AI and Gamification Technologies for Complex Work

The medium through which training in the workplace is delivered has been changing in recent years to offer a more personalized and immersive experience.

Phillip M. Mangos, PhD, is the CEO and Chief Scientist of Adaptive Immersion Technologies, a Florida-based business focused on the synthesis of predictive data modeling and analytics, simulation, and assessment technology to optimize human performance. He holds a BS in Psychology from the University of South Florida and a PhD in Industrial/Organizational and Human Factors from Wright State University. With a diverse career background, he has worked as a team member to support projects in aviation, law enforcement, transportation, intelligence, information technology, and utilities industries. James C. Ferraro, PhD, is a Senior Human Factors Research Scientist at Adaptive Immersion Technologies. He specializes in intelligent simulations and game-based assessments to improve human performance in complex, automated systems. He holds a PhD in Human Factors and Cognitive Psychology and an MA in Applied Experimental and Human Factors Psychology from the University of Central Florida. His research focuses on human-machine interaction, trust in automation, and performance prediction. Dr. Ferraro has contributed to government-sponsored projects and co-edited multiple book series on human performance and simulation, with numerous publications in the field.

- A Theoretical Framework for Performance Analysis in Competency-Based Experiential Learning Environments - Instruction Intervention in Game-Based Assessment of Unmanned Systems Operator Performance - Game-Based Small Team Training: A Guide to Implementing Adaptive Game-Based Simulation Training - Game-Based Tools for Highly Automated Work: Trends, Challenges, and Opportunities - Artificial Intelligence Explainability: A Human Factors Approach - Using Artificial Intelligence to Train Human Intelligence: Theory and Practice in the Design of Adaptive Training Systems - From Manual to Machine Learning: Reflecting on the Development of an Adaptive Training System for a Military Decision-Making Task - Exploring Cognitive Science Foundations for AI-Driven Healthcare Simulation - Augmenting Rater Judgment Using Artificial Intelligence - AI and the Employee Lifecycle: What We Know and What May Come