Sharing What Works

March 16 – 18, 2016 Orlando, FL

Register Now Includes:

LS201 Accountant, Strategist, or Sherlock: Using Learning Data in Context

1:00 PM - 2:00 PM Wednesday, March 16

Data and Measurement

Poinsettia/Quince

Most people in the learning and development field didn’t choose the profession because of a deep love for statistics, and few have ready access to data scientists for consultation. But the availability of an ever-growing body of data highlights the value of a fundamental understanding of data collection and analysis. Learning data will only provide valuable, actionable information if curated and evaluated strategically.

In this session, you will learn how to develop clearly defined, context-dependent information goals which will then serve to delineate the data required to meet those goals. Lessons and heuristics from other analytic fields, including business intelligence, competitive intelligence, and web analytics will be used to help provide you insight on the data requirements for a variety of information goals. You will also learn how to effectively communicate analytic results to stakeholders at various organizational levels.

In this session, you will learn:

  • How to define goals and context for data acquisition
  • How to take a strategic approach to data
  • The value of quantitative and qualitative approaches to improve insights
  • How to deliver context-specific results in terms relevant to stakeholders

Audience:
Novice and intermediate designers, project managers, managers, and directors.

Technology discussed in this session:
Common tools for data collection and analysis such as LMS, LRS, spreadsheets, and databases.

Janet Laane Effron

Managing Principal

Four Rivers Group

Janet Laane Effron is a data scientist who focuses on the creation of effective learning experiences through iterative processes, data-driven feedback loops, and the application of best practices in instructional design. 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.

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