This quote is originally ascribed to mathematician Clive Humby in 2006. But this quote got real traction when “The Economist” published a report in 2017 with the title “The world’s most valuable resource is no longer oil, but data”.  The biggest companies in the world by net worth – Alphabet (Google), Microsoft, Apple, Amazon, and Facebook are all technology-driven firms that have access to the data of their users. As there is a greater awareness of how these firms use the data of people, there’s a greater thrust on privacy and control of data. eLearning as a separate sphere of technology has grown immensely in the last decade. We have been fortunate enough to witness the growth of learning from computer-based learning to smartphones and mobile apps and personalized on-demand learning content delivered on a device of the learners’ choice. In this blog post, we seek to examine the importance of data-driven learning, how organizations are creating solutions to generate and analyze this data, and why you need a smarter learning platform to offer an engaging learning experience.

Role of Data in eLearning

Data plays a significant role in eLearning. Let’s look at the key facets:

1 – Learner analytics based on course progress and completion

2 – Data on learner behavior and preferences to build a recommendation engine

3 – Data used to create a better learning experience

Is the Course Offering Value?

When the learning administrator and the L&D managers get information about the progress of a group of learners about a specific course it gives them insights about the popularity and value of the course. Typically, we observe employees being forced to take up compliance courses, because the laws of the land require them to do so. But how interesting can a compliance training course be made into? Can we add elements of gamification or adopt a storytelling approach to make the course more interesting? Data helps decision-makers decide if the course is effective or if a new course needs to be deployed to educate the learners better.

Perfecting Recommendation Engines with Data

When you search for a product on Amazon and then decide to shop later the algorithms powering the shopping behemoth store data based on your shopping search queries. The next time when you decide to search for the product on Amazon, you are shown a host of recommendations even if you look for something totally different between the two searches. This is a subtle push to make you buy more! It is also the power of data and recommendation engines that are designed to make your shopping experience better. The same logic applies to eLearning. As learning at the modern workplace becomes more open and focused on improving the employees’ knowledge; we are seeing more organizations moving out of a forced/closed learning ecosystem. Essentially a system where your manager controls what you should learn and not what you ideally want to learn.

Learning systems are integrated with employee talent management systems and data flows both ways. The learning system recommends ideal learning programs to help the employee perform their tasks better. Course progress and completion data flows back to the TMS and this in turn is linked to employee performance data. If the L&D manager and the senior staffing managers feel that an employee despite completing specific programs is not improving work-efficiency, then remedial actions are prescribed. These include better training and in-person counseling to help understand any issue that the employee may be facing. We observe that data helps organizations to create an ideal employee experience. Be it building better learning experiences with revised training content. Recommending the ideal learning path for employees, or co-relating training data and performance metrics; data is a valuable resource for everyone.

How Does Data Flow in Learning Systems?

To understand how data flows in learning systems, we need to be aware of a few terms – LRS or the Learning Record Store, xAPI or Experience API, and the LMS or LXP that everyone knows. A traditional eLearning program or course comprises the following components:

• The actual course – this could be a video, presentation, or text file, or a combination of all elements
• The assessments linked to the course
• Learning resources built into the course
• Any external links to explanatory content that direct to a resource outside the course
• Additional resources that the learner accesses of their own volition and linked to their course     

Learners could access the learning content via their computer or laptop or use a mobile app to access the learning. It is important to synchronize the learning progress across different devices and networks. In this blog post on the Origin Learning Blog we had listed out how the LRS works and how it is used to track data. Re-using the image below to explain the functioning of the LRS in greater detail.

This is how data flows – from the interactions of the learners with the learning system and external resources all facilitated through the LRS and recorded and transmitted back to the learning administrator’s dashboard or as per the requirements listed by the organization. Linking this information to the ERP or CRM is based on the client’s discretion and requirements.

Data and Digital Badges

Digital Badges and credentials have a huge market of their own. With the growth in Blockchain-based certification providers and digital badges providers like Accredible, Bestr, and Badgewell there is greater importance on having up-to-date data on course completions and certificates. Systems can be engineered to offer automated certificates and digital badges based on course-completion. Learners can display these badges on their portfolio or LinkedIn accounts.  

What the Future Holds?

‘Data-analytics’ – two decades ago this term would not have held much relevance outside academia or government agencies looking at population registers and electoral charts. The growth of the Internet and all associated businesses that arose out of it have given birth to this market for ‘data’. The hunger for personalized data among organizations to sell individuals data-driven products will never end. In an era of app-driven shopping, instant reviews, multiple vendors selling the same product at different prices; data is the all-important factor that helps make a purchase decision. The same holds good for modern workplace learning as well. We are increasingly observing the use of platforms like LinkedIn Learning, Udemy, and Coursera at work. These are all platforms that have millions of users on them with perhaps LinkedIn Learning leading the roost. LinkedIn also has the convenience of displaying targeted ads on the main LinkedIn platform as well. With the right data-sets targeted advertising can influence users to sign up for a program.

That was just one aspect of data – data-driven marketing. The next big factor to consider is data-driven employee performance and engagement. By offering employees the opportunity to learn and grow in their roles; organizations create a positive learning and working environment. Repeated surveys by LinkedIn show that employees thrive and prefer to work in an organization that place importance on their learning and growth. As an organization are you using employee performance metrics effectively?

What are your thoughts on data-driven learning for the modern workforce?