| Many consumer products such as telephones, home appliances, electronics, and computer hardware and software are intended to be used by adults of all ages. However, current human-computer interaction design methods generally fail to take age diversity into account. Methods used to predict expert users' performance, such as the Keystroke Level Model, rely on parameters derived from the performance of a cohort of younger users (<40 years of age). The contributions of this project are (1) a better understanding of the effect of age-related changes on the performance of interactive tasks and (2) a proposed version of the Keystroke Level Model, called ElderKLM, that uses parameters that reflect the abilities of expert older users. ElderKLM has the potential to enable designers of interactive systems to better understand how older users will perform with their products. |
