LS105 Investigating Performance Using Data
10:45 AM - 11:45 AM Wednesday, March 22
Data and Measurement
Your access to learning-related data has grown dramatically over recent years. But just because you have a large volume of data doesn’t mean it necessarily provides value. While tools like xAPI make it increasingly easy to acquire data about learners’ activities, this information provides little benefit if you don’t know how to design to acquire meaningful data, interpret that data, or improve your learning design based on what you’ve discovered.
In this session, you’ll dive deep into how data should shape your learning systems design, including exploring the basic principles of how to use data effectively and how to design to provide meaningful feedback. To do this, you’ll look at outside inspiration from fields that are already doing this well: user experience design (UXD), web analytics, and business intelligence. You’ll also uncover some of the pitfalls of data collection and analysis, discuss using both qualitative and quantitative data, and address the difficulties inherent in finding valid measurements of learning.
In this session, you will learn:
- How to use your data analytics to improve course design
- How to design to gather meaningful data
- About the potential pitfalls of data interpretation
- Lessons, from fields like business intelligence and web analytics, about how to apply data principles to learning design
Novice and intermediate designers, developers, and managers.
discussed in this session:
xAPI and data analytics.
Sean Putman, a partner in Learning Ninjas, has been an instructor, instructional designer, and developer for over 15 years. He has spent his career designing and developing training programs, both instructor-led and online, for many different industries, but he has had a strong focus on creating material for software companies. Sean has spent the last few years focusing on the use and deployment of the Experience API (xAPI) and its effect on learning interventions. He has spoken at industry conferences on the subject and is co-author of Investigating Performance, a book on using the Experience API and analytics to improve performance.
Janet Laane Effron
Janet Laane Effron is a data scientist at HT2, an award-winning innovator in learning technology, where she develops learning analytics models to support improved design and performance. She has worked on xAPI design projects related to designing for performance outcomes and designing both for and in response to data and analytics. Janet’s areas of interest include text analytics, machine learning, and process improvement. She is also the co-author of Investigating Performance: Design and Outcomes with xAPI.