Evans and Taylor (Evans & Taylor, 2005) define scenarios “as stories focused on a user or group of users, which would provide information on the nature of the users, the goals they want to achieve and the context in which the activities will take place. They are written in ordinary language, and are therefore understandable to various stakeholders, including users. They may also contain different degrees of detail.”

J. Carroll (Carroll, 1999) attributes five characteristic elements to e-Learning scenarios: they include or presuppose a setting, they include agents or actors and each agent or actor has typically goals or objectives; every scenario has at least one agent and at least one goal. Finally all scenarios include sequences of actions and events, things that happen and change the scenario setting.

In our opinion, it is best to use interactive scenarios to support active learning strategies such as problem-based or case-based learning. It normally requires a learner to navigate a storyline/narrative across a temporal space (time), leading to an exploration of the aspects of and eventually resolution of the problem (posed in the scenario). Navigation of a scenario leading ‘decision’ points of the scenario requires the application of knowledge, critical thinking and to an extent, problem solving.

For workplace learning, scenarios can be used for developing skills that require decision-making based on a ‘set of principles’. They can be used for soft skills such as selling, communication, etc. Oftentimes, the word ‘scenario’ is incorrectly associated with EAT (Enterprise Application Training) simulations and refers to the setting of the scene that requires a particular procedure (being simulated). It can help to think of scenarios as a type of social simulations (think of the game ‘The Sims’).

Typically outcomes that involve decision making based on a ‘principle set’ are best served with scenarios as an instructional strategy. We often recommend the use of scenarios for technical/professional knowledge and skills as well. If the learning outcomes you require are predominantly at a recall/comprehension level, scenarios are not the way to go; you’d be better off using a series of discrete displays and associated practice examples.

One aspect of simulations that applies equally well to scenarios is ‘fidelity’. How real does a scenario/simulation need to be to achieve the required learning outcomes? This is especially true of scenarios that involve soft/communication skills; the use of video (high fidelity) is more effective than the use of image/voice-over.

The cost of design and development of scenarios varies and depends on various factors (not limited to):

1. Learning outcome

2. Level of detail and branching

3. Decision point and feedback strategy

4. Use of media

There are definitely some positive implications for use of scenarios:

1. Allows designers to Influence outcomes in the affective domain (Bloom)
2. Encourages critical thinking and problem solving
3. Allow risk-free exploration of outcomes (similar to simulations)
4. Requires leverage of learned knowledge/skills to achieve favorable outcomes

On the other hand, there are some clear drawbacks:

1. Text/Audio/Images used for representation result in a substantial drop in fidelity. If you want decent fidelity, try to use video. (especially for soft/communication skill courses)
2. How the narrative/event/situation is written and elaborated is important, too little detail results in it being interpreted as superficial, too much detail will result in difficulties understanding and may cause learner to be diverted from key learning/observations.
3. Scenarios are developed best using an iterative approach and this involves significant time from both designers and SMEs.

Try answering these questions to determine if SBL is the right option? (Clark, 2009)

1. Are the outcomes based on skills development or problem-solving?
2. Is it difficult or unsafe to provide real-world experience of the skills?
3. Do your students already have some relevant knowledge to aid decision-making?
4. Do you have time and resources to design, develop, and test an SBL approach?
5. Will the content and skills remain relevant for long enough to justify the development of SBL?

DOs and DON’Ts

1. Ensure there are direct and real consequences for every action the learner takes.
2. Ensure learners know why they failed. Feedback should be more than ‘Correct/Incorrect, please try again’. This may require writing detailed individual options, each of which is a plausible response to the question posed or decision required.
3. When designing scenario-based-learning, it helps to keep in mind that feedback can be both discrete and continuous. Typically designers are inclined to use discrete feedback in scenarios, but could also consider the use of continuous feedback elements such as scores or levels (typically game-based learning elements used in SBL to engage and motivate better).
4. It follows that the designer would write customized remedial feedback for each option. Do not under-estimate the learner’s intelligence. Don’t add decision points simply to allow learner interaction with the scenario. Instead, the decision points must make them think carefully about the options available before choosing one. This requires each option to be plausible and relevant.
5. Allow the learner to go back into time as and when they choose (not only when presenting the scenario, but also at any other point in the learning experience). One of the critical skills we are trying to develop is ‘discrimination’, so in a sense, they should be able to stop going down a particular branch of the decision tree the moment they realize they are going wrong. This mimics real life closely, you’d stop whatever you were doing the moment you realize you are going wrong, not necessarily when told you are wrong.
6. Think about balance – visualize your scenario as a tree, it should be fairly symmetrical around the central trunk, and the branches should appear similar to each other. It is alright to have a few dead ends, but most paths through the branches should lead to an outcome of some sort.
7. In a way, a scenario is modeled based on a ‘theme’ or a ‘world’, as a result thematic consistency matters. Actions/decisions should ideally reflect the context of the world they are made in. It would be incongruous to have actions in the scenario not reflect the world in which they are made in.

The post Is Scenario-based Learning The Right Option? first appeared on The Upside Learning Blog.

Interactions built into eLearning must align with the content types and outcomes, without this essential alignment they cease to be meaningful to the learner and the learning process. This challenge is one that instructional designers and developers face on a day to day basis.

I am presenting a free webinar to assist designers and developers in understanding and overcoming this challenge – ‘The Design of Interaction for eLearning’ on 4th December at 3.30 PM (GMT) & 5th December at 11 AM (IST).

In this webinar, we will explore content types as defined by Dr. David Merrill and which of these types lend themselves to meaningful interaction. We will also present a case-study around the design of interaction for a specific content type.

This webinar is recommended for instructional designers, developers or those involved in management of eLearning content development projects, and those having a keen interest in the design of interactions for learning. On completing the webinar, you’d have an understanding of content types, which of those are appropriate for interaction design, and have seen the application of key design principles in interaction design for eLearning.

Registrations are now open, please visit the link below and pick your preferred time. Hope to see you there! http://www.upsidelearning.com/elearning-webinars.asp

The post Webinar – The Design Of Interaction For eLearning first appeared on The Upside Learning Blog.

Five reasons we think Glass is going to matter:

• Ubiquitous – always on, always there – we left computers behind on our desks when we left home or work, we carried our laptop and notebook computers around, called them portable but didn’t really use them everywhere, then came tablets/smart-phone like devices; we carry them around but we aren’t always looking at them, or using them. Glass changes this in a marked way, rather than your computer being something you carried, turned on and looked at when required, it is cumbersome. Glass overcomes that by being always on, and as something you wear, always there.In this video, it becomes apparent that the wearable nature of the device overcomes many of the physical limitations of a device that must be carried, and turned on/off (or woken/sent to sleep).This video gives a great example of ubiquitous always-on devices integrated with back-end systems is capable of
• Capable of Continuous Capture – With an inbuilt camera for capture photos and video, Glass offers the ability to capture the user’s field of view. This is a pretty unique feature, up to now our devices with capture capabilities have been cumbersome. While smart-phones have changed the game for photos and videos, it doesn’t really offer a first-person view unless one makes an attempt at it. Google Glass changes that; because of its wearable design the Glass camera has a field of view that is close to what the user is actually seeing. While there has been a flood of ‘how-to’ videos around for a while, Glass takes away many of the perceived barriers to first person field of view video (device not on person, or carried on person but put away, having to turn it on/waken it, and then accessing the device menu to access the camera hardware, etc.). While at this time, the video duration Glass can record is limited, an SDK would allow a developer to circumvent that.Google Glass: What It DoesImagine a future where you can choose to record (and broadcast/stream)video on the go related to any type of performance. This will eventually lead to video content generated on the fly, that is indexed and documents job performances ranging from mundane to highly complex that require well-honed skills.
• Truly Location Aware – desktop computers weren’t location aware, and neither were the portable computers, the advent of phones bought approximate location awareness to devices. Embedding GPS, which is far more accurate than network/cell-based triangulation in wearable devices offers a fine location that is far more useful than a coarse approximation, Glass will always know where it is. While one could visualize many use-case scenarios for location in a wearable device, nothing is as persuasive as being provided information just-in-time based on location. If you are in a museum, get information about what you are seeing, or have detailed information presented to you as you navigate a new workplace, or as one attempt to use a particular use of equipment; the possibilities are enormous.Just to get a good idea of what Google Glass is actually about –Check out the bit where the reviewer asks for directions or Oriole Park, shows what location awareness does for the device and applications. The entire video points to the utility of a device such as Glass.
• Ability to Augment Reality – augmented reality so far has been focused around smart phones; simply because AR depends on the ability to determine location and the orientation of a device, something only smart-phones equipped with sensors and GPS allowed till this point in time. Glass becomes perhaps the first bit of wearable kit that comes with sensors and a display (coupled with it always pointing at the user’s field of view). If looked at differently, Glass can be considered as nothing but a device that is meant to augment reality, something smart-phones weren’t designed to do. This ability to augment reality with information or graphics points to a future of applications for learning that are context-sensitive and actually useful.I love this example of a Google Glass application being used to augment a baseball game
• Truly Hands-free – computers and smart-phones need ‘manipulation’ with hands to make them productive, they need input devices that require physical dexterity and hand-eye coordination. Glass doesn’t use any sort of hardware input device, it depends on advanced voice recognition to interpret commands and act accordingly – what this has done is to free up the user’s hands.This video gives insight into how voice works on Google glass (this is a bit geeky)So now, you could actually be using your computing device while using your hands to ‘work’ on something. One of the simplest examples I can think of is where a Glass-like device is being used when you are fixing something wrong with a car. The display overlays what you see with technical information, repair instructions pertinent to your situation, all this while you continue to work with physical tools – performance support like we’ve never known it.

One of the arguments I often hear is that a comprehensive SDK isn’t in place yet, and making something meaningful from a learning perspective won’t happen until there is an reasonably easy-to-use and cheap SDK in place. At this point in time, any development on Glass is restricted to what you can dream within the boundaries of a fairly restrictive API. As an Android device you could possibly used the Android SDK for development, but other than try out some ideas, I don’t see it worthy of sustained development efforts.

To create something meaningful, robust and use-worthy, we need a Glass specific SDK – it seems that just might be happening shortly – Google seems to be readying to launch the Glass Development Kit .

The age of context is upon us, hardware and software are now driving towards providing computing capabilities in the context of use – whether it is work, play or learning. Performance support applications will change form and become context driven. I believe Glass is just the first wave of devices that will provide context, this will fundamentally change how we leverage learning technology in our day-to-day lives.

The post 5 Reasons To Pay Attention To Google Glass first appeared on The Upside Learning Blog.

Do download a copy, there are some very interesting and practical tips in there about how to enhance engagement in learning content.

Our team voted on these for the three top tips –

1. In eLearning, we often associate engagement with interactivity, quizzing, and games, but to be truly engaging, we must appeal to the learners’ natural curiosity first. Give them something to be curious about. This is best achieved through an instructional narrative: a story that drives the learning. Without it, the interactiv¬ity, quizzing, and games become busywork. – Amy Jokinen
2. If you do not have engaging content, there really is no need to have engaging media … it’s like putting a caramel coating on a rotten apple. No matter how enticing the outside is, or how it may attract, it’s still not going to be a good experience. Looks good, tastes bad, and no one comes back. – Sean Bengry
3. Your brain processes new information by linking it to already existing information. Use easily digestible and recognizable words and images. Too much jargon or highly unusual images will disrupt the flow of learning because the user will focus more on the odd language and less on the meaning of the content. – Amy Leis

Tying back to my post that listed thoughts on engagement in elearning, these three ally quite closely. Amy makes a good point using narratives and stories to drive learning, without which little engagement is possible. Sean on the other hand, refers the actual engagement value of the content itself, again some content is engaging while some is not. He also points to the fact that just great multimedia can never mask un-engaging content. Lastly, Amy makes a closer connection to how our brain works, perhaps engagement comes from meaningful content that can be assimilated by the brain.

The post More About Engagement first appeared on The Upside Learning Blog.

Some of the responses, in no particular order, make for interesting reading.

1. Engagement is dependent on the target audience and their goals. Engagement happens when goals are laid out and provided at a regular frequency, but those goals need to make sense to the audience in context of their learning and performance.
2. Engagement depends to an extent on whether the audience is familiar with the content; familiarity might require a different approach for engagement then for an audience that was starting from scratch.
3. Engagement is clearly a feeling, perhaps an emotional state. (cue more debate about the difference between a state of mind and an emotional state, definitely closely linked to one another)
4. Engagement can be a result of many elements, the relevance of material to the task/problem/point of need, how accurate that content is in context.
5. Much mention is made of the storytelling and how a good story engages without needing the sort of interaction and visual representations that are possible in the digital space. The art of narrative takes many forms in books, etc.
6. Engagement is tied to the interest of the perceiver, and relevance of the material begin presented.
7. Engagement requires that you allow audience to control pace, it should stimulate them to want more, continue the consumption of the module, and enjoy doing it all the while.
8. Engagement can be the result of many emotional/mind states, anticipation, curiosity or even fear, all can prompt engagement. An appropriate level of challenge is required of the learning material, too easy and there will be disinterest, too hard and the audience stops ‘getting it’ and drops off. Important to note that using elements such as fear in the design of learning may be counter-productive.
9. Engagement may require the suspension of disbelief, without which fictional worlds cease to be engaging.
10. Engagement requires that the learner/audience enter a state of ‘flow’ as defined by Mihaly Csikszentmihalyi. To enter a state of flow the experience should carefully balance between challenge and skill, move out of that zone, and flow ceases to be. This is especially true of digital learning simulations.

The post 10 Thoughts On Engagement In eLearning first appeared on The Upside Learning Blog.

It isn’t really a stretch of imagination to consider how this technology can be put for learning assistance or performance, just like designers subsumed personal computers, and now tablets and smart-phones. While it seems novel for some of us, such technology has been around for a while, for example Motorola makes a whole range of devices that could be classed as ‘wearable computing’.

Folks were already talking about and proposing applications for this technology way back in the nineties (Brian D. Rauch).  In addition to seeing technology companies attempting to make a market of these technologies, there is also significant research emerging from academia around this area, couple of interesting papers –

Using a wearable computer for continuous learning and support, (yes, Springer, costs money 40 USD!)

Maintenance Activities with Wearable Computers as Training and Performance Aids, by David Liu, The University of Queensland (PDF automatic download)

I think there are three reasons we shouldn’t ignore wearable technology for learning-

1. ‘Real Sharing’ – (life streaming becomes real, searchable, sharable streams of data BIG data becomes real)

   We’ve realized that learning can be better in a culture driven by sharing. As wearable computing allows us to actually stream data about every little activity we engage in – this will generate large volumes of data – what I like to think of as the real ‘big data’. This data can be considered as learning content, (quite unlike conventional ideas of what content should look like – video, audio, images, text, and now VR and AR) coupled with an understanding of context (next) can potentially transform learning and performance support at a very fundamental level.

2. The Provision of context

   Computer equipped with sensors carried on the person can sense the user’s environment, starting quite simply with knowing location, the sensors and pattern recognition would allow the device to know what you are doing, be linked up with agents in such a way that it knows what you are looking at (sort of like Google Goggles, the image recognition and search tool). Then there will be devices watching your activities in real-time (devices like Nike Fuel). Putting all this together, and making some semantic sense of it is going to be a huge challenge that is being addressed by software as I write this. It’ll be possible for individuals to have a second memory in the cloud that records anything and everything the user might choose to build into the life-data-stream’.

   As I mentioned before, machine (software/hardware) agents with the ability ‘to use devices/sensors to sense and make sense’ of these enormous volumes of data will allow us the holy grail – ‘context’, as a designer if you can capture context, it changes the playing field. You can now target learning material and support, at the right time, actually realizing what JIT means. All this support or content delivered to the user without any or little human intervention won’t really change how we ‘learn’ but will definitely change our definitions of performance support and learning content.

3. Natural Progression from mobile phones

   When mobile phones started out they were like cinder blocks or bricks, now they are tiny, packed with enormous computing ability, storage and a lot of other features that make them apt personal computing devices. Over the last few years, we have seen the incorporation of sensors that are not typically used for human interfacing (gyroscopes, accelerometers, GPS, IR, etc… great link for more) These sensors now allow the device much more capability, while this may not be human friendly, it will certainly be machine-friendly.

   Last but not least, we shouldn’t discount the continuous adoption of technology, just like we moved from regular wire-line phone services to wireless data predominant services, we will move from using smart-phones to wearable personal computing devices. The first wave of devices is only just beginning to appear on the market. In another few years a lot of us will be wearing computing, perhaps quite literally on our sleeves.

The question now for designers and developers is simple, where does one begin? From experience, we know early developer adoption comes at a price. Should we tie into developing for clearly proprietary platforms or wait for open source wearable computing options to emerge on the market. Learning designer and developers will eventually have to make some hard choices if they are to start taking advantage of this new ‘instructional technology’.

Some random but interesting stuff I dug up – worth a look.

Wearable Tech
A great collection of pictures of the devices, the range is truly astonishing, considering this is only the beginning of a wave of devices.

Wearing Your Heart on Your Sleeve: A Wearable Computing Primer (of sorts)
A great presentation that gives a great idea of what wearable computing actually is, and should inspire learning designers.

Wearable Technology: The Bra Designed to Shock Attackers
Some wearable technology is just plain weird, or perhaps I’m looking at it wrong.

Smart Body, Smart World: The Next Phase of Personal Computing
Sarah Rotman Epps makes some interesting comments about the nature of wearable technology.

9 Trends to Watch For in Wearable Tech
If it is worn, can trends be far behind?

The post Wearable Computing Technology In Learning first appeared on The Upside Learning Blog.

So why aren’t we telling more stories to assist in learning? The truth is, we are, but it’s not something that you are likely to find formalized in workplace learning. So where are the stories? They are being told in books, on TV shows, on blogs, on YouTube and in varied forms, they are probably being swapped in your workplace too. In offhand conversations, water cooler gatherings and at lunch. You can find stories everywhere, they form one of the backbones of how humans share experiences. Humans telling stories embed information in them, and when someone listens to stories, the brain searches for a deeper meaning beyond what the words are saying. Stories are unique in how they use language; story writers use words with visual, auditory, olfactory, and kinesthetic associations, to evoke feelings in readers.

Here is an interesting article about learning using stories. What really caught my eye was this sentence – “Stories do not come out of nowhere, nor do they simply represent an experience or an event as it actually happened. Rather they are always a representation of that, and as such are a very rich means for accessing inner truths – those ideas, beliefs, and commitments that an individual holds dear.”

I have a suggestion for the business leaders out there, tell stories, encourage the telling of stories. Stories allow the creation of a culture, an attitude amongst co-workers, they eventually become part of the ‘mythology’ of the company. Great companies seem to have engaging, interesting stories told about them, both inside and out.

Some fellow team-members pointed this out to me – http://inform7.com. Looks like something we could use for learning. Tell stories using it.

The post Telling Stories first appeared on The Upside Learning Blog.

Why do I think this way?

We are falling back on the most portable form – HTML, which cannot compare to Flash. HTML in its current form is really incapable of providing the sophisticated artistic and media abilities that Flash provided. It’s like building experiences for today’s technology using a markup language that is ancient, and in all likelihood obsolete before becoming a standard (HTML5). Portability demands scaling of experience, that is really not happening with HTML5 unless it really gets into the game and there are several authoring solutions that ‘designers’ and not ‘coders’ can use.

Why doesn’t the courseware we make scale across platforms as we have come to expect from most mobile/cloud applications? Scaling of experience in my eyes is simply being able to leverage the hardware and software feature-set that the platform provide i.e., the courseware/content should be able to use the feature-set to enhance the experience, not just provide a baseline function. So if I were looking at a course on a Nokia Symbian phone vs. a Apple iPad, I’d expect the iPad to provide a much better user experience than on the Symbian phone simply because it is capable of much more. Developers are looking at it the other way – you want it to run on Symbian, that the is the least common denominator, so expect that experience on all devices. Why? It’s probably about time and money, it mostly always is.

Buyers/Users of eLearning are giving up on developing engaging interactive learning experiences and attempting to replicate a more basic experience across multiple devices, multiple platforms. I am not sure this is the right way to go. Sure, it’s great to have courseware that runs across platforms and devices, but is that really what you need? For just-in-time, simple to read and use information, mobile delivery is a great strategy to support performance and learning; but there will always be learning needs that must be addressed by courseware that does not require mobile delivery, what counts there is an engaging, interactive experience. Simulations, games, scenario-based learning, the options are huge. Choose wisely.

The post The Genericization Of Content first appeared on The Upside Learning Blog.

There is a bit of marketing claptrap; and it may require the installation of Silverlight, but the idea of using tablets in-flight and its implementation is nice. Gives clues on what ‘mobile learning’ is actually about – providing information and connected tools at the point of need.

The post Learning On Tablets At Emirates Airlines first appeared on The Upside Learning Blog.

Algorithmic generation of content has existed for a while now, most commonly used in games to generate content used to populate the game environment; I stumbled on this great wiki that lists the ‘Algorithms for Procedural Content Generation’, it makes for interesting reading. So how long before we have algorithms that are setup to create ‘learning material’ by constantly monitoring streams of user generated content, monitoring individual context. Then actually delivering this content to users using social or environmental awareness in some form. It’d probably mean the end of ‘training content’ as we know it. If and when such a time comes – curation will become what humans do, content will be created by machines. In the future of learning, being able to find, rate, package, even ‘create’ content will be the domain of algorithms assisted by humans, rather than the other way around. The first inklings of this are already visible, in the form of search, discovery and sharing services such as Scoop.it and Summify and a whole lot more. Here is an entire list of such services.

While these services are helping us deal with the information overload, they still rely on human users to generate the content that the services reference, rank and share. The algorithms the services use don’t really create the content, but that will change soon. We will have algorithms that actually glean information from various streams and write content. I’m inclined to agree with Dan Woods mentions in his article at Forbes:

• Algorithmic content creation will play a role in creating types of content that we are not using now.
• Algorithmic content creation will accelerate and enhance the traditional process of content creation.
• Algorithmic content creation will support new types of hybrid content that is collaboratively created by humans and machines.
• Algorithmic content creation changes the economics of publishing.
• The automation pioneered by algorithmic content creation will improve traditional publishing.

These observations apply ‘learning content’ just as they do to publishing. It’ll be interesting to see how these new tools for content generation will impact training.

The post Algorithmically Generated Content In Learning first appeared on The Upside Learning Blog.