Real-Time Adaptive Game to Reduce Cognitive Load

Games have the potential to be used to enable the general public to understand the application and implication of many forms of work. We demonstrate an adaptive game that simulates the activities happening in extreme environments where robots carry out tasks and human operators control robots. Under the emergency, operators can experience high cognitive load (CL), so the game dynamically adjusts its support strategy to the user's CL. We evaluated the adaptive game to find its effectiveness towards reducing user's CL in real-time by comparing it with the non-adaptive and randomly adaptive versions of the game. The results showed that the method developed to dynamically adjusts the game-support strategy to the user's CL was promising. The method reduced the CL significantly when compared to the randomly adaptive version, where the adaptations were randomly enabled or disabled on the game. The findings confirm the applicability of the method used to adapt the game and demonstrate the potential to be used to disseminate the work to the general public.