Want To Measure Training Success? Use Learning Analytics!

You’ve worked hard investing in a training program for your learners, but how can you tell it was a success? Measuring and recording the return on investment (ROI) for training is crucial for sustaining learning engagement and creating a supportive workplace. While it might seem like a daunting task to measure training success, learning analytics can help you pinpoint what you want from your training and how to get there. 

This post will walk you through the definition of learning analytics, explain how they reflect a learner’s experience, and break down how to measure the success of three different kinds of learners. 

What Are Learning Analytics And What Are You Looking For?

Defining Learning Analytics: Looking at training completion statistics alone won’t tell you if learners gained valuable knowledge from a course. This is when learning analytics come into play.

• The 1st International Conference on Learning Analytics and Knowledge defined learning analytics as the “measurement, collection, analysis and reporting of data about learners and their contexts.” 

Learning analytics ultimately help leaders understand why learner’s performed a certain way, and how they can perform better in the future. Before choosing the right learning analytics program for your organization, it’s important to address what you want to measure and how that information will help your team thrive. Here are a few examples of data that can be recorded from a learning analytics program:

• Learning engagement in assigned projects and activities
• Levels of digital literacy
• Interaction and effectiveness with digital educational tools
•  Learner behavioral data 

Learning experience analytics often assess how much a program is being used, how long it is being used for, and how learners navigate the overall training experience. Read on to discover what learning analytics can tell you about different types of learners. 

What You Can Identify Through Learning Analytics

When content developers use learning data, they can identify who is actively learning, who might need support, and if their team will reach their training objectives within a certain timeframe. 

• Some of the most successful learning analytics are mobile, which have been shown to attract learner’s attention, make for easy navigation, and fit seamlessly into everyday schedules.

With mobile learning analytics, you can see how many learners access optional resources and gain insight into your team’s digital literacy level. When measuring training success, it’s important to assess the performance of each learner and provide support where it is needed. But what kinds of learners should you look out for, and what does each one need?

The Self-Motivated Learner: If your learning analytics show that a learner signs in, completes material in solid chunks of time, and is quick to correct their errors, it will let you know that they are self-motivated and likely to succeed with slightly less support. 

For these kinds of self-motivated learners, make sure to provide positive feedback directly after they complete an assignment. By doing this, you’ll encourage them to continue their great work ethic and make them feel confident in their performance. 

Promoting Learning Engagement For Those Who Need It Most

The Struggling Learner: When a learner signs in and out sporadically and has trouble finishing material and completing tasks sequentially, this could mean that they need extra assistance moving through training. To motivate these learners, use analytics to find out where they got stuck, target those areas, and check-in with your learner to find out what they need help with. 

• Time is of the essence when helping a struggling learner. Intervening quickly will show them you value their learning experience and are willing to provide them with coaching, support, and extra assistance. Once you pinpoint the learning blocks, make sure to update content or adjust training settings accordingly. 

The Learner Who Is On Their Way: If a learner is moving through the course, fixing their mistakes, and paying attention to feedback, it’s a great sign that they are on the path to success. You might find that these learners need an extra boost of motivation to complete assignments on time and push themselves during exercises. 

• When providing feedback to these kinds of learners, try addressing their learning blocks in the beginning and ending their feedback session addressing all of the things they are excelling in. This will leave the learner with a positive outlook on their work, and inspire them to reach their full potential. 

Learning Analytics For A Better Future

At WeLearn, we know great course content needs a great learning analytic strategy to measure progress, issues, and goals moving forward. Not only do learning analytics benefit learners, but they also help instructors and business leaders build a more supportive community in their workplace and beyond. How has your organization been using learning analytics to measure training success? What kind of learner do you think you are? Share your thoughts with us here at WeLearn, because together we learn.