How to Map Out Learning Analytics During the Front-End Analysis

Modern learning solutions can yield powerful analytics that strengthen the connection between performance and business outcomes. The worst time to determine if your analytics answer strategic questions or demonstrate performance improvements is once you begin authoring the solution. Instead, begin designing your desired end-state analytics during front-end analysis.

In this session you’ll learn how to pinpoint learning analytics during your front-end instructional analysis. Using multiple design frameworks, we’ll explore how to create a complete learning analytics picture from the beginning and start executing on it when you develop instructional interactions, assignments, or instructor-led training. To go beyond common L&D metrics and make the most of modern technologies (e.g., xAPI, HRIS), you need a clear roadmap for how learning data is sequenced and streamlined early in the design process. This session will use case studies to demonstrate the approach. We’ll also discuss the key questions to ask and methods to use to collaborate with SMEs and stakeholders and gain their valuable insight into learning data and analysis.

In this session you will learn how to:

• Assign relevant metrics to knowledge and skills outlined in Tiemann and Markle and Mager’s instructional design frameworks
• Match analytic needs to instructional methods
• Ask specific questions of SMEs and stakeholders during discovery to identify meaningful learning metrics before design and execution begins