Learning Analytics

This learning analytics online course from AIHR helps you develop the skills needed to track the impact of your employee training programs and the costs involved. You will have clear insight into what you need to improve to increase the effectiveness of your training. This is your first step to designing cost-effective learning solutions that not only help your workforce reach their full potential, but also contribute to your business success.

As a Learning and Development professional, your responsibility doesn’t stop at designing and implementing L&D initiatives that are valuable, effective, and applicable to your workforce. You also need to have the data to support your learning interventions and get buy-in from business leaders and key stakeholders.

AIHR’s learning analytics program is designed with practicality and applicability in mind. The theoretical component of the course is always accompanied by concrete examples. This makes it easier to understand how the theory behind learning metrics and analytics plays out in real life. Additionally, you’ll study popular models in the field of L&D (such as the ADDIE model and the Kirkpatrick Model) and have the chance to apply them in practical case studies.

A learning analyst (also called a training analyst) collects and interprets data on L&D activities to show whether employee training is working. That means tracking participation and completion, measuring knowledge and behavior change, and connecting learning outcomes to business results like performance, retention, and productivity.

In practice, a learning analyst’s work includes:

• Gathering qualitative and quantitative data across workforce training programs
• Building dashboards and reports that use clear learning metrics and analytics to communicate progress
• Calculating learning ROI to justify L&D budgets and investment decisions

AIHR’s learning analytics course teaches you to do this effectively, even if data isn’t traditionally part of your role.

Learning analytics covers a wide range of data points and methods used to evaluate and improve L&D efforts. Common examples include:

• Completion and engagement rates for training programs, showing where employees drop off or disengage
• Pre- and post-training assessment scores that measure actual knowledge or skill gains
• Learning ROI calculations that weigh training costs against measurable business benefits
• Manager and employee feedback data linked to performance or productivity outcomes

AIHR’s learning analytics course walks you through a step-by-step process to analyze data like this, so you can build an L&D program that delivers real business impact.