Training can look successful on paper and still fail where it counts: on the job. We’re digging into the data literacy instructional designers and educators actually need right now, especially as AI tools speed up decisions and raise new privacy questions. If you’ve ever stared at completions, seat time, or quiz scores and wondered, “So what do I do with this information?”, this conversation is built for you.  We walk through the mindset shift that makes measurement useful: data is evidence, ...

Designing with Love

Jackie Pelegrin

Data Literacy for IDs: The Basics You Need to Work Smarter

APR 29, 20268 MIN
Designing with Love

Data Literacy for IDs: The Basics You Need to Work Smarter

APR 29, 20268 MIN

Description

Training can look successful on paper and still fail where it counts: on the job. We’re digging into the data literacy instructional designers and educators actually need right now, especially as AI tools speed up decisions and raise new privacy questions. If you’ve ever stared at completions, seat time, or quiz scores and wondered, “So what do I do with this information?”, this conversation is built for you.We walk through the mindset shift that makes measurement useful: data is evidence, not the mission. You’ll hear the three traps that quietly sabotage learning measurement and training evaluation, including confusing activity with impact, optimizing for easy-to-track metrics, and sharing more learner or project data than you intended when using AI. Then we break down five practical “data basics” you can apply immediately: inputs vs outputs vs outcomes, leading vs lagging indicators, correlation vs causation, data quality basics, and privacy by design with data minimization and anonymizing habits.To make it actionable, we translate everything into a simple, repeatable workflow: Measure, Interpret, Act. You’ll learn how to pick one metric per layer, ask better “why” questions, and choose the smallest change to test. We also share a concrete example where a 95% completion rate hides the real problem, and how scenario-based practice plus an in-workflow job aid can drive true behavior change. If you want to feel confident talking about impact and still use AI responsibly, hit play, subscribe for the rest of the AI Ready Designer Series, and share this with a colleague who needs clearer metrics.🔗 Episode LinksPlease check out the resource mentioned in the episode. Enjoy!Data Literacy Compass Send Jackie a TextJoin PodMatch!Use the link to join PodMatch, a place for hosts and guests to connect.Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Support the show💟 Designing with Love + allows you to support the show by keeping the mic on and the ideas flowing. Click on the link above to provide your support.☕ Buy Me a Coffee is another way you can support the show, either as a one-time gift or through a monthly subscription. 🗣️ Want to be a guest on Designing with Love? Send Jackie Pelegrin a message on PodMatch, here: Be a guest on the show🌐 Check out the show's website here: Designing with Love📱 Send a text to the show by clicking the Send Jackie a Text link above. 👍🏼 Please make sure to like and share this episode with others. Here's to great learning!