Quick Guide: Brinkerhoff’s Success Case Method in Workplace Learning

How to use Brinkerhoff's Success Case Method in workplace learning?

How to Use Brinkerhoff’s Success Case Method in Workplace Learning

There are a lot of different frameworks that organisations use to evaluate the impact of their workplace learning initiatives. The Kirkpatrick model and the Philips ROI model may be the most common ones. While the Brinkerhoff’s Success Case Method is perhaps a less known one, it can too provide value when used correctly. In this post, we’ve compiled a quick overview of the method and how to use it to support L&D decisions in your organisations.

What’s the Brinkerhoff’s Success Case Method?

The method is the brainchild of Dr. Robert Brinkerhoff. While many of its original applications relate to organisational learning and human resources development, the method is applicable to a variety of business situations. The aim is to understand impact by answering the following four questions:

  • What’s really happening?
  • What results, if any, is the program helping to produce?
  • What is the value of the results?
  • How could the initiative be improved?

As you may guess from the questions, the Success Case Method’s focus is on qualitative analysis and learning from both successes and failures on a program level to improve for the future. On one hand, you’ll be answering what enabled the successful to succeed and on the other hand, what barred the worst performers from being successful.

How to use the Brinkerhoff Method in L&D?

As mentioned, the focus of the method is on qualitative analysis. Therefore, instead of using large scale analytics, the process involves surveys and individual learner interviews. By design, the method is not concerned with measuring “averages” either. Rather the aim is to learn from the most resound successes and the worst performances and then either replicate or redesign based on that information.

So ideally, you’ll want to find just a handful of individuals from both ends of the spectrum. Well-designed assessment or learning analytics can naturally help you in identifying those individuals. When interviewing people, you’ll want to make sure that their view on what’s really happening can be backed with evidence. It’s important to keep in mind that not every interview will produce a “success case”, one reason being the lack of evidence. After all, you are going to be using the information derived with this method to support your decision making, so you’ll want to get good information.

Once you’ve established the evidence, you can start looking at results. How are people applying the newly learnt? What kind of results are they seeing? This phase requires great openness. Every kind of outcome and result is a valuable one for the sake of analysis, and they are not always the outcomes that you expected when creating the program. Often training activities may have unintended application opportunities that only the people on the job can see.

When should you consider using Brinkerhoff’s Success Case Method?

It’s important to acknowledge that while the method doesn’t work on everything, there are still probably more potential use cases than we can list. But these few situations are ones that in our experience benefit from such qualitative analysis.

  • When introducing a new learning initiative or a pilot. It’s always good to understand early on where a particular learning activity might be successful and where not. This lets you make changes, improvements and even pivots early on.
  • When time is of the essence. More quantitative data and insights takes time to compile (assuming you have the necessary infrastructure already in place). Sometimes we need to prove impact fast. In such cases, using the Brinkerhoff method to extract stories from real learners helps to communicate impact.
  • Whenever you want to understand the impact of existing programs on a deeper level. You may already be collecting a lot of data. Perhaps you’re already using statistical methods and tools to illustrate impact on a larger scale. However, for the simple fact that correlation doesn’t mean causation, it’s sometimes important to engage in qualitative analysis.

Final thoughts

Overall, Brinkerhoff’s Success Case Method is a good addition to any L&D professional’s toolbox. It’s a great tool for extracting stories of impact, telling them forward and learning from past successes and failures. But naturally, there should be other things in the toolbox should too. Quantitative analysis is equally important, and should be “played” in unison with the qualitative. Especially nowadays, when the L&D function is getting increased access to powerful analytics, it’s important to keep on exploring beyond the surface level to make the as informed decisions as possible to support the business.

If you are struggling to capture or demonstrate the impact of your learning initiatives, or if you’d like start doing L&D in a bit more agile manner, let us know. We can help you in implementing agile learning design methods as well as analytical tools and processes to support the business.

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How to Write Good eLearning Questions?

How to write good elearning questions?

How to Write Good eLearning Questions?

Wherever there’s learning, we often need some kind of assessment. While learning analytics have evolved considerably over the past few years, often the easiest method to try to capture learning is through asking questions. However, it’s good to keep in mind other formative assessment methods, that might be better in evaluating long-term learning outcomes. Regardless, there are certain elements to asking questions as well. Naturally, you’ll want to be sure that you’re evaluating learning, not just the ability to regurgitate facts or recall statistics. Thus, we put together a quick guide on how to write good eLearning questions. Here you go!

1. Align your questions with the learning objectives

Whenever you’re writing questions, you should keep in mind what the learning objectives of the activity are. When going through subject matter and material, it’s easy to pick on certain things (especially facts, figures, numbers) in the hopes that they would make good questions. However, often these questions don’t go beyond the trivial level, and thus don’t support the learning goals either. Overall, we should focus on the use of knowledge, rather than the ability to recall content. Hence, you should focus on writing eLearning questions that require understanding the concepts and ideas, as well as practical applications.

2. Use a variety of question types

Simple multiple or single choice questions are probably the most used ones. However, there’s no reason you should limit yourself to those. Question types like drag-and-drop, fill-the-blanks, sorting activities and open-ended questions all work well and are easy to execute. The added variety has two benefits. Firstly, it may help in engagement. Instead of mindlessly clicking through alternatives, learners have to focus on the questions type first, and then the content. When you get people to focus, they are more careful, which means you’ll get better answers. Secondly, using multiple different eLearning question enables you to ask about the same thing from different perspectives and in different ways. This helps to really understand whether the learners truly understood the concept or are just working with surface level knowledge.

3. Keep the questions clear and concise, avoid negative

The aim of assessment should naturally be to test whether someone has understood your content. Now, if your learners have trouble already understanding the questions, you’ll just make everyone frustrated. The learners are having trouble answering and you can’t be sure whether it was the content or the question that wasn’t understood. So, keep your eLearning questions clear and concise. Avoid ambiguity, “circling around” and unnecessary detail, and be direct.

Also, you should try to avoid negative phrasing of questions wherever possible. Studies show that negatively phrases questions are more difficult to understand and thus result in more frequent mistakes.

4. Provide valid answer options without free clues

This is probably the part where it’s the easiest to cut corners when you’re under a time pressure. When designing the alternatives that the learner is supposed to pick from (in e.g. a multiple choice question), we’ll naturally already have the question and the right answer ready. It’s probably easy to just come up with random options for the wrong answers, which are also referred to as distractors. But you really shouldn’t do that.

Good assessment tries to eliminate the possibilities of guessing. We often say that “it’s not the correct but the incorrect answers that determine real knowledge”. By providing “bad” alternatives or silly distractors, you’re effectively making it a whole lot easier to pick the right answer from the rest. So, ensure that all the options could at least seem plausible to someone who had not learned the topic. Also, make sure that all your alternatives are roughly the same length and same phrasing. We human beings instinctively look for visual cues when trying to solve problems. By keeping things uniform, you’re not giving away unnecessary free clues.

Final words

Overall, writing good eLearning questions is not rocket science by any measure. A good rule of thumb that encapsulates a lot of the previously said would be “keep it clear and don’t try to trick the learner”. It’s very easy to sabotage one’s own “data set” by asking silly questions, but that only comes back to haunt you as an L&D professional, as you won’t get an accurate picture of the knowledge and skill levels in your organisation. So, the next time you’re designing an eLearning quiz, keep these 4 points in mind!

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How to Use Data to Support Face-to-face Training?

How to support face-to-face training with data?

How to Use Data to Support Face-to-face Training?

Organisational learning and development is becoming increasingly data-driven. This is fuelled by the need to demonstrate impact, be more effective and direct resources more efficiently. With the advent of new learning technologies and platforms – many of which come with built-in analytics capabilities – we are increasingly better equipped to measure all kinds of learning in a meaningful way. However, for the most part, the collection and especially the use of this data has been limited to only digital learning experiences. But there’s no reason to draw that kind of limitation. In fact, traditional face-to-face training could benefit greatly from having access to data and analytics. So, let’s explore how we could support face-to-face training with data!

Current challenges with face-to-face training

Face-to-face training has its fair share of challenges ahead. On one hand, it’s rather expensive, once you factor in all of the lost productivity and indirect costs. However, cost becomes less of an issue as long as you can demonstrate impact and value. And that’s perhaps a business challenge. The real learning challenges, on the other hand, are related to the delivery.

Overall, face-to-face learning is not particularly personalised. Trainers are often not aware of the existing knowledge of the participants, let alone their personal context: jobs, tasks, challenges, problems, difficulties, team dynamics etc. Hence, the training – especially in subject matter intensive topics – often results in a more or less one-size-fits-all type of approach: trainer goes through the slide deck, perhaps with a few participatory activities and some feedback at the end. Even if you’re an experienced trainer, it’s difficult to improvise and go off-course in the heat of the moment to pursue the emerging (personal) needs of the learners.

So, wouldn’t it be beneficial and make sense to put that information into good use and start to support face-to-face training with data? Yes it would. Here are two easy ways you can get a lot more out of your “classroom” sessions.

1. Determining existing knowledge and skill level with pre-work

One of the simplest things you can do to get more value out of your face-to-face training is to start using pre-work. Have your learners go through digital learning materials before coming to the session. Build in some seamless assessment and collect information in the form of user submissions and feedback. With good design and proper use of learning analytics, this already gives you a lot of valuable information.

As a trainer, you can then check e.g. what your learners already know and what they are having difficulties with. It probably doesn’t make sense to spend a lot of time in the classroom on things they already know. Rather, you’re better off using the time on addressing problem areas, challenges and personal experiences that have come out during the pre-work. Or if you want to explore making things even more impactful, try an approach like flipped learning. In flipped learning, you use digital to deliver the knowledge while focusing the classroom time solely on discussions, practice and hands-on activities.

2. Using learning records history to understand the people you’re training

Another idea we could do better at is understanding the people we deal with. At their best, these records may provide a whole history of learning. As these digital platforms compile more and more data about our learning experiences, it would be beneficial to let the trainers access that as well. By understanding prior experiences, the trainer can create scaffolding – build on what the employees already know from before. This might be totally unrelated to the current topic too.

Furthermore, having access to a “HR” history of the employees might be beneficial too, especially in large organisations where the trainer doesn’t necessarily now the people personally. For instance, what are the attendees jobs? Where do they work? Where have they worked before? In what kind of roles? All the information like this brings additional data points to personalise the learning experience on. In some cases, you might even find that there’s a subject matter expert in the group. Or someone who has dealt in practice with the issues of the ongoing training. These could be assets you can leverage on, of which you wouldn’t perhaps even know about without the data.

Final thoughts

All in all, there’s a whole lot that data and analytics can offer to “traditional” training. The need for personalisation is real, and smart use of learning data helps to cater to that need. Of course, you can use data to support face-to-face training in many more ways, these are just two examples. For instance, post-session feedback is much more handy to do digitally. This feedback can then be used to improve future sessions on the same topic (or with the same participants).

If you feel you could do more with data and smart learning design, don’t hesitate to reach out. We can help you design blended learning experiences that deliver impact and value.

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How to Make Your Corporate Learning Relevant? And Why It Matters

How to make your corporate learning relevant?

How to Make Your Corporate Learning Relevant? And Why It Matters

One of the bigger problems hindering the impactfulness of corporate learning is not lack quality content or great delivery methods but relevance. Employees often see the corporate just assigning them new training, with little consideration to whether it actually helps them or not. Furthermore, many organisations still do employ a one-size-fits-all type of approach to learning, which is setting up for failure. However, many are realising that providing employees with relevant learning opportunities is crucial. Thus, let’s look at firstly why relevance matters in learning, and then how we can deliver something that truly resonates with the audience.

Why relevance matters in corporate learning?

Relevant learning is crucial for a number of reasons. Firstly, it’s the way our brains work from learning standpoint. Relevant and meaningful activities that resonate emotionally and connect to existing knowledge help form new neural connections and pathways and build long-term memory storage.

Secondly, it’s a matter of engagement as well. Learners that don’t “connect” with the topic or material are much more likely to disengage, resulting in low retention. Furthermore, they might even lose the motivation to try (and it’s harder to win them back afterwards).

Thirdly, relevant learning is important because the fundamental goal of corporate learning is not just to acquire knowledge, but to transfer it into new work practices and behaviours. And change is hard. If we want to elicit behavioural change, we have to address the specific situations and challenges of the employees, rather than simply providing facts and information and leaving them to figure out the hardest part themselves.

How to deliver relevant learning?

So, how could we deliver learning experiences, whether online or face-to-face, that overcome the challenges above? Much of it deals with personalising learning. While that’s another article’s worth on its own, we thought we’d pick a few fundamental things that are easily forgotten.

  • Go learner-centric: designing and developing your learning experiences in a more learner-centric way helps to tackle a lot of the challenges. Spend time listening to your learners, their challenges, problems, contexts and situations. Involve them in the process as much as possible. Don’t deliver “content”, deliver relevant learning experiences that help them succeed.
  • Create scaffolding. Use the information and data you gain from your learner-centric design process to create scaffolding. Relate what is being learnt to the learners’ previous knowledge, learning history, professional experience, job functions, market areas etc.
  • Keep it fresh: remember to revise and update your activities regularly. The subject matter doesn’t necessarily change, but the context will constantly. Keep your examples, scenarios and cases current, which in turn helps in the scaffolding.

Does technology play a part in this?

One of the bigger promises of today’s and tomorrow’s learning technology is the ability to deliver more personalised learning everyone. While tools like AI are still relatively new in the learning and education space, there’s already quite a lot of good that can be done today.

At the very least, the new abilities to collect learning data and determine real learning needs help to fuel the learner-centric design process. Increasingly many learning environments also use algorithms to recommend relevant learning content and personalise the experience. Some more advanced ones venture into adaptive learning, where the individual learning path shifts based on a number of factors.

But even if you don’t have access to such tools or resources to buy into such technologies, don’t worry. Fundamentally, it’s all about doing the simple things right, and spending time to figure out the real needs. One thing that gets you pretty far: talk to your people!

Final words

Overall, relevance seems like a much undervalued factor in learning. However, the science and research is pretty clear: you need relevant learning to get results. In the corporate world, that’s even more evident, as studies have shown that people learn the new, but still easily revert back to the old ways of doing things. So, consider starting to help your employees and learners succeed by focusing on what helps them. And if you need help in going learner-centric, or leveraging technology to design more relevant experiences, we can help. Just drop us a note here.

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Micro vs. Macrolearning – What to Use and When?

Microlearning vs macrolearning what to use and when

Micro vs. Macrolearning – What to Use and When?

Microlearning has been all the rage in recent years. While we shouldn’t undermine its effectiveness when designed and used properly, it isn’t a solution to all learning problems. Concise and contextual bursts of learning are good for certain uses, but not all. Sometimes, we still need more long-form education, macrolearning.

While the traditional training approaches of organisations perhaps rely more on macrolearning than they should, we do need to make sense of when to go micro and when, on the other hand, we are better off with macro. So, let’s explore what to use, when and how.

We need macrolearning to build new skills…

Generally, we can distinguish between the need of macro vs micro by analysing the existing skill level of the learner. If the topic is entirely new, or the learner has had very limited exposure, macrolearning is the more suitable approach. Novices tend to benefit from structured and guided instruction, as well as learning about the topic with a wide perspective. This helps to develop an understanding of the topic to the level that the learner can start self regulating his/her own learning.

Conversely, attempting to use microlearning on such new topics wouldn’t work very well. As the learners are not familiar with the topic beforehand, they are less likely to be able to form the links between concepts (i.e. relate the microlearning activities to the bigger picture).

Hence, if we consider some practical use cases, macrolearning is likely to be at its best in:

  • Transformational programs. E.g. training people on contemporary topics such as principles of data science, design thinking, machine learning etc. In many organisations, these are skills not readily available in the skill pool.
  • Learning to use the organisation’s tools. E.g. training on how to use various software and information systems of the organisation.

… But microlearning enables us to build on existing skills

Whereas macrolearning focuses on complete skill areas and “the bigger picture”, microlearning is better suited for more specific needs. Pedagogically, we should use microlearning to build on existing knowledge. Once the learners already have a baseline of knowledge to work with, they can contextually apply and relate the newly learnt things to the existing. For instance, once you know enough of a language, learning new words brings immediate benefits. But learning vocabulary without knowing the grammar or how to use the language won’t give you good results.

Additionally, microlearning has the characteristics of being able to help people to learn something small in a convenient, rapid manner. Convenience and speed are key factors when considering learning in the flow of work. Smaller “chunks” are simply more convenient to offer and use than large “chunks”.

So, taking this into account, we could establish that microlearning is potentially better suited for uses such as:

  • Updating” knowledge and skills. E.g. new SOPs, new workplace practices, product updates and best practices. All of these are topics that employees would already have experience on. Hence, micro rather than long-form learning should be better off.
  • Performance support. Practical knowledge and information on how to perform specific tasks, delivered just-in-time.
  • Increasing retention. Refreshers, knowledge checks and other spaced learning elements help to increase retention, even within a wider “macrolearning” activity.

Final thoughts

We should never assume that there are any one-size-fits-all approaches to learning. Ultimately, executing an effective workplace learning strategy is about combining different methods, formats and approaches in a way that makes sense – for both the organisation and the employees. Perhaps a key thing to remember for the future is that neither micro- or macrolearning has to be just “formal” learning activities. Furthermore, we shouldn’t forget the clear link between the two. Micro will always be a part of the macro, and macro will always include the micro.

Hence, you should take the time to analyse your own organisational needs, and see what where you might best utilise either of the approaches, and even better, how to play them together. And if you think you might need help in developing this kind of a learning strategy, we can probably help. Just shoot us a message here and we’ll get back to you.

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How to Help Learners Succeed with Personal Learning Analytics?

How to use personal learning analytics to help learners succeed?

Personal Learning Analytics – Helping Learners with Their Own Data

Generally, the use of data and analytics in workplace learning is reserved for a small group senior people. Naturally, learning analytics can provide a lot of value for that group. For instance, data-driven approaches to training needs analysis and measuring corporate learning are quickly gaining ground out of the need to prove the impact of workplace learning initiatives. However, there could be further use cases for those analytical powers. One of them is helping the learners themselves with personal learning analytics.

What is ‘personal learning analytics’?

Like the title may give away, personal learning analytics is just that: individualised information made available to the learner. The major difference with conventional “managerial” analytics is that most of the information is about the learner in question. Whenever that’s not the case, the information of others would always be anonymised. A few exceptions could include e.g. gamification elements which display user names and achievements. So, effectively, it’s all about giving the user access to his/her own data and anonymised “averages”.

How can we use personal analytics to help learners?

One of the challenges in conventional approaches to workplace learning is that the process is not very transparent. Often, the organisation controls the information, and the learners may not even gain access. However, a lot of this information could help the learners. Here are a few examples.

  • Comparing performance against others. While cutthroat competition is probably not a good idea, and learners don’t necessarily want others to know how they fared, they can still benefit from being able to compare their performance against the groups. Hence, they’ll know if they’re falling behind and know to adjust their effort/seek new approaches.
  • Understanding the individual learning process. All of us would benefit greatly from information about how we learn. For instance, how have we progressed, how are we developing as well as how and when do we engage with learning. Luckily, personal learning analytics could tell us about all of that. The former helps to keep us motivated, while the latter helps us to identify patterns and create habits of existing behaviour.
  • Access to one’s learning history. We are learning all the time and all kinds of things. However, we are not necessarily very good at keeping track ourselves. If we just could pull all that data into one place, we could have a real-time view into what we have learned in the past. Potentially, this could enable us to identify new skills and capabilities – something that the organisation would likely be interested in too.

Towards self-regulated learning

Across the globe, organisations are striving to become more agile in their learning. One key success factor for such transformation is the move towards more self-regulated learning. However, achieving that is going to be difficult without slightly more democratised information.

If the learners don’t know how they are doing, they cannot really self-regulate effectively. And no, test scores, completion statistics and annual performance reviews are not enough. Learning is happening on a daily basis and the flow of information and feedback should be continuous. Thankfully, the technology to provide this sort of individual learning analytics and personalised dashboards is already available. For instance, xAPI and Learning Record Stores (LRS) enable us to store and retrieve this type of “big learning data” and make it available to the learners. Some tools even provide handy out-of-the-box dashboards.

On a final note, we do acknowledge that the immediate applications of “managerial” learning analytics likely provide greater initial value to any given organisation. And if you’re not already employing learning analytics to support your L&D decision making, you should start. However, once we go beyond that stage, providing access to personal learning analytics may be a good next step that also helps to facilitate a more modern learning culture in the organisation.

If you’re eager about learning analytics, whether on an organisational or personal level, but think you need help in figuring out what to do, we can help. Just drop us a note here, and let’s solve problems together.

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How to Move Towards a Resource-based Learning Strategy?

Moving towards resource-based learning strategy in the workplace

How to Move Towards a Resource-based Learning Strategy?

In modern workplace learning, speed and flexibility are more important than ever. Meanwhile, employees expect learning to be more personalised and happen at their terms rather than the corporate’s. Conventional approaches to training, such as lengthy classroom sessions or elearning courses are often ill-suited for the real learning needs of the modern worker. Overall, the highly structured, one-size-fits-all formal training is coming to the end its road. So what does the future hold then? Well, many things, that’s for sure. But one major paradigm shift in the way we view corporate learning is the shift towards resource-based learning strategies. Let’s look at that shift in a bit more detail.

What’s a resource-based learning strategy all about?

So, let’s first tackle what’s changing and the factors driving the change. First of all, workplaces are increasingly performance-focused, and that’s affecting learning as well. The need to prove the benefits for performance has been partly fuelled by L&D’s inability to use data and prove the impact of different learning activities. Secondly, skills and knowledge are changing and expiring faster than ever. The employees naturally need to keep up, but don’t have the luxury of time on their side. Thirdly, we’ve realised that one size doesn’t fit all, we can’t force people to learn and a whole lot of learning is not being applied by the employees. A resource-based learning strategy can help to address all these issues.

Here are a few key shifts in thinking and considerations when moving towards resource-oriented learning.

Focusing on helping the employees to do their jobs better

The ironic thing about conventional corporate learning is that it sometimes actually hinders our employees’ ability to do their jobs. We take them away from their jobs. We have them spend their time on learning things that we think benefit the company. Furthermore, we often get carried away with competencies, curricula and courses. But actually, all that matters is that we help the employees do their jobs better. Hence, instead of inconveniencing them with learning, we should build and curate learning that helps them to carry out specific tasks. These kinds of resources have to naturally be quick to access and consume. Time is money. From a learning standpoint, conveying information that the learner can apply immediately is also of much higher learning value than going through abstract concepts that are quite remote from the job at hand.

Allowing people to direct their own learning

Traditionally, companies manage their training in quite a top-down manner. However, more learner-centric approaches to people development may garner better results. One of the key aspects of a successful resource-based learning strategy is the learners’ ability to influence their own development paths and activities they uptake. Allowing people to choose which learning resources to consume and when (often at the point of need) ensures that the material is always relevant and can often be applied into practice immediately. Moreover, learners have a much higher share of intrinsic motivation, compared to L&D team having to lure them over with “artificial” techniques like gamification.

Arguably, modern employees are quite well aware of the fact that they need to take a proactive stance in their own development. This is evident from the statistics on the free time spent on learning various things. A resource-based learning strategy empowers the employees to take (to an extent) charge of their own development. The responsibility of the organisation is to provide the resource base for it. Well-curated resources help cut through the clutter, and find the “right” content.

Final thoughts

Corporate learning has for a long time over-emphasised formal training. However, as traditional approaches start to fall short, we need to refine our strategies. The general need to shift from courses and curricula to resources seems evident. In fact, leading organisations are already implementing learning initiatives to empower their employees unlike ever before. All in all, the shift in philosophy is a fundamental one. Hopefully, this post provides a baseline of concepts to explore further from. And should you need help in future proofing your organisational learning strategy, we are happy to help. Just contact us here.

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3 Reasons Your eLearning Should Never Be Mandatory

3 Reasons to Avoid Mandatory eLearning

3 Reasons Your eLearning Should Never Be Mandatory

When designing corporate elearning experiences, it might often seem compelling to make them mandatory. For some reason, we’ve grown to believe that forcing the learners to “take up on courses” or “participate” will guarantee learning. But the unfortunately reality is that it doesn’t. Far from it actually. Making a learning activity mandatory is a great way to kill motivation and effectiveness as well as introduce an inherently wrong culture of learning in the organisation. Thus, we should find alternatives. Here are three reasons to avoid mandatory elearning.

1. Mandatory eLearning kills motivation

Learners like choice, freedom and personalisation. Furthermore, adult learners tend to be relatively more self-directed than kids at school. Finally, learning is something that is inherently fun and rewarding, thanks to the element of discovery. Whenever you make learning activities compulsory, you’ll take away from all that. As soon as something is made mandatory, you’ll evoke a psychological defensive reaction: “why do I have to do this”. And if your training materials are not relevant, the employees will soon feel like you’re wasting their time. Continue that for long enough, and you’ll find it very hard to introduce meaningful learning initiatives within the organisation.

2. Having to go through everything doesn’t constitute effective workplace learning

On a practical level, once someone has decided to make elearning mandatory, a common technique to enforce that in practice is to use a technique of “locked progress”. Essentially, this means that the learner has to go through every piece of material, most often in a pre-defined sequence, to complete the learning. Unfortunately, this type of approach doesn’t serve the modern workplace learning at all.

Workplace learning is inherently informal and sudden. To really affect and enable performance, learning has to be much more just-in-time. In fact, most of the traditional corporate elearning today would probably be better off served as performance support resources than highly structured activities. If you’re wish to support your people at their jobs, limiting their access to information and having them jump through the hoops of locked progress might not be a good idea, as it kills all this natural inquiry -type of behaviour. And it’s not that they won’t learn, no. Your employees will probably find the resources via other channels. It’s just not going to be your learning materials, hence you cannot control the validity of the information.

3. Mandatory eLearning reinforces tick-box culture

Finally, the perhaps highest level challenge in trying to force your employees to learn is that it reinforces a tick-box culture. As there’s a good chance that the employees don’t feel that your mandatory elearning is all that relevant or beneficial to them, they are likely to try to minimise their effort to go through it. Yes, they will probably click through the slides or loop through the videos if you force them to, but that’s where it ends. You see a learning culture where it’s enough that something has merely been completed. We sure hope no-one still believes that having someone complete something is a good indicator of learning (hint: it’s not). Rather, learning requires active thinking, reflection and application and is a much more complex process.

Final words

All in all, we don’t think making your elearning or any kind of training mandatory is ever a good idea. Instead of trying to force people to learn, it’s our job as learning professionals to design workplace learning experiences that actually help them to perform better and motivate them to learn on their own. Some will undoubtedly argue that some learning needs to be mandatory for compliance reasons, and that may be true in some cases. However, even if you have to have your employees go through training doesn’t mean that you have to use the same old “mandatory” playbook. Rather, find ways of using things such as gamification, social or experiential learning to make it a bit more interesting. Or, use proper analytics to prove that the required effort has been put in, instead of forced tests or completions. And if you need help, just contact us.

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Responsive Design in Mobile Learning – 3 Tips for Better UX

3 Tips for Responsive Design in Mobile Learning

Responsive Design in Mobile Learning – 3 Tips for Better UX

Professional learning is increasingly happening on the mobile. While learning that is happening via devices, be it desktops, tablets, televisions or mobile phones often gets labelled as just “digital” or “eLearning”, we might be better off thinking of the various mediums more granularly. Due to the limitations and restrictions caused by e.g. screen size, we cannot simply expect the same type of design to work for all the devices. Responsive design has emerged as a solution to that problem. However, simply using a responsive and automatically adjusting layout is not enough. Hence, we’ve compiled three tips for using responsive design in mobile learning. Let’s have a look!

1. Don’t overkill with interactivity

Looks like we barely made it to the first item and we are already contradicting conventional wisdom! Shouldn’t all learning contain as much interactivity as possible?

Well, no. Firstly, you should never use interactivity for the sake of being interactive. Rather, you want to make sure that the learning interactions actually contribute to the experience. Secondly, we need to carefully consider the peculiarities of mobile use if we want to deliver successful responsive design in mobile learning.

For instance, whereas on the desktop, having the learners “click” through objects is a widely used mode of interactivity, it doesn’t really work on the mobile. Rather, such interactivity in responsive mobile learning should be based on scrolling and swiping, two “natural” behaviours on mobile. Also, due to the smaller screen real estate, you don’t want your learners to have to jump through hoops and constantly open or launch new pieces of content.

2. Optimise your media and graphics elements

Another important factor to take into account is the use of media, graphics and visual elements. Generally, mobile devices are not great mediums for focused, extensive reading. Hence, we often tend to look at visual ways of conveying the information. However, there are a number of things to consider with visual elements when it comes to responsive mobile learning design. Here are a few you should keep in mind:

  • Optimise your file sizes. Mobile often goes with limited bandwidth, and increased loading times will get your learners dropping out.
  • Use simple graphics. Don’t attempt to include all the information in a single graphical illustration. This will often result in something that the learner has to zoom and manoeuvre about. Also, try to keep text out of graphics that are going to be scaled, as the text becomes illegible very easily.
  • Use icons, breaks and white space. Icons are great in communicating many things, e.g. navigation, context, sections or instructions. Breaks help the learner to pace the content and avoid “scrolling too fast”. White space works equally well in that, and also helps to balance out the design.

3. Design intuitive UIs and navigation

If we want to be successful in responsive mobile learning design, we also need to focus on UIs and navigation. Whenever our learners are spending time navigating complex structures or trying to find the information they are looking for, they are not learning. Thus, we should make finding and retrieving information as fluid and seamless as possible.

What’s fluid and seamless then? Firstly, you might be better off following the prevailing “logic” and “flow” of everyday applications. It gets very irritating when navigation elements like “previous”, “next”, “exit” or “play” are not in their “common” places. And you probably don’t want to make your learners frustrated. Furthermore, when it comes to mobile learning, it’s important to acknowledge the screen size limitations once more. Due to the small field of view, it’s much harder to quickly find new elements, compared to e.g. desktop, where one can see a lot more at once.

Final thoughts

Responsive design in mobile learning definitely proposes an extra hurdle for organisations, as they have a lot more to consider when designing digital learning. However, it’s a hurdle that one really can’t ignore. We haven’t seen any organisations that have ignored the need for responsive design and “mobile optimisation” and succeeded with their mobile learning initiatives. If this sounds entirely foreign to you, we are happy to help you understand the peculiarities of mobile, and to deploy effective learning initiatives utilising mobile devices. Just contact us here.

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How to Enable Mimetic Learning in Organisations?

Mimetic learning in organisations

How to Enable Mimetic Learning in Organisations?

While we have a tendency to over-estimate the learning value of formal learning activities (e.g. teaching a class), we tend to underestimate some other activities. Throughout human history, people have learnt trades, professions and skills through a much less rigorous approach, learning by imitation. This type of learning by “copying” others also occurs on much wider scale. For instance, learning how to deal with different cultures or social settings may often happen through imitation. But could there be value in enabling mimetic learning in modern organisations? Let’s explore.

What’s mimetic learning?

For definitions’ sake, let’s quickly define the term “mimetic learning”. To avoid misconceptions, mimetic learning shouldn’t be seen as to only consist of copying and imitation. Rather, we should view it as the act of relating to other persons, situations or “worlds” in a way that in turn leads us to improve our own views, actions and behaviours. In simple terms that would mean not just mindless copying, but first imitating and then critically implementing relevant behaviours.

Potential Value-add Cases in Organisational L&D

To understand how to facilitate this type of learning, we first have to understand what it may be good for. Here are a few ideas:

  • Learning practical or trade skills. For instance, novice engineers developing their technical skills could vastly benefit from being able to imitate and follow more seasoned experts. The better the knowledge transfer, the better the results.
  • Developing soft skills. For instance, new frontline employees in customer service roles could benefit from being exposed through mimetic learning opportunities to how senior employees approach and resolve conflicts and communicate in difficult situations.
  • Understanding culture. Each culture, whether an organisational one or something else, has its own artefacts, social rules and common behaviours. What a better way to learn about these kind of unique traits than through observation and learning by imitation?

How to facilitate mimetic learning in organisations?

Facilitating learning through imitation should be about providing opportunities for it and connecting “novices” to “experts”. There’s obviously a whole lot that can be done via traditional means. However, we’d like to focus on a few ideas involving the use of digital:

  • Digital communities of practice. Let novices follow experts via digital channels, while the experts showcase their techniques, methods and secrets through videos, writings, etc. Focus on practical applications. These digital communities of practice can have similar technical functionalities to social media platforms.
  • Enable curated sharing on organisational level. What if an employee thinks that they have a better, novel way of doing a particular task? What if you let them share it across the organisation to make more people aware of it? Don’t want to spread false practices? You can always curate and moderate what employees share.
  • Provide opportunities to practice. Encourage employees to take up new things and practice on their jobs. Have the experts chime in and watch over the process if possible. Perhaps even some digitally enabled coaching could be possible.
  • Enable wide exposure. Share things with your employees. A lot of the mimetic learning is reported by employees to happen thanks to “just being there”. Hence, expose your employees to different lines of business, problems and challenges as much as possible.

Final thoughts

Often, organisations fail to pay attention to a lot of the “natural” processes of learning, while focusing on a very narrow subset of formal, instructor-led techniques. Mimetic learning represents one of these highly natural ways of learning. While it’s hardly the solution for every learning need, it could help to solve some of the common organisational problems related to knowledge transfer and upskilling people on their jobs. The great thing is, that just like community-based learning or user-generated content strategies, facilitating people learning by “just being there” can be quite a low investment-high impact initiative. If you’d like to do that, or enable other methods of informal learning, feel free to contact us. Let’s try and solve your problem together.

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