Designing Learning That Sticks: Using Data, AI, and Neuroscience to Improve Skill Retention
Wednesday, May 20, 2026 10:00 AM to 11:00 AM · 1 hr. (America/Los_Angeles)
Room 301B, Level Two
Solution Session (Provider-Led Education)
Solution Session
Information
Why do learners quit even when the content is high-quality and relevant? Many organizations invest heavily in upskilling programs, yet learners still drop off before new skills are fully developed. Let’s move beyond choosing content and into the neuroscience of how to increase motivation and retention.
When cognitive load overwhelms working memory, delayed feedback disrupts reward cycles, or assessment triggers threat responses, learners disengage, often permanently. Understanding what’s happening in learners’ brains allows learning leaders to move beyond surface-level engagement tactics and design experiences that actively regulate attention, effort, and persistence.
In this session, we’ll explore the neuroscience behind learner drop-off across critical moments in the learning journey. Drawing from applied learning science, behavioral data, and AI-enabled design strategies, you’ll learn how to use in-platform Coursera features to:
- Reduce cognitive overload during the first week of learning.
- Preserve productive struggle without triggering withdrawal.
- Design feedback systems that sustain motivation.
- Extend momentum after key assessments.
- Create adaptive experiences that maintain the optimal challenge zone.
You will leave with practical, brain-based retention techniques you can immediately use to audit and redesign your own programs. This session bridges neuroscience and modern learning technology to answer one core question: How can we design learning experiences that better match how the human brain develops skills?
When cognitive load overwhelms working memory, delayed feedback disrupts reward cycles, or assessment triggers threat responses, learners disengage, often permanently. Understanding what’s happening in learners’ brains allows learning leaders to move beyond surface-level engagement tactics and design experiences that actively regulate attention, effort, and persistence.
In this session, we’ll explore the neuroscience behind learner drop-off across critical moments in the learning journey. Drawing from applied learning science, behavioral data, and AI-enabled design strategies, you’ll learn how to use in-platform Coursera features to:
- Reduce cognitive overload during the first week of learning.
- Preserve productive struggle without triggering withdrawal.
- Design feedback systems that sustain motivation.
- Extend momentum after key assessments.
- Create adaptive experiences that maintain the optimal challenge zone.
You will leave with practical, brain-based retention techniques you can immediately use to audit and redesign your own programs. This session bridges neuroscience and modern learning technology to answer one core question: How can we design learning experiences that better match how the human brain develops skills?
Learning Objective 1:
"Recognize the brain-based drivers of learner disengagement in online and workforce learning environments.
"
Learning Objective 2:
"Design learning experiences that reduce overload, threat, and motivation loss while supporting skill development.
"
Learning Objective 3:
"Apply a neuroscience-informed framework to improve retention and completion rates using features available in modern learning platforms like Coursera.
"
Format
In-Person
Schedule-At-A-Glance
Solution Sessions
