Preparing your organisation for AI supported learning

Supporting learning with data is a process of using analytics to empower learning and making decisions based on data-backed evidence.

Smart new technologies, such as machine learning and data mining have made significant progress in recent years, and their impact is growing in many areas of life. The finance sector is a prime example of how data and machine learning are used to optimise business processes. The field of finance naturally lends itself to data. It runs on clear metrics and has precise targets for optimisation.

Organisational learning, on the other hand, is an example of a field with varied goals and fuzzy data. That is the main reason, the area of learning has largely been lacking analytics and data-powered decision making. However, technological developments are reaching a stage in which these obstacles can be overcome.

HR has a natural position to becoming a true leader in digital learning. This transition has started, and it will gain strength with time. The phases and tools of the process are described in Graph 1 and explained in the following text.

Graph 1. The phases of leading learning with data  

Scattered data
The data is already here, but where exactly?  

Most organisations already collect and hold massive amounts of learning related data. Digital platforms, online courses, tests, competence appraisals, self-reports, education feedbacks, and other similar systems produce a wealth of information. One of the key challenges is that data is located in multiple unlinked systems. To use this data, one needs to derive it from various sources and combine it manually. As a result, HR is left with periodically producing one-off reports with cross-sectional analyses about the current state of affairs.

Manual reporting, even if partially automated to reduce the amount of work, is not real-time. It focuses on a pre-selected set of explicit variables and is rudimentary and lacks the possibilities for insights compared to more present-day solutions.

 

Combined data and dashboards

Once an organisation combines its databases or builds interfaces for that purpose, more efficient data-enabled learning can begin to commence. Combining the learning management system, educational data, competency evaluations performance data brings insight into how all of these relate to one another. Ideally, this information is presented in a simple dashboard providing real-time analytics about learning and development. It can bring insights into where learners are spending time, what they are engaged in and what seem to be the evident obstacles for development. Correlating the educational variables with business results, such as sales data, provides ways to explore the progress and effects of specific programs or interventions.

For the most part, dashboards are still constrained with human deficiencies in decision making. They only show what they are planned to show. We are inclined to focus on the explicit relations between the most obvious variables. Many of the implicit reasons between causes and effects are hidden from a human investigator.

 

Predictive insights

Even with the ill-defined datasets related to learning and development, advancement in natural language processing and image recognition allow algorithms to make sense of contents and contexts in materials. That is, they can mine the data points for meaningful correlations that often escape the naked eye, such as finding relations between implicit, hidden variables, and draw on historical data and decisions within the organisations. They lack some of the pitfalls compared to human decision making and can outperform even most experienced human practitioners. An effective way to gain insights into learning data is merging the desired outcomes, such as sales results or customer feedback with the usage patterns in a learning platform. This highlights effectiveness of different ways of engaging with the learning possibilities offered by an organisation. The information can then be used to adjust the learning programs for future learners.

These systems can be assigned to identify learners who are not participating, or whose skills are in danger of lagging behind. They can also highlight some of the knowledge gaps or strengths within an organisation. In parallel with helping HR professionals, the same algorithms can be harnessed to serve the learners. Indeed, the next level of learning systems is that which can make accurate recommendations for learners, educators, and HR.

 

Dynamic, actionable recommendations

Web stores and social media are effective in making interpretations about our interests and recommending us products or services that appeal to us. This same technology can be applied to support learning. This enables an organization to deliver truly tailored recommendations for ‘just-in-time‘ learning and personalised training programs for each employee instead of fixed courses designed for the masses.

When a system has understanding about the needs, interests and learning activities of employees, it has a robust set of data to conclude from. It can recommend materials, activities and interactions to a specific learner based on identified needs. Further on, a learning platform can make accurate recommendations for future learners about which actions would be beneficial for them based on previous learners‘ activities.

The next developments in this process will be automated learning paths using materials inside an organisation and automatically providing appropriate tests to measure learning and motivation.

 

Conclusions

Digitalisation and data are not solutions to every problem. Leading with data is about developing new ways of operating. It is slow; it requires work and most of all, it requires a comprehensive understanding of current operations. The first step is recognising the current state of learning data in an organisation and designing the steps to take the process forward.

Data-driven systems do not replace effective competence management, but HR professionals that refuse to leverage available data for this purpose will be replaced by those who do.


This article was also posted on the latest EAPM Newsletter

Topi Litmanen

Dr. Topi Litmanen works as a Chief Educational Scientist in Claned Group. He is responsible for ensuring, that the pedagogical aspects of the Claned are based on latest learning research. Topi makes sure that Claned customers get the needed support for meeting their digital learning needs.

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The essence of success in online learning

The first theme of our blog posts this year has been how to succeed with your online courses. We wanted to cover different key topics to help you to build a successful online learning business and to create quality content to engage your learners.

Here are some key takeaways from each of the topic that we have covered over the last few weeks. Each headline links you to the blog posting in question. Enjoy!

How to create a successful online course business?

The series kicks off with our Chief Commercial Chief Petri Virtanen reminding us that when choosing your learning platform provider, you should also think about them as your partner. A partner, who helps you to scale your business, supports you with learning content and instructional design, and offers insights into your content helps you to build even better content.

Why does service design matter when creating online courses?

Next, Solja Sulkunen, our Head of Customer Experience, makes a great point about service design. You should always design the whole learning process from the learners’ point of view – from sign up to the certificate. The course needs to be scripted so that in each part of the course the learners know what is expected of them and how different learning activities support their learning outcomes. It is crucial to bear in mind that doing this design takes time and resources, so equip yourself accordingly or engage with a suitable partner to work with.

Creating engagement with social learning

Not only is well-scripted content essential to a successful course but as Claned’s Chief Educational Scientist Topi Litmanen reminds us in his blog, the interaction is equally important. Collaboration and active participation increases the enjoyment of the course but also improves learning results. You can read some simple design ideas from Topi’s post to enhance the interaction between learners.

Simple secrets of great learning videos

Videos are very hot content right now, but often they seem a bit difficult to produce. Not to worry,  Teemu Vaalasmaa, our Customer Success Manager, shares some insights with you! There are some great easy-to-use tools available when you want to get started with some videos of your own. Read from Teemu’s blog how you can start producing some of the video content yourself and also find out what are the benefits when using a content creation partner.

Why looks matter in learning content?

By now we have covered how to create the working course script and activate interaction But you should also pay attention to the visual quality of your course? In her blog Chief Creative Officer Virve Tamminen shares insights into why design matters and how to achieve it with some simple design choices. We are not saying that you should throw away that 32-page-long black and white PowerPoint, but yeah, we kind of are encouraging you to think about it.

A buyer’s cheat sheet to UX in online learning platforms

Whilst getting your digital course content designed and structured right, it is essential for your e-learning business to choose the right learning platform, points out Head of User Experience Miska Noponen. In his blog, Miska highlights out some of the potential pitfalls and how to avoid them when choosing a  platform. The key takeaway here is that the user experience is a lot more important than a long list of feature bullets.

Three key benefits to demand from learning analytics

Analytics is a word that gets thrown around a lot these days when talking about online learning. In online learning, analytics is a lot more than just progress tracking and should provide you with some clear benefits in terms of successful learning experience and results. In this blog Dr. Topi Litmanen encourages you to think about analytics through these three key questions: Can I increase the engagement on my course? Can I personalize my course for different kinds of learners? Can I see whether my training programs increase work effectiveness?

That’s all folks!

For us, this blog series was a fun to produce. We are very passionate about what we do and happy to share our expertise and experience with you and for your benefit. If you want to know more about any of the topics we have explored in our blogs, get in touch with us and let’s discuss how can we create success for you. Our next blog series is already in making and will hopefully be as useful as this one.

 

Teemu Vaalasmaa

Teemu is passionate about e-learning and technology in general. He helps customers to succeed in using Claned platform.

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Three key benefits to demand from learning analytics

The best thing about learning analytics is that it sheds light into issues surrounding learning usually hidden from the naked eye. That is, it provides ways to peek into the details of the learning process. More importantly, analytics provides new ground for evidence-based learning interventions without taking away the need for a skilled educator but instead highlights the importance of pedagogical expertise.

Education is largely different from many other fields, which have been revolutionised by data. As it is largely related to human interaction, decision making will remain in the hands of skilled educators. Learning analytics do not offer fixes. Instead, using it provides an effective way of improving educational programs and making effective interventions. And the impact of analytics is directly linked with the quality of analytics that you have access to. So, if you are about to invest into a new learning environment that promises analytics, or you already receive analytical views into the training process, let’s ask some critical questions on what matters most in learning analytics.


Can I increase the engagement on my course?

The most crucial problem in online learning relates to the frustration when facing ambiguous challenges and getting stuck. Too often this is caused by a confusing or unsuitable learning passage that can hamper even the best course.

In order to take corrective action, learning analytics should provide a way of highlighting the sections of a course, which are challenging. On the other hand, analytics should also show which parts work and create engagement.

Additionally, you should be able to identify the challenges faced by the whole learner population or just or particular groups of learners. Thanks to automatic keywording of materials using natural language processing, in addition to single materials, you should have the option of viewing this at a topic level. For example, which of the central themes in a course are problematic.

So, after setting the initial question and goal, in this case, engagement, learning analytics can highlight the sections in need of a fix and what works already. This offers the basis for identifying the target of improvements and measuring the effects afterward. However, no technology does or will do the actual work of designing appropriate learning activities. But with the support of analytics, the content iteration will be more successful.


Can I personalize my course for different kinds of learners?

Learners are different. They have varying amounts of experience, different strengths, and diverse interests. Some might find your course too easy while others are struggling. Just how different are they and where they differ is up for the learning analytics to reveal.

Learning analytics should be designed to identify groups of participants or individuals with specific needs or challenges. As the analytics can identify distinctions in behavioral patterns, you can focus on how these relate to performance, quality of social interaction and background variables, such as professional role in a company.

Once you have been able to identify the differences between learners, you can provide tailored paths based on their interests and background. For example, by offering background information for those with less experience in a topic, or alternatively more advanced information for those that need more challenge.

You should be able to intertwine groups from two different backgrounds by first providing a path for each to prepare them for the subject,  and then offer a shared part where they can share their knowledge. Imagine, all this with the help of effective learning analytics using your existing materials.


Can I see whether my training programs increase work effectiveness?

Whether you work in a company offering training programs or responsible for courses inside an organization, the holy grail is showing the real impact of training. That is, how does the actual performance change as a result of training.

An example of an industry transformed by data is finance, an area that naturally lends itself well to smart technologies. It has clear metrics and outcomes. As a result, algorithms which optimise the desirable outcomes can do their magic. Learning, on the other hand, is another story.

In a learning process, the affecting factors, nature of the information or collected data, and even the results are not easily defined. However, this is slowly changing as more developed technologies, such as natural language processing can make sense of sets of unstructured data.

However, combining learning data with performance indicators it is possible to reveal what kind of impact the training programs are producing. These outcome metrics can include customer service, sales or other measurable results. For education providers, the possibility to finally show what they can deliver through their training programs is now within their reach and will soon distinguish the best in the business.


Arm yourself with goal-oriented analytics

When we started our journey in developing Claned, we wanted to invent the new standard for learning analytics and how it provides the ability to support successful training programs. In order to do this, we had to create the best learning analytics in the business. And we did, and it is now available to enhance training programs anywhere. We believe the investment into learning platforms should contain a clear view into ROI, for example, through the number of drop-out rates, improved learning results, employee satisfaction, and improved sales.

We believe the use of learning analytics should relate to your training goals from the start.

That is why, in Claned, we focus on two main ways of using learning analytics to help education providers. Our learning platform holds inbuilt analytics for real-time follow-up on an education program level. These you will have for any course implemented in the platform. Secondly, we offer tailored data consultation services to answer specific challenges. Evidence-based decisions and personalization according to gathered analytics can significantly help you improve the experience for your learners.

If you want to hear more about how we can help you to achieve new heights of success for your training programs, get in touch and we tell you more.

Topi Litmanen

Dr Topi Litmanen works as a Chief Educational Scientist in Claned Group. He is responsible for ensuring, that the pedagogical aspects of the Claned are based on latest learning research. Topi makes sure that Claned customers get the needed support for meeting their digital learning needs.

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