What feels like effective training is not always what produces lasting learning.
In Episode 56 of Beyond the Blueprint, Matthew Hays, Ph.D., SVP of Research & Analytics at Amplifire, joins hosts Tim Jones and Kris Baird to explore the gap between how people think they learn and what cognitive science tells us actually helps knowledge stick. The conversation examines why performance during training can be misleading and how techniques such as retrieval practice, spacing, varied practice, and delayed feedback can strengthen long-term retention.
The discussion also tackles a challenge that is especially important in healthcare: every learner enters training with different knowledge, experience, and misconceptions. Traditional, one-size-fits-all training can spend valuable time teaching clinicians what they already know while failing to uncover what they do not. Matt explains how measuring both knowledge and confidence can reveal Confidently Held Misinformation™, when someone is confident in information that is actually incorrect. In high-stakes environments, those hidden misconceptions can carry significant risk.
Matt and the hosts also explore what healthcare organizations should expect from their investment in training. Completion rates and post-training assessments tell only part of the story. The more meaningful question is whether learning changes what happens on the job. That means connecting training to outcomes such as clinical performance, patient safety, and workforce readiness. A personalized learning approach can focus training on each learner’s actual needs while using cognitive science to build knowledge that lasts.
The conversation closes with AI and its growing role in learning. While AI can create new opportunities for personalization, Matt emphasizes that technology does not change the fundamental way the human brain learns. Effective AI learning experiences still need to be grounded in the science of how people build, retain, and apply knowledge.