Leverage Data to Improve Your Learning

Join us for these eight sessions and learn to understand and read data to develop an actionable plan that can be used to improve your learning content and strategy.

DAY 1: September 27

Amber Boyd

101: Using Data to Align Training to Business Goals

Amber Boyd, Nationwide Insurance

8:30 AM – 9:30 AM PT

Do you find it challenging to marry business expectations with adult learning principles? In this session you will learn how to request the required data needed to establish rapport with your stakeholders to create learning experiences that will meet the needs of the business and learners. Learn more.

Bill Conran

201: How to Use Learning Data to Answer Key Business Pain Points

Bill Conran, Watershed

10:00 AM – 11:00 AM PT

Discover the data you’ll need to answer common questions, including tips on accessing and sharing these insights and selecting the visualization that suits your needs. We’ll explore questions by “analytics category” (i.e., learner experience, content utilization, learning programs) and run through questions that different business areas frequently ask. Learn more.

Sara Thompson and Traci Cantu

301: Automate and Visualize Learning Data for Improved Efficiency and Support

Sara Thompson, Your CLO

Tracie Cantu, Your CLO

11:30 AM – 12:30 PM PT

Businesses often deploy more than one software solution and without sophisticated integrations, it's challenging to get a view of learning ecosystem data. What if it was possible to do this without ongoing IT support? In this session you'll learn ways to automate the export and aggregation of data from your learning platforms and gain an understanding of how data visualization can ease administrative burdens and improve visibility. Learn more.

Alexa Krezel and Madeline Holiman

401: Taking a User Experience (UX) Approach to Learning Analytics

Alexa Krezel, Fannie Mae

Madeline Holiman, Fannie Mae

1:00 PM – 2:00 PM PT

You want to start turning the data from your learning ecosystem into insights that guide your people and learning strategy. So how do you do that? Discover how smart analysis of data can improve learner experience and help you deliver more effective programs by identifying pain points and factoring this into future learning design. Learn more.

DAY 2: September 28

Jason Haag and Chad Udell

501: xAPI Learning Analytics: Real-world Examples & Tool Evaluation Tips

Jason Haag, Veracity Technology Consultants

Chad Udell, Float and SparkLearn

8:30 AM – 9:30 AM PT

As the adoption of xAPI becomes more widespread, organizations are searching for solutions that can provide them with more usable data. This session will show more extensive reporting and learning analytics capabilities made possible by xAPI. We will also provide examples of how you can use the data you collect to help you make more informed business decisions. Learn more.

Leigh Ann Morgan

601: Seeing is Believing: Simplifying Complex Data with Visual Brilliance

Leigh Ann Morgan, Greene Tweed

10:00 AM – 11:00 AM PT

During this session we will explore the art of creating impactful infographics that effectively communicate complex data. You will discover strategies for simplifying complicated information, organizing content for clarity, and building compelling narratives by presenting data in a visually appealing way that resonates with your audience. Learn more.

Sandie Dela Cruz

701: Streamlining Learning Data Analytics with Power Automate and Power BI

Sandie Dela Cruz, Edwards Lifesciences

11:30 AM – 12:30 PM PT

This session aims to help learning professionals optimize their use of learning data analytics by integrating Microsoft Power Automate and Power BI. We will explore the concepts of automated workflows, data visualization, and reporting, fostering a more efficient approach to understanding and using learning data. Learn more.

Zsolt Olah

801: Data Literacy for L&D

Zsolt Olah, Amazon

1:00 PM – 2:00 PM PT

In order to have an impact, L&D must become fluent in the language of impact: data. This session focuses on the basics of data literacy skills for learning professionals: a mental model to think differently about data, fundamental knowledge of data classification, and some creative tools to get those who are not enthusiastic about data involved. Learn more.

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