Christopher Bennett
The University of Maine, Orono, Maine, United States
Safe and efficient navigation often relies on the development and retention of accurate cognitive maps that include inter-landmark relations. For many older adults, cognitive maps are difficult to form and remember over time, which introduces serious challenges for independence and mobility. To address this problem, we explore an innovative compensatory augmentation solution enabling enhanced inter-landmark learning via an “X-Ray Vision” simulation. Results with (n=45) user study participants suggest superior older adult cognitive map retention over time from a single learning session with the augmentation versus a control condition without the augmentation. Furthermore, results characterize differences in decay of cognitive maps between older adults and a control of younger adults. These findings suggest important implications for future augmented reality devices and the ways in which they can be used to promote memory and independence among older adults.
doi.org/10.1145/3613904.3642644
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)