Author : Megan Torrance
Publisher : Association for Talent Development
ISBN 13 : 1953946453
Total Pages : 286 pages
Book Rating : 4.9/5 (539 download)
Book Synopsis Data & Analytics for Instructional Designers by : Megan Torrance
Download or read book Data & Analytics for Instructional Designers written by Megan Torrance and published by Association for Talent Development. This book was released on 2023-04-11 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Add Data and Analytics to Your TD Toolkit Instructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data—from how to design learning experiences with data collection in mind to how to use the data to improve and evaluate those experiences. With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before. With that comes the question of what to do with the data. While most data and analytics books focus on their application for measurement and evaluation and assume a prior baseline understanding of what learning data and analytics mean, Data and Analytics for Instructional Designers delves into the foundational concepts that will enable instructional designers and L&D professionals to use data in their roles. Split into two parts, the book first defines key data and analytics terms, data specifications, learning metrics, and statistical concepts. It then lays out a framework for using learning data for planning how to gather data and to building scale and maturity in your data operations. Megan reassures readers that basic math skills with some computer assistance is what you’ll need to get going. So set aside any math anxiety! Through a “If I can see it, I can be it” approach to learning data and analytics, the book blends practical what-is and how-to content with real-world examples and longer case studies from practitioners. Chapters conclude with opportunities for you to put these techniques to work right away, whether you are in a data-rich environment already, or whether you are just getting started and working on hypotheticals.