Capturing Data to Improve the E-Learning Experience with Learning Analytics (Part 1) | ATD

Whether you work in industry or education, your training initiatives should have well-defined goals and produce measurable outcomes, as ATD reports.

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By clearly establishing objectives, collecting data, and analyzing trends, you will obtain a much clearer understanding of how well your training programs are performing. This will allow you to see which programs are working, what you need to improve, and how best to implement that change. Increasingly, learning and development (L&D) organizations are coming to appreciate the power of a rigorous analytics strategy.

Approaching Your Learning Analytics Data
Ultimately, the goal of data analysis is to obtain actionable information. To do this, you need to establish a consistent framework that gives context to your raw learning data. A complete analytics framework has two main components: strategy and techniques. Strategy refers to the high-level questions that will determine the key objectives, metrics, and tools for your analytics program. Techniques are the best practices that will allow you to design and implement an effective program.

In the first part of this two-part blog post, we will discuss the ‘Strategy’ piece...

Appropriately calibrating your expectations can mean the difference between a successful analytics program and one that fails to get off the ground. In our next blog post, Capturing Data to Improve the E-Learning Experience with Learning Analytics (Part 2), we’ll discuss the various techniques required for implementing learning analytics.
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In our last blog post (Part 1), we talked about how strategy can help align your approach to your learning analytics data. In this post, we will discuss the second part of that framework: techniques used for implementation. 

Source: ATD