A quick guide to analytics

31 October 2022 by Rachel Sweeney

If you’re using an LMS or LXP to curate and deliver digital learning, you’re inevitably collecting data.  This learning data can help L&D and HR professionals take action to enhance training and performance.

 

What is learning analytics?

Simply put, analytics is the collection and analysis of data.  Analytics can give you a more complete view of aspects of learning from enrolment, through engagement, to completion and performance.  It provides the evidence and rationale for the planning, design, development, implementation, and evaluation of digital learning.  It highlights challenges and points out the way to resolve them.  

But what data should be captured and what should we do with it?  While the granular nature of the learning data captured is impressive at first sight, it’s worth very little if it can’t be analyzed and utilized.  

What learning analytics can tell you

  • Where you’re at: The data captured by your learning management system paints a picture.  It outputs and visualizes raw data in reports or dashboards.  You can use this data to measure where you are against your learning objectives and KPIs.  The data points range from the total number of successful enrolments in a course right down to individual interactions with individual screens or pieces of content.  Analytics offers both a holistic and a granular view.
  • Take-up: Your analytics tools show details of enrolment and content accessed by learners.  Analytics will capture individual and aggregated rates of learner choice, engagement, and completion.  It will also reveal the time learners spent engaging with content and what wasn’t accessed.
  • Learner progress: You can use analytics to track how learners are progressing through a course or a process (like onboarding).  The system collects data on quiz or test results, milestones reached, awards and badges received, and certification achieved.  Analytics records completion and failure to complete – vital information in an area like compliance, for example.
  • Learner experience: You can observe learner progress from captured user interaction data and provide additional data capture points to record the learner experience.  Surveys, polls, and feedback opportunities in your digital learning programs allow learners to record their views and add more individual, experiential data to the mix. 
  • ROI and effectiveness: The learning data collected can be used to calculate ROI.  You can relate rises and dips in performance after training back to the uptake, engagement, and completion data from analytics.  This analysis determines the effectiveness of training and indicates where you need to intervene and make changes.

What you can do with learning analytics

  • Improve your content: Analytics gives L&D and HR the data to decide where training needs to be enhanced.  Information on learner uptake and engagement and feedback from learners giving their preferences and recommendations will lead to better design and management of content.
  • Make L&D more responsive and proactive: Data on what’s working and what isn’t allowed L&D to make more targeted and timely interventions.  This could be in the form of breaking up content, increasing interactivity, introducing more frequent quizzes, or creating new micro content for immediate use, rather than waiting on the next cycle of course development
  • Overcome skills gaps: Analytics enables you to see and identify areas of low uptake and potential gaps.  You can then take action to address these skills gaps either by directing learners to the training that’s there, repurposing it (as microlearning, for example), or creating new content.
  • Introduce personalization: Analytics gives you a clearer picture of how individual learners are progressing in relation to other learners and their own personal development goals.  This provides an opportunity to personalize learning by creating learning pathways that take account of the individual’s experience and learning development needs.
  • Suggest content: Learning analytics can be used to record learner choices and infer learner preferences. The data feeds into AI-powered recommender functions within the LMS to automatically push new content recommendations or refresher training to individual learners.
  • Improve the learner experience: Analyzing learning data means you can allocate training resources more effectively.  The insights gained from tracking learning interactions and progress plus feedback from learners themselves help to optimize the learner experience.  A better learning experience in turn boosts engagement and improves knowledge retention. 
  • Increase quality: Increased access to critical data offers the chance for more regular and evidence-based reviewing and enhancing of training content.  That process promotes standardization and evaluation.  The review cycle helps raise the quality, engagement, and effectiveness of your digital learning offering.

 

Learning analytics is a vital tool in developing and improving training programs.  The hard data it provides enables you to get a handle on what’s working in your training programs and what’s not.  Analytics gives you the insight to take timely and effective remedial action and fully realize your investment in learning.

 

If you’d like to learn more about how Learning analytics can help your organization, get in touch now.

Rachel Sweeney
Digital Marketing Executive

Since joining Learning Pool’s Marketing team in 2018, Rachel focuses on Lead Generation, qualifying any potential leads and working closely with our Sales team.

Rachel also works on creating and promoting marketing campaigns around Learning Pool’s products and services and managing the ever-growing team content planner for our website and social media platforms.

Outside of work, Rachel loves being a new mum, getting to the gym and spending family weekends away in Donegal.

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