3 Examples of Making the Most of Data in Learning

For the last few years, Big Data has been recognized as a valuable resource across many industries. The elearning industry has historically been interested in consumption data, like user completion rates and time spent in a course. However, our industry, like others, is expanding the role and use of data, especially data that is more readily available.

So, where can all of this data come from and what can it do? Keep reading! 

Look at the Details to Gain Insight

If you’re looking for more detail on how users experience and perform in elearning courses, consider a change to the tools you’re using on the course’s backend. By switching from SCORM to xAPI you’ll be able to gain far more granular insight into the performance and habits of your learners. A SCORM output will only capture a completion status and an assessment score. Whereas, xAPI gives you the capabilities to track just about anything in a course, e.g. whether or not a learner clicked on any additional resources throughout the module in an attempt to find the right answer, how long they viewed a video and how they responded to any question in the course. There’s a lot to be learned about how users are experiencing and navigating your course.  This can help you assess how effective you were with the course structure and design and tell you a lot about what content users are accessing. One Kineo client, for whom we developed a series of system help resources, uses data about what content users access to help inform what parts of the supported software may need design improvements.

Get Social to Track Application

How do we leverage our love of social into learning? Real data mining can happen when you integrate social tools into your learning design. These social tools can help provide insight and create discussions around far more detailed aspects of your course than “did everyone complete it?” and “did they think it was okay?”

Social data can be used to connect learners and track progress. Assignments and follow-on activities that call on learners to share what they learned, to apply new knowledge and to report progress offer a wealth of data and insight.  This information can be mined to measure application and impact. For example, when working with HT2Labs, Intercontinental Hotel Groups (IHG) used a MOOC platform as the central hub for accessing content and completing weekly assignments that included discussions, sharing content and tracking their outcomes.  With the help of xAPI, HT2 was able to mine this data to measure the impact of the course. Check out the case study for more detail.

Data Isn’t Only about Training

It’s safe to say the L&D department is late to the big data arena.  Our peers in other departments have been collecting and analyzing data for quite some time.  This is data we can leverage to inform what training is needed and to measure our success. A very simple example to consider is that of POS data – the cash register in a quick serve restaurant.  Imagine a quick serve restaurant wants to increase the throughput per cashier during the lunch hour rush (the # of customers they help per hour). Data from their POS will tell them a lot.

  • They have data on how many customers each cashier handles between a set time.
  • They can also see that, for example, on average a cashier reverses 10 transactions per hour.
  • They can also see what item(s) are ordered on the transactions that result in errors.

From this data they form a thesis: cutting the number of errors in half will increase throughput at the lunch rush by 5% per cashier. The company decides to build a game that gives cashiers practice  with the problem transactions and simulates the pressure of the lunchtime rush.  They will then continue to monitor the same data that informed the training solution to monitor results.

A second example comes from Yet Analytics and how they collected activities including the opening, closing, and re-opening of issues from repos on the GitHub platform as interoperable xAPI data.   The information collected includes the timestamp of the event, the description of the issue on GitHub (e.g., “Dreamweaver crashes opening HTML or PHP files calling Bootstrap 3 files”), the User, and the verb (e.g., the User “closed” the issue). This data is then analyzed to better understand the learning needs of the Users.

To learn more about how xAPI can improve your courses, check out our recording 5 things you can do with xAPI that will change your life.