens the development pool and makes it easier to generate content.

All of these developments and change have come over the past ten years. We start to see a very different landscape from what it was when this learning objects concept originally peaked and then faded in the early 2000s.

When you look at all these developments together, and reflect, you start to wonder if maybe that old idea of learning objects might have renewed relevance in today’s environment.


So what’s changed?

So putting it together, what is different today?

Cell phones and inexpensive but powerful recording equipment let us easily record content. Easy to use authoring software lets us easily assemble media into small but meaningful packets of learning material. Ubiquitous network connections and sharing features in apps let us easily upload content from almost anywhere.

Platforms like Youtube, Soundcloud, Facebook, and others give us a place to upload and organize content, share it with others, see what others have shared, and further pass content along to others.

To keep up with the rapid pace of the age, these pieces of content are short and focused. In line with trends in informal learning and continuous learning, a lot of learning materials are posted on these sorts of platforms and on company intranets, so learners can access brief, relevant material as needed on the job rather than taking a formal course. There is also the trend in microlearning, focusing on short learning pieces of a few minutes in length.Short learning pieces also work better with the usage patterns of smartphones

Responsive web design and responsive eLearning design allow content to be developed once, hosted in one location, and accessible from different devices, at any time, wherever the learner may be.

New standards technologies such as TinCan API/xAPI make it easier and more flexible to track learning on materials accessed and hosted in different locations and in a wider variety of different formats.


And so we see a lot of elements of this original vision of learning objects being realized thanks to these many separate factors coming together.

And though it is a concept that has its valid criticisms, learning objects may offer an interesting an useful model to help manage and guide this new world of content production and sharing.

The earlier discussions of 10-15 years ago may give useful insight as to how to design, structure, and build short content. As well, it may guide us as to how to meta-tag, store, and search for these materials. And, finally, these earlier discussions may give us insights into how to repurpose and combine these learning pieces into larger, cohesive learning experiences, both online and blended learning, for both individuals and groups.




Additional Links

Encouraging worker engagement and ongoing professional development with mLearning and Gamification


I have a confession. I fiddle with my phone at work. We all do this from time, throughout the day, when we’re bored, or our brain is mush, when we’re stuck/blocked, or just when we need a change of pace or break. It’s compulsive (damn you variable ratio schedule of reinforcement!)

The companies we work for don’t tend to like this so much (something about productivity), which is why most of us try to keep it to a dull roar. Many companies have de jure HR policies technically prohibiting such a thing. It’s mostly unenforced, though, because most people are responsible, and because, really, who cares so long as objectives are being met. (Also, front line managers are usually just as glued to their phone screens!)

But what if instead of fighting this tendency, companies were smart about it?

I know. Crazy talk, this. But bear with me.

What if companies and their management embraced that workers mostly have smartphones, and simply accepted as a given that they are going to take them out during the day and use them? What if, taking this as a given, they looked at ways to make lemonade out of lemons, and found a way to harness this natural behavior of employees and channel it toward ends useful to the company and to the worker as an employee?

Mobile phones present an excellent opportunity for companies to help encourage engagement at work and ongoing professional development. The concept presented here is a novel idea for encouraging worker engagement and promoting ongoing professional development in an organization through a combination of mLearning and gamification.

Technological component of solution

Informal learning through short mLearning modules

Workers have phones and use them during the day. The company has new policies and procedures it wants the workers to learn, and also wants to have a workforce committed to ongoing personal and professional development. The company wants workers that are always learning and developing their skills. Combine these two elements and make the worker’s smartphone a platform for employee training and development.

Build continuing professional development materials in small mLearning modules, targetting a length of 2-5 minutes. Design these as informal learning pieces. Include both typical didactic learning elements, but also fun, hands-on activities and games.

Design the modules as stand-alone learning moments that don’t depend too much on other learning pieces, sort of like the late 1990s/early 2000s idea of “Learning Objects.” Design the modules with a “mobile-first” approach, such that they are intended to be seen on mobile phones and look good / are easy to use there. Ensure that the modules are meta-tagged according to some logical schema / ontology of tags appropriate to the workplace or industry so that the modules are easily searchable and findable. Make the learning modules available on some TinCan API /xAPI enabled LMS,

Ensure that there is an interface for searching for and browsing modules that is easy and time-efficient for users to use on a smart phone.

Link it to HR

Track the modules taken by learners and their scores on any assessments or pass/fail. Send this data to HR data systems for tracking.

Link back HR systems the other way so that HR systems could recommend specific modules based on learner time available and on defined professional development objectives.

Allow the system to send suggestions based on most viewed content, most uprated content, and the types of content the learner has enjoyed in the past. Enable a rating system, where learners can provide as much evaluation data as they like. Either “smiley face” basic impressions data or more in depth questionnaire/short survey or both.

Within HR systems, take the data on module completion and track this compared to documented development objectives. For mandated training coming from HR, have subscribed modules or module clusters. This content would be suggested or pushed out from HR. Use notifications, either in app notifications or via text/IM/Lync.


Have a gamification layer to encourage and reinforce engagement with the system, though be careful to keep it within reason so that learners don’t feel “gamed.” Keep a tally of hours spent, courses completed, skills learned. Use gamified elements like badges and leader boards. Give the learners incentives to keep engaging with it. Track some of these stats through HR to have data on how much the employee is engaging in learning activities.

Make it social

Allow users to rate content, whether with a simple upvote/downvote or with a five star system. Allow them the opportunity to make comments. When a user is browsing modules, make information on average ratings or upvotes/downvotes visible to learners to help them with their choice. This gives feedback to designers/developers and also helps to identify quality content for other learners. This data gives a good sense of what sort of content the learners want and like, and this can be helpful for training development teams as a guide for how to allocate resources for future development.

Also, allow workers to recommend or share content they like to others. This will allow workers to help you promote good content and will further encourage engagement with the system.

Help learners get access

Make Wifi readily available to employees without restrictions. Employees are not going to really engage with this if you’re going to make them use their own data plan. You provide wired internet access to employees as a tool of work; do the same with in-building Wifi.

Human system component of solution

As with any human systems intervention, however, technology alone will not do the trick.

Workers need to be openly encouraged to use the system at work. As this is rolled out, the teams responsible need to make a concerted effort to promote this training system, both initially and as an ongoing reinforcement. This has to be more than a mass email to “Employees: All.” A nice promitional video will be helpful, but workers need to get introduced to it as well in a face to face meeting involving their front line management and perhaps their director. Give people a chance to ask questions and get answers.

“Bored? Brain-fried? Need a break? Tired? Stuck/writers block? Switch gears for a few minutes, play with your phone, so long as you’re using it to learn something.” Everyone should be actively encouraged to do this, and made to feel comfortable taking advantage of the policy.

Management at all levels, from the top down, needs to sets an example of welcoming this. Both in terms of words and in terms of concrete behavior. Management have to also be encouraged to (within reason) use the system and be seen using the system.

The tracked data that HR collects about how many hours the workers are engaged in learning what they are learning, and their completion stats can add to or supplement performance data for annual/semi-annual review. Workers should have visibility via some dashboard of the same sort of data that HR has summarizing their learning and training activities. That way, the worker can go into performance review meetings armed with data to demonstrate commitment to new learning and skill development. The learner can use this to start conversations about raises or about getting more resources or support for further deeper training or broadening of tasks. Conversely, managers can also look at the data to start their own conversations.


Workers have smartphones. Workers are going to look at them during the work day. If companies are smart and tech savvy, they can encourage ongoing training and development if they put out learning content in a way that is tailored to viewing through the workers’ smart phones. The effectiveness of this is reinforced if the company includes sucessful elements of gamification and social media and backs up the project with support from HR and management.

Swimming an Ocean: Motivation and Persistence in Massive Open Online Courses


As I’ve discussed in a number of recent posts, MOOCs, or Massive Open Online Courses are a big phenomenon lately. A big issue of discussion with regards to MOOCs is the question of how to support motivation and persistence in Massive Open Online Courses.

This is a form of learning that works very well for certain groups of learners, but, traditionally, not so well for others. This has been an issue for distance learning in general.

In particular, MOOCs work well for for autodidacts, or self-directed learners. These are people that are able to, and enjoy learning on their own, and who either don’t need a teacher. (I count myself as one of these eccentric and annoying creatures!) Such learners are able to learn regardless of the format, and the online aspect makes the learning process very convenient. The course materials can be accessed from a home computer, any time of the day or week.

It is a more difficult environment however for marginal students. These are the students who succeed at a decent rate in traditional universities largely thanks to support systems within the university campus, both formal and informal. Whether official tutoring services, or study technique mini-courses, mental and physical health support, campus social support organizations for different minority groups, unofficial study groups of students in the same specialization, or even just campus extra-curricular and social organizations. All of these features of the brick and mortar landscape, formal and informal, help support students and keep them mentally, socially, and psychologically engaged in the university community and in their courses.  An active area of inquiry centers on how to keep these sorts of students attracted enough to persist online with courses all the way through to completion.


Measuring Student Engagement in Massive Open Online Courses

One metric that is talked about a lot by critics with respect to MOOCs is the low completion rates. Typically only about 5-10% of “enrolled” students “complete” the class. This looks pretty bad on the surface.

However, we need to understand that these students are not all the same, and that enrollment in a free online course doesn’t necessarily mean the same thing as it does in paid enrollment at a university. These traditional statistics are somewhat misleading. Students enrolled in MOOC courses are looking for different things. Because it’s free, online, somewhat anonymous, students don’t have to commit money or time to move somewhere or commute to study. As a result, registering for a MOOC is not the same implicit commitment as registering for a paid course at the university. Different students are bringing a wide range of different levels of commitment, different intentions or goals. Even the same student it may differ from course to course.

Take myself as an example. I am “enrolled” in a few different MOOCs right now. (I’ve been between work contracts for a few weeks, so I’ve been taking advantage of the time to take some courses and expand my skill set. This may level off a bit as I start a new job next week)

One Coursera course,  in Interactive Programming in Python from Rice University, I have been actively engaged in the course activities. I’ve spent a good 10 hours a week or more, all told, watching all the lectures, doing all the assignments and quizzes on the official schedule, engaging in the course discussion forums, posting and engaging with other students. I am also a paying participant in the course. For a number of reasons. One, just to give a little kick of external motivation. Two, because I’m interested in certification in MOOCs as a personal informal research issue and would like the verified completion with honors certificate at the end for my LinkedIn.

Other courses, though, whether because of time and / or money limitations, or because the course is interesting, but overly challenging, or because the course is finished, I’m following along with the free and open online record of lectures and assignment exercises, but not fully engaged. For example, I’m also looking at a course in Functional Programming in Scala from Lausanne Polytechnique. For a few reasons. First, because it’s a trendy language used on a lot of sites like Twitter and Quora. Second, because it’s focusing on a more exotic programming paradigm of functional programming. Third, because the course is taught by Martin Odersky, a star computer scientist who created the language. It’s fascinating stuff, and I’m roughly following along with  the lectures, (though a little behind now) and taking a look at the weekly exercises. But I’m more peripherally involved. Again, for a few reasons. First, because the teacher and the presentation are very abstract, and because the course is intended for an advanced audience. Also  there’s not much support for low level things like guidance on syntax of the language, and I don’t have enough time to properly dig around on the internet, at least for now. Also, I’m still refreshing my knowledge of computer programming, so it’s not easy to process more exotic and abstract ideas right now. So I watch lectures to absorb some of the theory, and maybe next time it’s offered I can engage more. Or I can play with the exercises later when I have time.

Another course on Coursera I’m following is in Gamification from University of Pennsylvania, put on by a very engaging Wharton Business school lecturer, Kevin Werbach. It’s not a technically demanding course; it’s theory and c0ncepts mostly, but peppered with lots of practical examples. The course is already finished, so I’m following the lecture record with interest.

Some other interesting looking courses I registered almost as a bookmarking exercise for my later reference so that I can find the courses later in my account on Coursera. Probably not how Coursera intends for you to use the enroll button, but it’s a functional hack that works for me. I similarly have a few courses bookmarked on Udacity and EdX

So just to illustrate, people have different interests and goals. The percentage of people completing / people enrolled is based on the idea that everyone has the same goals. Which is not at all the case. Some want to master a new skill and get a certification they can try to leverage professionally, maybe to expand career options. These ones tend to spend more time, and tend to complete at a higher rate. Others just want to learn some new things seriously, but casually. Others are just poking around, trying out a few courses to see which few they’ll spend more time with. So these completion rates are misleading. The more important metric is how much people are getting out of the course in relation to what they hoped to get out of it going in. And on this metric, many or most are getting as much or more out of it than they intended.

That said, there is doubtless room for improvement in making courses so that more people will engage in them to a deeper, more persistent manner. And this is where I’d like to turn to now.

Again, I’d like to illustrate from my own experiences, particularly with the interactive programming in Python course. The course had lectures, weekly graded multipler choice and short answer exercises, and  weekly mini-project programming challenges. The programming challenges were typically games. An early project was a textr based game of Rock-Paper-Scissors-Lizard-Spock (a nerd-variant of the popular game Rock Paper Scissors). Each week, this stepped up in difficulty, through programming a version of Pong, a version of memory, a visual game of Blackjack, and finally, a two week project building a space shooter game based on Atari Asteroids. Here is my final submission, by the way:

People started having trouble when it got to the Blackjack game. This was the week when the programming paradigm of “Object Oriented Programming” was introduced. Coming from an abstract mathematical sort of background, I was able to grok the basics of this pretty easily, and managed to finish the project early. As someone who is also from an education background, I decided to go onto the course discussion forums to try to help out anyone who was having difficulties. There was a  lot of chatter during that particular week from people thinking about quitting. I spent a lot of time on the weekend that project was due on the forum trying to talk people down from the ledge and  trying to help different strangers who were stuck. It was a rewarding experience. But it illustrates the fragility of the online environment for those who are borderline.

Supporting Engagement in Massive Open Online Courses

So this is a big topic, how to support learners who are less auto-didactic, less internally motivated than someone like me. I’ve always been someone who benefitted from a good teacher, but didn’t really need one. Online works  naturally for people like me. But what about for others? There are a few different ideas.

More development of discussion forums. This is a great option currently used by different courses. It helps to build a course community and gives students a forum to discuss, exchange ideas, ask questions, get answers. People like online discussion forums, and they play a useful role in the educational experience. The key is to motivate possibly borderline students to engage on the forums and to make sure that the forums are a welcoming, friendly, and safe place to try out ideas and learn. This takes promotional efforts from the instructors to spend time encouraging the use of the forums, and periodically reminding about the existence and usefulness of the forums. It also requires volunteer or paid TAs to help monitor and moderate the discussions.

Another option currently enabled by some MOOC providers is local meetups and other similar projects. Coursera for example enables the ability to try to organize face to face group meetings of people in the same city who are taking the same course. In this way, people could theoretically get together to form real world study groups.

Another idea would be assigned buddies or groups made up of other students. Whether for all or for those who ask for it as an optional support. One possible way to incentivize this into a voluntary effort would be to have a survey at the beginning of the course where people can identify their level of familiarity with the subject going in and their level of confidence in their ability to succeed. People with little experience and low confidence could be directed to a page where they can opt in to being paired with a volunteer student with more experience and confidence. Conversely, those with more experience and confidence could be directed to a page where they can opt to be put into a pool of people who will be randomly paired with a few students who anticipate needing help. It could be entirely voluntary, but incentivized for example with marks. If you opt in to this and actually help people out, then you can get a few bonus marks that can make up for a bad performance on an assignment or quiz.

Another option to make things more lively and interactive than discussion forums would be something like Google Hangouts. People could talk face to face about ideas in the course. This would work best probably with arts and social sciences content, but could find application more generally too.

Finally, another option is to have some minor collaborative exercises in the course where you need to work together with other enrolled students. There would be logistical challenges to dealing with this, for example, if the random forming of teams included a number of more peripheral students not taking active part in the assignments. But if you can find solutions to these challenges, the social, collaborative aspect could help to engage many in the course.


New ideas and technologies for learning and performance support

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