Realizing the Potential of the Tin Can API

By Joseph Suarez

Each time a major eLearning authoring tool or LMS vendor announces they are (or will be) supporting the Tin Can API, the eLearning community can be heard giving a simultaneous cheer and moan. Why would the “next generation of SCORM” cause such a mixed reaction? Here's my interpretation.

Cheers:
In the short term, Tin Can support is perceived as a good thing because it means organizations will theoretically have the capability to migrate from SCORM to what's being promoted as a highly improved standard for recording and tracking learning experiences. With vendors adding Tin Can support to their products, it signals a quick and wide adoption of the new standard. This is a cause for celebration to some.

Moans:
However, unless the promised improvements of Tin Can are also eventually realized, the future won't likely be any brighter. For years, thought leaders in the industry have been calling for radical change that moves us beyond the simple LMS completion checkmarks SCORM has become notorious for. They would argue that to adopt Tin Can only as far as to replicate SCORM’s limited functionality completely misses the point.

Without getting into the history of SCORM, it’s fair to say that how it is widely used today was only part of what was originally imagined. Julie Dirksen described the missed opportunities of SCORM with this analogy over on the official Tin Can API blog:

“Basically, it’s like someone having a $50K budget for a new car, and spending a thousand dollars on the actual car and the other forty-nine thousand on making sure we always have a parking space.”

Chicken & Egg
Remember when fuel-efficient hydrogen cars were supposed to be the next wave of the future? A major problem keeping the idea from taking off is a classic chicken-and-egg dilemma. No one wants a hydrogen car if there are no refueling stations around, and no refueling stations are going to exist without a customer base of hydrogen car owners.

I see Tin Can as having a similar dilemma. If we don't eventually see and experience examples of Tin Can utilized to its full potential, how are we going to create enough market demand to pressure vendors to fully empower their tools with that ability? Yet how can the full potential of the Tin Can API become mainstream if that capability isn't within arm’s reach of developers?

It’s not an insurmountable problem by any means. It just requires some pioneering developers to enlighten the rest of us to what's possible. Fortunately, that may have already has begun through a Tin Can API prototypes page. It’s worth bookmarking and checking up on in the hopes of doing more cheering down the road.

What are your thoughts on Tin Can's potential?

Designing eLearning for Cognitive Ease

By Shelley A. Gable

I recently started reading Thinking, Fast and Slow by Daniel Kahneman, and the chapter on cognitive ease offered all sorts of implications for eLearning design.

Promote a good mood.

The Finding: Kahnemann describes a study in which participants needed to rely on intuition to complete a task. The study found that participants in a good mood doubled their accuracy, while those in a bad mood performed poorly. This, combined with additional discussion in the book, suggests that a bad mood creates cognitive strain, and a good mood promotes cognitive ease.

Implications for eLearning: Although we may not have control over a learner’s day or personal life, perhaps there are things we can do to make learners smile from time to time. Consider a dash of appropriately placed humor, a relatable and/or inspirational story, and graphics that create a warm, positive tone.

The amount of time spent on eLearning may influence mood, too. Long lessons may leave learners wondering if they’ll ever end, while a series of short lessons can help create a sense of progress. Shorter lessons can also help prompt learners take a brief break and re-energize if they’re feeling mentally fatigued.

Ensure repeated exposure to critical content.

The Finding: I took a social psychology class several years ago and clearly remember this mantra: “familiarity breeds liking.” Kahnemann’s book explores this concept, describing studies in which participants were exposed to messages repeatedly over time. Repeated exposure seemed to increase participants’ liking and trust in the message.

This reminds me of the concept of spaced learning that Hermann Ebbinghaus – one of the earliest researchers of learning and memory – introduced in the 1800s. Spaced learning suggests that we retain newly learned knowledge longer when taught repeatedly over a period of time.

Implications for eLearning: Two simple ideas come to mind. First, we can take advantage of the flexibility eLearning offers to spread out training. Instead of conducting four hours of training within a single day, consider dividing it into one-hour sessions over four weeks, for example. Although the content will likely advance from one session to the next, this spaced approach would allow for reinforcing core components over time.

Another consideration is to ensure that core messages are repeated at every practical opportunity (this doesn’t have to mean repeating it verbatim every time). For instance, I recently worked on some customer service training where anticipating customer needs was a core principle. Although the training teaches a variety of tasks and behaviors, nearly every scenario prompts learners to pause to anticipate needs and then reinforces the impact of doing so.

Create clean visuals.

The Finding: The book describes a study in which participants were asked to solve a case study problem. For one group, the problem included a company name that was difficult to pronounce, while the other group’s version had an easy-to-pronounce company name. Everything else about the problem was identical. Interestingly, the problem-solving success rate of participants with the easier company name was significantly higher than that of the other group.

The book also describes similar studies where research participants working with low quality images or difficult-to-read fonts were also more prone to errors in completing tasks.

Implications for eLearning: The study about the difficult company name immediately prompted me to think about the names I assign to characters in the stories and scenarios I write. This reinforces the importance of keeping those names simple.

It also reinforces the need to include crystal clear images in training. Occasionally, I encounter an eLearning lesson that has an image (often of a system screen) that is either too small to read easily or a bit unclear. While most of us can probably intuitively agree that this type of thing is annoying, the evidence in Kahneman’s book suggests that it directly impairs learning. In fact, one of the studies described would even suggest that problematic images continue to negatively affect learning, even after learners have moved past the image and it is no longer the focal point.

Did you notice other implications?

If you’ve also read Thinking, Fast and Slow, do you recall any “ah ha” moments you encountered while reading the book? And did any of those learnings affect your eLearning design? If so, please share!