Learning analytics: How to use data to measure the effectiveness of eLearning courses and improve learning outcomes

eLearning learning analytics measure eLearning effectiveness

UI/UX Designer

eLearning has become an increasingly popular mode of learning in recent years. However, with the rise of eLearning comes the need to evaluate its effectiveness. That's where learning analytics come in. Think of it as a way to gather and analyze data on the learning process to see what's working and what's not.

The first step is to gather data, which can be done through eLearning software or a learning management system (LMS). This data can be used to evaluate learner behavior and track progress, allowing you to identify knowledge gaps and critical areas for improvement. The second step is to analyze the data to direct and fine-tune your company's training roadmap, leading to continuous improvement in the learning process.

Learning analytics can provide valuable insights into the return on investment for training, as well as identifying the most effective learning methods. Data can be correlated with individual key performance indicators (KPIs) to estimate a precise return on investment (ROI) at the end of the analysis. Numerous other data points can also be collected and evaluated in order to test specific hypotheses. By collecting and evaluating data such as training costs, test results, and completion rates, we can determine what's working and what needs improvement.

But learning analytics isn't just about measuring the ROI of training but also to observe real-world skills development. Skills development is no longer merely a question of stocking up on knowledge, but about achieving higher levels of competence, such as specific problem-solving and real-world skills. This helps us understand how eLearning is preparing learners for the challenges of the modern workplace.

In addition to observing skills development, learning analytics also help to identify the most effective learning methods. For example, target group information such as device, location, selected content language, time of the day can be used to calculate time spent studying and compare target groups.

Data collected on learner behavior can provide valuable insights into their learning process. This includes information such as the number of content views, click behavior, video playback duration, and time spent on different types of media. These data points can be used to assess which content was successfully learned on the first attempt, identify learners’ interests, and determine their preferences. Results data, such as completion status, knowledge test scores, and the number of test attempts required, can also be used to gauge successful completion and adapt learning products to the learner's prior knowledge.

So, are you ready to take your eLearning one step further with learning analytics? Remember, the benefits of learning analytics go beyond measuring ROI or identifying the most effective learning methods. They also enable you to observe and foster real-world skills development, an increasingly critical aspect in today's digital landscape.



Lehnert, M. (2022) Learning analytics: How to use data to optimize learning outcomes, Knowledgeworker. Available at: https://www.knowledgeworker.com/en/blog/learning-analytics-how-to-use-data-to-optimize-learning-outcomes (Accessed: April 5, 2023).

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