While learning effectiveness still has a part to play in education, when we talk about workplace learning, it helps to focus on what we’re really designing for – learning transfer.

We don’t need people to merely learn better, we mainly need them to carry out their responsibilities with more efficiency and accuracy. To achieve that, they need to transfer what they have learned into (as Clark Quinn most eloquently puts it) “all appropriate and no inappropriate situations” in the course of their work.

I’m using this lens of learning transfer to explore some design fallacies that are distracting us from optimizing for better workplace performance.

Fallacy #1 – The transfer of learning is considered complete only when learners can recall the information provided in the learning intervention after the said training.

Wouldn’t it be a perfect world if we could avert workplace accidents just by getting all our employees to “recall” safety guidelines (and sing them to the tune of Twinkle Twinkle Little Star)?

That has never worked, right?

The transfer of learning, therefore, is complete only when learners have in some way demonstrated their ability and willingness to follow precautionary safety procedures and perform/trigger emergency protocol in case a safety incident occurs. In other words, such behavior has to become their second nature for the transfer of learning to be considered complete.

So essentially, since workplace learning is not for the sake of learning itself, the outcomes need to be measured against performance parameters and not knowledge parameters.

Fallacy #2 – All content should be created equal.

Once the goalpost moves from knowledge to performance, the lens with which we approach content needs to change too. Since workplace learning is aligned with performance outcomes, we need to wear the Performance Consultant hat instead of the Learning Consultant one – and a Performance Consultant’s aim is to enable learners to perform their jobs better.

We need to be able to segregate content into:

• Knowledge in the head – information that is vital to workplace performance, and needs to be retrievable from memory whenever and as many times as required; and
• Knowledge in the world – information that supports workplace performance and is fed as “cues” into the workplace environment so it can be readily referenced as and when required.

For instance, if the objective is for a set of learners to be able to use a new system, you need to segregate the system’s functions into:

• Actions that are integral to the work the audience does – The solution must be designed with the objective of enabling learners to perform these actions with various levels of automaticity in the real world. In other words, this is information they need to learn and retain in their memory.
• Actions that are “good-to-know” and/or may need to be performed as an exception – Considering that each of us only has finite storage space in our working memory, we can reduce cognitive load for learners by embedding this information in their work environment for easy access. The solution must therefore be designed with the objective of allowing learners to refer to this material with minimum effort when they need it, and in a form that allows them to perform the action “in the flow of work”.

Fallacy #3 – Excessive content and done-to-death page-turners.

For too long we’ve burdened learners with tons of content, and then added token knowledge checks that test recall. The result has been consistent – 80% assessment scores, but little measurable improvement in performance.

It’s time to turn this model on its head. If learners are expected to perform certain actions in the real world, we need to prime them to do exactly that – and allow them to fail in a safe space with no real-world consequences, over and over again, till they gain confidence and do it right.

Consider a parent teaching a child how to ride a bicycle. No number of theoretical sessions about the workings of a bicycle and the science of balance will enable that child to ride the bicycle. However, taking them out on a bike ride with training wheels on, can help them practice the skill of building balance in a safe space. And what’s more, falling a few times in a grassy field rather than a crowded street will help them understand and bear the consequences of mistakes in an environment that protects them from serious injury.

That’s exactly what we should be able to simulate in our learning programs – safe practice opportunities that incrementally build confidence and competency in the tasks tied to the performance outcomes.

And it’s only after we design these practice experiences that we plug in content.

But when we’re being so moderate and cautious with the amount of content we add, it puts that much more onus on us to ensure that it really counts!

What do learners really need in the form of content? The bare minimum…

• Causal explanations for why they’re supposed to do things a certain way, or in other words, mental models. It can be difficult to mug up a set of process steps, but once you understand the logic that drives the sequence for those steps, you’re much more likely to remember the process.
• Worked examples are another great way to cover varied contexts in which the content can be applied. This works especially well with novice learners. While we’re waking up to the importance of scenarios in learning, worked examples still remain a grossly underused instructional strategy. Narrative-driven examples that lay out a problem statement, the context in which it occurred, the application of a mental model to arrive at a solution, and the misconceptions that can imperil the desired outcome, are far more useful to learners than abstract concepts chunked into pages and pages of eLearning courses.

Arguably, those two forms of content are all learners need, apart from insightful and consequential feedback embedded into practice exercises.

To conclude, I’d just like to reiterate that, unlike students, workplace learners are neither required nor expected to “learn” – they’re expected to “perform”. For the longest time, learning designers have been made to mimic strategies used in education. Unlearning is never easy, but we need to start somewhere. Let’s start simply by asking ourselves at every step of the design phase – “Does this enable my audience to perform their jobs better?”

The post Design Fallacies Getting in the Way of Learning Transfer first appeared on The Upside Learning Blog.

Aren’t we supposed to remember things that we naturally take an interest in?

Turns out, it’s not that simple. ‘Taking interest’ in something, by itself, is not enough to codify it into long-term memory – and to be honest, that’s perfectly fine. Not everything needs to be remembered long-term (I’m all for a de-cluttered brain). But for the things that do, we need to be more deliberate about designing intelligent learning interventions that leverage memory-related research to enable long-term retention of key information.

In my previous blog within this series, I made a case for leveraging spacing to counter the Forgetting Curve. Spacing is an incredibly versatile tool that can be incorporated at every stage of a learning intervention to maximize its effectiveness.

Figure 1: Stages of an Effective Learning Intervention

Spacing in the Encoding Knowledge Phase

Content Dripping

Microlearning has been quite the buzzword these past few years. It relates to breaking down dense content into easily digestible nuggets. However, one important aspect that has by-and-large been ignored, is that of scheduling these content nuggets and delivering them in stages.

Nuggetized learning, if not spaced, is as good as creating one long, complex dump of content, which overwhelms learners. The spacing between nuggets, if planned intelligently, can help learners get comfortable with one level of knowledge before proceeding to a next one.

It also creates a routine over time, allowing learners to process and play with the knowledge they have already gained, before moving to the next set of (possibly more complex) topics.

Spaced Repetition

As we know by now, repeated exposure to a concept over a period helps move it to long-term memory. This strategy becomes even more effective when the information is presented in a different context each time – i.e., the same concept can be defined in one nugget, presented with an example in a second one, and as a case study/scenario in a third one.

On one hand, the repetition increase familiarity with the concept, while on the other hand, the variety of contexts deepens the learners’ understanding of it, making it easier for them to apply it in different situations.

Spacing in the ‘Providing Contextual Practice’ Phase

Spaced Practice

Practice that requires learners to retrieve learning from memory, has been found to be a much more effective mode of remembering that learning, than revisiting the content repeatedly.

Spacing this retrieval practice effectively is a great way to convert knowledge into long-term learning. According to the book ‘Make it Stick’, when practice is spaced, learners are required to “reload or reconstruct the components of the skill or material anew from long-term memory rather than mindlessly repeating them from short-term memory”. This process helps learners build stronger connections between various aspects of the topic, in turn reinforcing its meaning and varied contexts.

Practice Loops

One of the most common learning requirements organizations have, is to build proficiency amongst their workforces. This means they should be able to apply multiple skills in combination, for achieving desirable outcomes.

Loops of practice essentially mean an activity or a set of activities that is repeated over and over, until you reach proficiency in them. In such a case, the first level could involve activities that are designed to teach an individual skill in isolation. As the learners get better at applying each skill in isolation, the next level could involve more complex activities that require learners to combine multiple skills. The pace at which this progress happens could be completely customized, based on individual skill and required proficiency levels.

If these loops of practice are spaced meaningfully, they allow for some forgetting time and reflection time, helping make the progress through these loops more significant and long-lasting.

Spacing in Testing

Testing as a Tool for Learning

We are used to seeing testing as a measure of the effectiveness of the preceding learning. How about flipping the context and seeing it as a tool that allows you to compare ‘the feeling of confidence’ to the actual ‘demonstrated level of proficiency.’

When used in that context – regular, spaced testing can provide insights into the gaps in learning, the movement of individuals between levels of proficiency, and an insight into the skill inventory within a team/organization.

In Conclusion…

The expectations from learning have evolved drastically in the past few years – from learning-centric outcomes to performance-centric ones.

It’s time we took off our blinders and took a good hard look at the bigger picture – and if it scares us, we’re better off ditching feeling-based learning design in the favour of research-backed findings that can help us achieve more measurable outcomes.

Spacing is the tip of the iceberg; it is time to explore more deliberate tools and frameworks that have shown measurable results in creating an impact on performance.

References:

• Make it Stick: The Science of Successful Learning (Book by Henry L. Roediger III, Mark A. McDaniel, and Peter C Brown)
• Quinn, C. N. (2011). Designing mLearning: Tapping into the mobile revolution for organizational performance.
• Spacing Learning Events Over Time: What the Research Says (Will Thalheimer)
• Storm, Benjamin C. “The Benefit of Forgetting in Thinking and Remembering.” Current Directions in Psychological Science, Vol. 20, No. 5. October 2011.
• https://people.ucsc.edu/~bcstorm/s_2011b.pdf

The post Incorporating Spacing within Digital Learning Interventions first appeared on The Upside Learning Blog.

When I think back on my time in school and college, some of the most vivid memories are of cramming for exams through the night—running on pure adrenaline, fueled almost completely by anxiety. More than 20 years later, I still get nightmares about blanking out during an exam, and I’m pretty certain I’m not alone. After years of formal education where academics were the primary focus, how much did I retain? Let’s face it—very little. The only things we tend to retain from our formal education are things that we’ve been able to apply in some form during life and work: concepts that we’ve revisited in different forms repeatedly and have had a chance to apply in real-life situations.

This can be attributed, at least in part, to what Hermann Ebbinghaus described as the “forgetting curve”, which talks about how we tend to forget newly acquired information as time passes. Though Ebbinghaus’ theory has been criticized for various reasons, multiple researchers have attributed the encoding of information into long-term memory to how often someone is exposed to that information. An excellent piece of related research is Benjamin Storm’s paper titled “The Benefit of Forgetting in Thinking and Remembering”, in which he elaborates on the way our brains function, by stressing the fact that “the ability to retrieve and generate information that is wanted, relevant, and appropriate is made possible by the ability to inhibit, and thus forget, information that is unwanted, irrelevant, and inappropriate.”

What Does This Mean For Learning Design?

One of the most effective ways to improve the way we learn is to “interrupt the process of forgetting” (Brown, et al., 2017), which means retrieving the information from memory multiple times at spaced intervals. In his book Designing mLearning, Clark N. Quinn elaborates on two different applications of spacing in learning design: spaced practice (allowing learners to apply the information in different scenarios at spaced intervals to cement concepts), and spaced testing (reactivating the information by presenting learners with tests that trigger recall at spaced intervals). Not only does taking these approaches make the memory for the information last longer, but it also makes subsequent retrieval of this information easier. One marked benefit of this is that as the information gets more readily retrievable from memory, the information can be applied to varied contexts and situations more easily.

According to Hintzman, Dempster, and Russo et al., there are three primary reasons why spacing of learning can be effective. Let’s look at them from a learning design perspective:

• Encoding variability—taking information and recording it in long-term memory
  The encoding variability theory says that if the information is repeated multiple times at spaced intervals through a variety of modalities, there is a deeper encoding of this information, leading to long-term retention and a deeper understanding of the underlying concepts and relationships.
• Proficient processing—leading to long-term memory success
  Research has established that repetitions in close succession are relatively less efficient in achieving long-term memory encoding than repetitions that are spaced. This can be attributed to boredom, mental fatigue, or the familiarity trap that comes into play when you read the same information repeatedly in close succession. Spaced repetitions allow for some forgetting between interventions, creating more memory connections that make retrieval easier and more contextual over time.
• Learning-strategy adaption—learning through retrieval failures
  It is now believed that since the spacing of learning interventions allows for some amount of forgetting, learners are more likely to fail in the initial attempts at retrieval. This acts as an inducement for learners to process information more earnestly and elaborately.

Does This Mean That We Have Found The Magic Sauce?

In a nutshell—no! Spaced retrieval by itself is of no value unless there’s an effective learning strategy woven around it. It is, at best, an enabler for retention, not a stand-alone learning solution.

In today’s business environment, most organizations are looking to L&D to be result-driven and are insistent on seeing its impact in terms of RoI. This means the role of L&D has clearly shifted from “teaching” learners concepts to “enabling” them to perform in a competitive work environment. In my next article, I’ll try to delve into how spaced learning can be leveraged in different forms within various learning modalities and delivery methods to support better workplace learning outcomes.

References:

• Brown, Peter C., Henry L. Roediger III, and Mark A. McDaniel. 2017. Make It Stick: The Science of Successful Learning. Cambridge, MA.: Harvard University Press.
• Quinn, Clark N. 2011. Designing mLearning: Tapping into the Mobile Revolution for Organizational Performance. San Francisco: Pfeiffer.

This blog was previously published on elearningindustry.com

The post Why Learning Design Should Incorporate Spacing first appeared on The Upside Learning Blog.

Organizations are looking for ways to align their learning initiatives to their business goals. It’s no surprise then that the focus of learning seem to be gradually shifting towards “performance” and not just “awareness”. Organizations are looking at improved individual performance as a desired learning outcome, indicating an increased scope for immersive and long-term learning interventions. Learning campaigns incorporating blended learning solutions that engage diverse learning forms and environments, and are spaced out over a longer duration seem to be the perfect answer.

When we look at any business goals, they are invariably about some form of change. So, if organizations want to align learning to their business goals, we need to start looking at blended learning solutions as a tool that supports Change Management – be it for products, processes or culture. However, the success of such initiatives is highly dependent on how well the workforce understands the purpose of change, and how well they adapt to the actual change process.

Lewin’s 3-Step Change Model provides a great framework Change Management, and can facilitate strategic planning for blended learning solutions like Learning Campaigns, to support the change process. With three simple steps, it captures the essence of how Change Management can be initiated and rolled out for maximum effectiveness.

So how can we support each of these phases of change by wielding the instructional value of a learning campaign?

The key lies in identifying the needs that each of these phases creates within the organization’s workforce, and aligning learning objectives to address them.

The graphic presented here identifies the feelings associated with each phase of Change Management, and attempts to link it with derived objectives from the viewpoint of a campaign. It then goes on to explore some possible learning components that best support the achievement of these objectives.

Having a framework that clearly identifies the phases of Change Management allows organizations to anticipate learner needs, and plan for them effectively.

As learning practitioners, we’re not new to the phrase “training is not always the solution”. True! That is precisely why we need to find ways to take learning outside the realm of classroom training and digital learning.

Learning design is coming of age, and it’s time we saw it as a sub-set of performance management. Combining media formats, environments, technologies, and modes of delivery allows learning design to be truly dynamic, and impact more areas of workplace performance by facilitating and supporting Change Management.

The post Designing Learning Campaigns to Support Change Management first appeared on The Upside Learning Blog.