6 Ways to Improve Courses with Data-Driven Learning Design

data driven learning design

What is Data-Driven Learning Design

Data-driven learning design means using data when making design decisions for the elearning course. The typical learning products designed with a data-driven mindset are almost always more effective because they eliminate barriers to positive training outcomes that often hinder learners’ progress in a conventionally designed course.

Often, when we start looking at how learners engage with our content, we start to uncover that maybe what we assumed is not necessarily correct. We can even start seeing some trends and insights that can inform future design decisions and lead to better engagement and more effective courses.

While using a data-driven design approach sounds like a no-brainer, it requires additional work to collect and analyze learning data. This could be tricky for many learning experience designers who are not engaged in data analytics as part of their day-to-day responsibilities.

Data-Driven Learning Design Examples

Here are 6 actionable tips to help you get started with data-driven learning design:

1. Revise the instructions you provide

While some learners who are less experienced with elearning may find the meticulous instructions helpful, others may find thorough instructions condescending. Most people know how to use a computer, and how to use the mouse button to drag things around. You can experiment with the instructional language to see if using less or more thorough instructions leads to changes in activity engagement. Measure how the learners engage with the content, then change the instructions, and measure engagement one more time. You now have excellent data points to use when designing learning activities.

2. Add storytelling to dry content

Oftentimes, when the learners find the training content too dry, they may skip it altogether. In other situations, when the learners find the training content too watered down, they may also skip it. So, what can you do about it? One suggestion is to collect training data to identify the slides or chapters that are often skipped. Then try adding storytelling elements and measuring the learners’ behavior one more time. If they are now spending more time with the content, chances are storytelling makes the content resonate with them.

3. Analyze learning activities

It’s often a good idea to collect data points on how learners engage with the activity. Are they completing it? How long do they stay on the slide? Are they, perhaps, coming back to it? This information will help you understand the level of learner engagement with content, and you can use it to make future data-driven learning design decisions.

4. Check what device they use to access the training

Learning experience designers often don’t realize that the learners may be using more than one device to access the training. Consider tracking the types of devices they log in on. Do they mostly use mobile devices? Do they only take training on the desktops? This data is important because the screen type and size can dictate many learning design decisions we make daily.

5. Pay attention to the presentation method

The same type of content can be presented in a text-only PDF file and a talking head video. But which approach is more effective? And which approach do your learners prefer? You will never know for sure unless you try both, and measure the retained knowledge, learning outcomes, and learner satisfaction in each test.

6. Measure content value

Understanding what content the learners find useful is critical to designing effective learning. You can start by measuring the time spent on and engagement with different pieces of content. This data will show if the learners see value in the content you offer. The data-driven learning design can help you understand what types of content, what formats, what media, even what types of headlines engage the learner and make them stay on the slide longer.

If you haven’t been using a data-driven design approach in the past, start by looking at the behaviors of the learners. Collecting multiple data points and measuring engagement can shed light on how the learners use the materials you produce, what types of content they engage with, how long they stay on a slide, what devices they use, etc. If you put all those answers together, you will have a comprehensive pool of data that can help answer many of your design questions. And, if implemented properly, this can lead to higher engagement levels and better training outcomes. This is the power of data-driven learning design.

How to Get Started with Data-Driven Design for eLearning

Having access to the right tools is key to successful data-driven learning design. You need to be able to gather the needed information consistently in order to track data points and run experiments. This means having the right infrastructure and skills needed for the task. One great way to get started is by partnering up with a reliable elearning development company that already has the right expertise and infrastructure in place.

If you are a learning experience designer or an elearning developer looking to improve your data-driven design skills, consider adding the Data Cloud widget for Articulate Storyline and Adobe Captivate to your elearning development toolset. The Data Cloud is a free and easy to use tool that will help you to start collecting learning data from the courses you develop. Start by tracking just a few metrics, and once you have enough data, move on to making predictions and running experiments based on the data you collect. You will start seeing patterns and finding ways to improve your courses in no time.




eLearning Company Blog | December 18, 2019