Effectiveness of User Models in Reducing Cognitive Load

摘要

We strive to improve human performance through the adaptive filtering of information. The research results will help guide the design of future crisis/ battlefield management interfaces. Our experiments show: (1) eye fixations can be used as a measure of cognitive load in simple visual search tasks, (2) hand and finger pressures on a mouse indicate cognitive load in target selection tasks, (3) mouse click signatures can be used for continuous identity verification, (4) nested objects are significantly more difficult to count than adjacent objects, (5) performance decreases significantly with both map complexity and task complexity, (6) up to three static distractors make no difference in map route finding performance, (7) increasing numbers of moving distractors decreases map route finding performance, (8) having one distractor at a time move makes no difference in map route finding performance, (9) judgment of ratios is significantly easier when presented two-dimensionally rather than linearly, (10) training in one graphic data model style does not transfer to other graphic styles.