Learning Engineering: Data-Driven Mastery in Practice

Most training ends the moment a learner clicks submit. Jim Goodell joins IDIODC to make the case for something better: continuous mastery practice backed by real performance data. It's a shift from one-time compliance checks to lasting skill building.

Jim has spent years applying learning science and data to real-world design problems. He brings a data-driven lens to L&D, showing how xAPI and predictive feedback can be plugged into content for ongoing performance improvement. This one is about connecting learning directly to measurable outcomes.

Jim dives deeper into these topics in the upcoming webinar: https://learn.dominknow.com/make-lnd-a-driver-of-performance-not-just-compliance

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Jim Goodell is the founder of INFERable, using AI to bring mastery-based practice to learning platforms everywhere. He also edits the Learning Engineering Toolkit and chairs the IEEE Learning Technology Standards Committee, shaping the data standards behind modern edtech.

For over two decades, Jim has asked one core question: how do we know learning actually works? He blends learning science with real performance data to answer it, pushing L&D beyond checkboxes and toward measurable workforce impact.

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