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Data & 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.
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.
286 pages, Kindle Edition
Published April 11, 2023
17 people are currently reading
41 people want to read
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Displaying 1 - 2 of 2 reviews
September 12, 2023
I read about this book from an ATD email soon after ATD Press published it. Overall, I think it was a good overview of the power that analyzing learning data can bring, although I often found myself wondering if a full-scale data analytics team dedicated towards looking at learning has some lower threshold. The company I work for has about 280 employees and has no desire to delve that much into learning data. “Did you complete the course?” and “Did you fail on your first attempt?” are common questions. But there is no desire to delve into granular details, like how long they lingered on a page or if they second-guessed their multiple choice answer. I might use xAPI, but I’m not using it beyond the basic reporting functions. So at what point is this level of analysis justified?
I was really hoping for something more practicable for someone in my position, where I might use basic data collection from an LMS and turn it into something useful. Torrance seemed to scoff at this though, opting to talk more about massive data collection and learning record stores.
For someone like me, working with the basics of course completion status, score, time spent, and how the learner answered an exam question, I’m starting from very basic data. I was hoping that Torrance gave me more to go on. I’m not sure it’s her fault, so much as mine for being the wrong target audience.
I was really hoping for something more practicable for someone in my position, where I might use basic data collection from an LMS and turn it into something useful. Torrance seemed to scoff at this though, opting to talk more about massive data collection and learning record stores.
For someone like me, working with the basics of course completion status, score, time spent, and how the learner answered an exam question, I’m starting from very basic data. I was hoping that Torrance gave me more to go on. I’m not sure it’s her fault, so much as mine for being the wrong target audience.
April 15, 2023
A little thin on content for the price.
Displaying 1 - 2 of 2 reviews