Kayla Watkins
Papers
1
Total Citations
8
H-Index
1
About
Kayla Watkins investigates the intersection of robotic skill acquisition and human learning retention, with a focus on simulation-based training methodologies. Her most-cited work, “Utilizing Simulation to Evaluate Robotic Skill Acquisition and Learning Decay” (2023, 8 citations), challenges conventional assumptions about long-term skill retention in robotic platforms. Watkins hypothesized that a three-month break from training would actually reduce learning decay and improve retention—a counterintuitive finding that reorients how we design spaced practice in technical education. By leveraging simulation environments, she provides empirical evidence that rest intervals can strengthen procedural memory in complex robotic tasks. Her research carries significant implications for surgical robotics, manufacturing, and any field requiring sustained proficiency with automated systems. Watkins’s work bridges cognitive psychology and robotics engineering, offering practical insights for curriculum designers and trainers seeking to optimize learning schedules. Though early in her career, her focused contributions to understanding how humans master and maintain robotic skills mark her as a rising voice in human-robot interaction and training science.
Research Focus
Key Achievements
Top Papers
- 1