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Topics: Informal learning

Informal learning:
Everyday hero of work

“Formal learning is like riding a bus. Informal learning is more like cycling.” What exactly does that mean? What makes informal learning a secret but everyday hero in the workplace? Nick Petch, Head of Learning Experience and Design Strategy at imc explained this in a recent webinar. We summarised the key facts and recommendations.

lms hot topics, informal learning

Last week, I finally got back to the office. For me that means: No more sitting at home all day! Above all though, it means I can meet colleagues without having to make special arrangements. A brief chat over a coffee or quickly popping in next door to ask how things are going with client XYZ, rather than having to pick up the phone or writing a message – such a relief!
While some still keep a critical eye on these exchanges and consider them a waste of time, it is far more than just vain chit-chat. It is part of informal learning.

INFO

In contrast to formal learning which involves learning pre-defined content at a specific time, informal learning relates to the learner receiving information exactly in the moment or at the point of need.

BUS OR BIKE?

Most of the time, this knowledge acquisition happens without us giving it a second thought or realising that we are learning. In actual fact, we all use informal learning all the time: We google for information, write Teams messages, consult Wikipedia – and check with the colleague next door.

Quite often, we remember the knowledge acquired this way better than the things we learned by heart at some point. That is because we process and use the information straight away.

Nick Petch, imc

Nick Petch, Head of Learning Experience and Design Strategy bei imc

Informal learning has piqued the interest of Nick Petch, Head of Learning Experience and Design Strategy at imc, for years. His take: "Formal learning is like riding a bus. While I decide whether to take the bus and where to get on, it is the bus driver who dictates where I can go and how fast I will get there.

Informal learning is more like cycling: It is entirely my decision where I go, which route I take, how fast I go, and whether I complete the journey non-stop or allow myself a break in between.”

Yet, the necessary awareness that such informal exchange can be crucial is lacking in many companies. Their focus is often limited to formal development opportunities. Studies show that this is not conducive. For example, the US American Education Development Center (EDC) found that around 70% of competency gains obtained in an organisational context come through informal learning. That only leaves 30% as a result of traditional personnel development.

THE CRUCIAL QUESTION

Achieving a balanced mix of formal and informal learning is therefore key. Nick Petch explains: “The two elements need to build on one another. Formal learning remains crucial. It helps people to learn how to learn. Learning is a skill that further enables you to choose when and how you adopt informal learning. If you keep on training your employees to sharpen these skills, your company becomes more agile and able to respond to changes or challenging times in a flexible manner.”

More specifically, this means that companies must train their employees to obtain knowledge as quickly as possible, and to map at least the basic concepts in a system. This documentation achieves two things: It boosts appreciation for the acquired knowledge, and it makes this knowledge available for other employees.

 

To avoid unnecessary log-ins, it helps to use systems the users log into regularly, such as the company’s learning management system (LMS). If the informally acquired knowledge is at least outlined here, shown in the relevant employee’s profile and a link is set e.g. from an internal wiki, colleagues can see who might be able to help them.

 

Yet, this is where we run the risk of going around in circles. How can an informal instrument be translated into formal structures?

ADVANTAGE THROUGH KNOWLEDGE TRANSFER

First of all, the principle and appreciation of informal learning must be anchored firmly in the corporate culture. A sharing-is-caring culture must be created. In other words: Knowledge should not be hoarded centrally in individual departments or persons, but must me available in a decentralised manner. Such decentralisation can also buffer the loss of individual employees. Companies that realise this successfully have an enormous advantage over their competitors.

 

While access to explicit knowledge including documents, wikis and blogs is important, so is straightforward access to colleagues and specialists who can be approached “on demand” as and when the need arises. Companies can leverage structures like Communities of Practice, Working out Loud-Circle, expert profiles or dedicated Teams channels to drive networking.

Uwe Hofschröer is involved in strategy consultancy at imc and confirms: “Companies are becoming more aware of the topic. Questions on how to create structures that promote such knowledge transfer within an organisation are on the increase.”

 

On-the-job training is certainly an option. This describes direct learning in the workplace supported by colleagues or tools like the imc Process Guide, an electronic performance support system (EPSS).

Uwe Hofschröer

Uwe Hofschröer, Head of Learning Strategy Consultant bei imc

The crucial thing for companies to understand is that you cannot merely push a training course that teaches informal learning. Rather, meta competences like reflectivity and problem solving must be trained.

In order to achieve that, companies must start by creating the right environment to promote informal learning. Our experts have compiled the key factors for meaningful realisation of informal learning in the workplace:

  1. Making informal learning visible in the system
    Provide room for the topic. Motivate your employees to get actively involved in blogs or wikis and share their knowledge. Utilise knowledge-sharing opportunities, such as regular feedback rounds after projects are concluded where lessons learned are shared and documented.

 

  1. Coaching & mentoring
    Conversations are one of the richest sources of informal learning. Creating opportunities for regular exchange is key. Coaching and mentoring can also be implemented across departments. Identify your early adaptors, i.e. the team members who get excited about new developments and strive to be the first to apply them. Get these colleagues on board to actively promote knowledge transfer.

 

  1. Creating an open learning culture
    This final piece of advice sounds a lot easier than it really is. It is, however, crucial. Effective informal learning is only possible if the company has established an open learning culture and the concept of knowledge transfer is firmly anchored in the mindset of every employee on all levels.
    Sharing is caring! Individual employees guarding their knowledge like a treasure they refuse to share with others must be an absolute no-go. This takes trust and autonomous collaboration. Flat hierarchies help to achieve this, while also supporting the creation of Communities of Practice. Providing the physical space for employees to meet, talk and make arrangements without additional hurdles also helps to create an open learning culture.

Once such a learning culture is realised in the workplace, the odd chat by the coffee machine should no longer raise any eyebrows, either. That’s exactly where I’m heading right now.

More information

The webinar  in full length with Nick Petch about informal learning, can be found here.

If you would like to learn more about digital learning strategies or about imc Process Guide, please visit the corresponding pages.

 

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Contact

I have been working in the Marketing & Communication Team at imc since March 2019.

Communication, creative content and social media are my passion. "KISS - Keep it short and simple" is my credo.

 

To explain complex content in an understandable way and thus make the topic of e-Learning accessible to everyone is an exciting challenge every day.

 

Privately I love to read, play poker and travel a lot.

I am always happy to receive feedback or suggestions.

Photo of Nadine Kreutz
Nadine Kreutz
Communication Manager
LMS Hot Topics
Topic: AI in Corporate Learning

Artificial Intelligence:
Useful tool in Corporate Learning or a complete loss of control?

What kind of influence does artificial intelligence (AI) have on learning management systems? Where and how is it being used already? And are all employees about to be continuously monitored by machines?

These are just some of the questions that are also on L&D specialists’ minds as they consider the potential applications of AI in learning systems. And that’s more than enough reason to take on some of these questions and look at them in greater detail.

Andreas Pohl
A lot of the fears related to the subject of AI are unfounded.
Andreas Pohl
Director Reasearch & Development
imc AG

When it comes to the topic of artificial intelligence, there are a lot of misgivings. Losing sensitive data and constant employee monitoring are only two examples, and learning experts are also having to confront these questions as they develop.

However, imc software expert and AI enthusiast Andreas Pohl thinks it’s important to put things into perspective: “A lot of the fears related to the subject of AI are unfounded. Sure, there absolutely are justified concerns regarding ethical issues that need to be clarified, but when it comes to our Learning Management System (LMS), customers don’t have to worry about the possibility of an evil AI suddenly stealing their data or something like that because it’s not a thing that can actually happen.”

To provide a better understanding of what AI really can and cannot do and how it is used in our LMS, we’ll go over the most important concepts and provide concrete examples of their use.

MACHINE LEARNING

What is machine learning?

The term is used to describe dynamic algorithms that are able to learn and improve by themselves in such a way that systems can recognize recurring patterns, develop solutions, or provide advice, for example. And the more data that is entered, the more accurate the corresponding predictions.

However, it’s absolutely imperative to define, in great detail, what data is relevant and which rules should be used to analyse data and recognize patterns. In other words, it requires for human beings to actively step in when it comes to the analysis of data and the actual decision-making process.

 

For more information, visit DeepAI.org.

Icon representing Intuitive

What is machine learning used for?

One typical example of a machine learning application is image recognition processes. If you teach a machine that a triangle always has three corners and a rectangle always has four, the program will recognize this. It’s important to point out, however, that very exact parameters need to be set up and that if an image doesn’t meet those exact parameters, it won’t be recognized sometimes.

Where in our LMS does machine learning take place?

A typical example consists of automatic recommendations similar to those used by Amazon: “You like A, so check out B.” This is the exact same principle used by the recommendation engines in learning management systems.

Basically put, a person chooses the course they want to take, and the system provides additional recommendations based on this. In fact, these recommendations can also be linked to the person’s learner profile, i.e., their position, their development goals, the courses they’ve already completed, etc.

And the more data that the underlying algorithm has, the better its recommendations will be. This is one of the classic applications of machine learning.

DEEP LEARNING

What is deep learning?

Deep learning is a subset of machine learning in which a machine is able to improve its abilities independently and without any human assistance. In contrast to machine learning, people do not influence deep learning results at all, and instead only make sure that the required information is available and that the relevant processes are documented.

In fact, the machine itself carries out the actual analysis and uses it to derive forecasts and/or decisions without assistance on the basis of neural networks, which are connected to each other in a manner that resembles the human brain. Ultimately, the machine is able to make decisions based on these connections.

Now, it’s important to point out that this requires an enormous amount of data, and that this type of data is not found in individual learning management systems.

 

For more information, visit DeepAI.org.

 

Icon representing Intuitive

What is deep learning used for?

One typical example of a machine learning application is image recognition processes. If you teach a machine that a triangle always has three corners and a rectangle always has four, the program will recognize this. It’s important to point out, however, that very exact parameters need to be set up and that if an image doesn’t meet those exact parameters, it won’t be recognized sometimes.

Where in our LMS does deep learning take place?

Generally speaking, using deep learning in learning management systems is still extremely difficult given the lack of sufficient data. In fact, in order to be able to analyse specific patterns and processes, learning platform vendors would have to analyse the data from various companies together, but this isn’t possible due to the fact that this data is subject to very strict data protection regulations and policies.

 

One concrete example of an area where deep learning algorithms could be used would be learning style recognition. With AI, this recognition could be much more efficient than it has been to date, as it would work uncoupled from manual input and tests.

In this scenario, a system would be able to automatically figure out a learner’s preferences and behavioural patterns and determine the correlation for the corresponding learning results. This means that, from a purely theoretical perspective, your LMS would be able to determine what your learning style is and recommend appropriate content for you based on that.

What is the reality?

In order for the system to be able to use the existing knowledge on how to use learning style recognition to provide appropriate recommendations, all learning contents would have to be available in various versions, that is, as text, images, video, games, or audio.

Needless to say, however, creating these individual contents would entail an enormous amount of time and money, so this approach has seldom been used to date in real-life applications. However, it’s reasonable to expect that these topics will be pretty important in the future, particularly in relation to improving learning efficiency and learning in the moment of need.

CONCLUSION

In other words, a lot of the fears that people have in relation to the topic aren’t really relevant, or at least not today. However, when it comes to the subject of learning and AI, it will admittedly be necessary to answer ethical questions regarding applications in the future.

Or as Andreas Pohl puts it: “I think we should see AI as an active tool for supporting people. Humans must always be in the foreground of everything, and every single system must provide customers with real added value, regardless of whether it uses AI or not. And at the end of the day, we can always turn any system or tool on or off.”

 

More about AI and how it can also be implemented in the onboarding process, you can find out in another article of LMS Hot Topics.

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Contact

I have been working in the Marketing & Communication Team at imc since March 2019.

Communication, creative content and social media are my passion. "KISS - Keep it short and simple" is my credo.

 

To explain complex content in an understandable way and thus make the topic of e-Learning accessible to everyone is an exciting challenge every day.

 

Privately I love to read, play poker and travel a lot.

I am always happy to receive feedback or suggestions.

Photo of Nadine Kreutz
Nadine Kreutz
Communication Manager