Data and analytics for instructional designers

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. "With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before but don't often have the skills necessary to extract and apply the data. Data and analytics pro Megan Torrance delves into the foundational concepts that 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--starting with planning how to gather data and ending with building scale and maturity in your data operatins."--Description from page 4 of cover "At the same time, I can argue that a singular focus on data-driven results may lead to gaps in understanding and result in errors in judgment. Consider Chris Anderson’s words, “There is no guarantee that a decision based on data will be a good decision.” And this from Simon Caulkin, summarizing a 1956 VF Ridgeway article in Administrative Science Quarterly: “What gets measured gets managed—even when it’s pointless to measure and manage it, and even if it harms the purpose of the organization to do so.”That last sentence should be among the take-aways you have from this book.