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How Data Can Inform Your eLearning Content

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Thought Industries
March 16, 2021
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The best learning organizations offer high quality and effective eLearning content. Good content brings in revenue, helps your learners succeed, and sets you apart from the competition. Whether you’re a professional training group or a customer education organization, it’s important to consistently look for ways to improve your eLearning content.

The first place to look for opportunities to improve eLearning is your data. Data is a powerful tool that can help you plan and build better experiences for your audience. To better understand how learning professionals can identify and use data, I sat down with two Thought Industries leaders: Daniel Quick, Vice President of Learning Strategies and Tim Harper, Senior Learning Experience Designer.

Learner engagement and pain points

Data comes in two forms, quantitative and qualitative. Either can be informative, but it’s best to use both kinds of data when making decisions. As Tim pointed out, “Together, they give you the insight you need to understand engagement and identify pain points. Learner engagement and pain are what powerfully inform your eLearning content.” To which Daniel added, ”Content must map against these needs, encourage engagement and drive consumption, address pain, and resolve friction.”

Learner engagement is simply that – how involved and engrossed learners are with your eLearning content, and whether they have made a psychological investment. One metric in your data that will help you understand engagement is the number of times learners access specific eLearning content. If there’s a spike – why? And what can we learn and do with what we learn?

Daniel provided a realistic view: “A spike might be due to superior eLearning content, and it might be that it was short or funny, or both. It might be all three. The point is what do we learn and how do we use it?”

How to increase engagement of eLearning Content

How do we use this kind of information to increase engagement with other eLearning content? Increased engagement results in satisfied learners that achieve their objectives. Satisfied learners are more likely to come back for more content and tell others about their experience. If you can identify the elements that engage your audience, you can find ways to use and combine these approaches for the best eLearning outcomes.

Pain points are the obstacles that can prevent a learner from realizing their goal. It might be a knowledge gap, outdated content, or something like scheduling conflicts. Regardless of the specifics, pain points can stop a learner from gaining requisite skills or knowledge. For the learning organization, pain points mean there won’t be any word of mouth or repeat business.

The data indicates pain points a number of ways. They might appear as drop-off rates in a course or video. They might appear as support tickets that focus on a particular topic. Assessment results can often show you what’s working and what’s not. Is a certain point missing in the instruction? Is another not clear enough for learners? Qualitative “voice of the learner” research can help you round out the picture, providing insights that make the quantitative data more actionable for improving your eLearning content.

All of these data points can be tracked to your business objectives. 

Data to improve customer education content 

Customer Education teams exist to create skilled customers. For instance, let’s say a SaaS company deploys training to teach customers how their tools work and how they fit together for specific use cases. 

There are a plethora of potential data sources that could indicate engagement for a SaaS company – smile sheets, content access, completion rates, digital badging, product analytics, etc. These data sources provide insight into customer retention and satisfaction, which are key metrics of success. Customer pain, which is also important to understand, is best expressed through support tickets, but search engine queries may also shed some light. 

“Data will lead you to what learners need,” said Daniel.

Informing professional training eLearning content and curriculum

Professional training is growing. One major reason is that more people are working from home. Individuals have time for self-improvement and they might feel the need to boost their marketability. eLearning content relevance and improvement will help your organization stay above the competition and keep your learners coming back. Without this, conversations about scalability are moot.

Professional training has clear education goals. Here’s a simple example: training to become a software developer. The goals of the training are to give learners the skills necessary to become a developer, and for them to get a job as a developer. These goals are inextricable if the training company wants to stay in business, and grow.

However, professional training is largely without the metric-rich environment of customer education. Their organization is not part of a larger corporation, like the SaaS company mentioned earlier. Learners want training to build specific knowledge, skills and competence that directly relate to the profession. They want to enter and advance in their field, like being a developer. To do this, they need to earn, maintain, or increase their professional credentials. Once they finish the course you likely will have plenty of quantitative data from their activity. But you will need qualitative data to best understand whether the learner was able to use what they learned to reach their goal. After you’ve collected this information through tools like surveys and interviews you will better understand your learners experience. You will also have a better interpretation of your quantitative data, and will better know what revisions are needed in your next eLearning content iteration.

Some of the metrics professional training companies use to measure engagement or pain points include:

  • Enrollment
  • Content usage
  • Completion, time to completion, and drop-out
  • Activity
  • Performance data (e.g., tests, exams, etc.)

A subject matter expert, or SME,  can provide essential insight into the profession of, say, being a barber. SMEs help you identify what a learner needs to know and helps you plan the learning steps they will take to go from beginner to novice to master. SMEs are also your conduit to developments in a profession and can offer guidance on responding to those changes. They can also help you address and predict the challenges that your learners will face. 

Getting started: How eLearning data can inform content 

Daniel suggests 3 avenues:

1. Get whatever reliable data you can. Don’t worry about being perfect. Make progress with what you have.

2. Prioritize the data. Look for signals on how your learning impacts your metrics. Incorporate the Kirkpatrick Model which evaluates all types of training results.

 

The Kirkpatrick Model was developed in the 1950’s and is still relevant today. The model consists of 4 levels which organize the data based upon its potential impact:

Level One is Reaction, or the learner’s reaction to the training. These are the smiley sheets and CSAT scores. They are the easiest to measure and the least useful.

Level Two is Learning, or did learning occur. Has there been an improvement in knowledge, skills, and abilities? An example would be pre and post-training tests.   

Level Three is Transfer, or was the learner able to apply the skills, did the training drive consumption? This is common with customer education but is very hard to track reliably in the professional training world.    

Level Four is Results, or what has been the impact of training on the business? Did this actually impact financial results or KPIs. It’s the hardest of all 

3. Iterate

Per Tim:  “Learn and iterate. Learn and iterate. You don’t have to be perfect, and you’re not stuck with the first attempt. Experiment.

“Some eLearning data is easier to collect – get the low-hanging, level one fruit. Talk to 10 learners. Don’t let all the possible sources paralyze you. You’re never really done.

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