There’s a lot of talk these days about Big Data and analytics. It’s a relatively new topic within the LMS community, but a critical one to get right with your organization’s LMS. Taking stock of what a vendor or package can offer around analytics and reporting is essential when selecting a new LMS, and this article will give you an idea of what to look for.
What Big Data can do for eLearning
The first thing to keep in mind is the purpose of even attempting to make use of data analytics within the context of your company’s eLearning efforts. The reason you want robust analytics in your LMS is to make informed decisions that will lead to better learning outcomes.
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In fact, one way to define analytics specifically for the LMS environment is to say that it’s analyzing data gathered from users in and around the LMS that facilitates decision-making that leads to improved learning outcomes.
An LMS has the potential to generate huge amounts of data – the real challenge is in figuring out what data you should be looking at and analyzing and how it can be presented in a way that facilitates informed decision-making.
Not all analytics are going to be useful to all users. Your company wants to know if its eLearning programs are getting the results desired – which first and foremost assumes you have spelled out what you want your LMS to accomplish. But there are also analytics that can be useful to your learners, helping them to get more out of their eLearning.
On the learner side of the LMS, there are three essential analytics that can help them be more successful:
- Progress Indicator: specific to the course being taken. Your learners should have constant, easy access to a progress indicator that tells them where they’re at in a course and what’s coming next to move them towards completion. When learners have the opportunity to engage in short-term planning that a progress indicator encourages, they tend to be more successful.
- Success indicator: This shows them their current level of relative success. Learners need to know if they are on-track or need additional time with a given topic. This also allows for the introduction of a competitive aspect to the eLearning process, which some may find useful.
- Interactive Engagement Indicator: The more that students can interact with peers and/or instructors, the better their learning experience will be. This analytic can be used to spur increased interaction.
Things your company should pay attention to include the following:
- Learner Participation: Which students are doing well and which need a bit of a push to deepen their participation? Your LMS should be able to provide you with a simple, quick view of learner participation levels.
- Learner Success: Just as students need a snapshot of relative success, your company needs to know if users are learning what’s intended. This will typically be achieved through various kinds of learner assessments (see the article, LMS Must-Have #1: Robust Assessment and Feedback Options).
- Learner Exposure/Success Ratio: How many exposures to a topic lead to a student’s success? Too few may indicate the course is too easy, too many may indicate the course is too difficult, or that the material needs to be presented in a different way. As this ratio is likely to differ among individual learners, it also presents a window into what each learner needs in terms of support.
- Course Quality: Soliciting feedback from students at various points is critical for identifying ways that the course or LMS can be improved.
The above represent just a sample of the kinds of LMS analytics that many find useful. Does your LMS provide easy access to these kinds of data analytics? How easy is it to pull reports on these kinds of data? Are the reports presented in a format that is easy to understand and use? Keeping these questions in mind can help your get the most from your LMS analytics.