Leaders use Learning Analytics

How do we ensure that students or employees are learning in the best possible way? Many educational institutions and organizations struggle with that question. A simple answer is not obvious. Because what you need is insight into learning developments and into(desired)learning outcomes. What you need is Learning Analytics.

Learning Analytics: data about planned learning, learning itself and the analysis you can perform on that learning data. Learning Analytics gives you insights into who, what, when is learning and how that can be improved. You use these insights to optimize learning and eventually even personalize it. Max Mertens and Jan Rijken talked about this and explored the barriers and possibilities.

Optimize learning, make it more effective and personalize it

As soon as you get started with Learning Analytics, you immediately see its added value. Namely, you gain insight into how people learn and what results those new knowledge, skills and abilities lead to. Thanks to the analysis of that data, you can also see which learning interventions are effective, you can improve the efficiency and effectiveness of the learning interventions, and you can ultimately better direct investments in learning and development. You also see how important it is to formulate learning objectives before you start designing and rolling out the learning solution, otherwise you can never measure (the right) outcomes.

Ambitious L&D practitioners can then use learning insights to personalize the content and design of learning materials to further optimize learning experiences. Immediate action, you might say! However, educational institutions and organizations still need to take major steps to get the most out of Learning Analytics.

Mindset and translation

In many organizations, the competencies and mindset needed to actually use Learning Analytics are not yet in place. This is partly because data, statistics and analytics are just around the corner. In many cases, L&D practitioners do little or no testing of learning effectiveness, for example, and the translation at the strategic level (in departments such as human resources, C-level management) also lags behind. And that translation is badly needed to make the added value of Learning Analytics truly tangible.

KPIs and good data

And even if the knowledge and mindset are in place and the translation does take place, organizations still experience some stumbling blocks when using and deploying Learning Analytics. After all, it is essential that you measure what you want to measure. In business language: we need good Key Performance Indicators (KPIs). And these, in turn, must be determined on the basis of objectives in terms of sufficient learning and performance data and that data must be of good quality.

For assessment results (test scores) you need a good measuring instrument that you can put alongside learning behavior: if someone is engaged more often in an online learning environment, you should also be able to measure better results. But you also need to be able to access that data directly and easily from an online learning environment. And that is often difficult, because not all online learning environments are built according to this principle.

Key prerequisites for Learning Analytics listed:

• good KPIs (measure what you want to measure)
• sufficient data of good quality
• Learning ecosystem from which you can easily extract data
• resources, mindset and knowledge are in place to get started with this
• translate to strategic layer (human resources, management)

Follow the frontrunners

Despite some stumbling blocks and a few preconditions, there is a trend of more and more organizations integrating the vision of Learning Analytics into their day-to-day policies and L&D landscape. It is worth keeping an eye on those frontrunners or, where possible, already following them.

What do these pioneering organizations have that the rest do not (yet) have? A data culture. At the frontrunners, L&D is an integral part of determining the Key Performance Indicators, or what we are trying to achieve with our educational offerings. L&D is also involved in collecting, processing and analyzing data. Thus, L&D practitioners not only become more proficient and effective in using data, but analytics departments within organizations also gain visibility into what L&D practitioners want to achieve. Win-win!

More prominent role for practitioners

Learning analytics has much to offer educational institutions, organizations and their L&D departments, but gote steps still need to be taken to make the most of it. Currently, the added value is known to a small group. If we keep an eye on those frontrunners, their experiences will provide insight into valuable and concrete applications of Learning Analytics. We will also then know better what steps are needed to properly measure learning developments and improve learning outcomes.

The more often those insights are translated into approachable out-of-the-box solutions, the faster the necessary knowledge and mindset will follow. Role models, lots of research and concrete examples are needed to ensure that Learning Analytics becomes an integral part of the knowledge and mindset of L&D. Will you join us?