Cognitive load reducing in destination decision system

Chunhua Wu; Cong Wang; Qien Jiang; Jian Wang; Hong Chen

doi:10.1117/12.784057

9 January 2008 Cognitive load reducing in destination decision system

Chunhua Wu, Cong Wang, Qien Jiang, Jian Wang, Hong Chen

Proceedings Volume 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials; 67944H (2008) https://doi.org/10.1117/12.784057
Event: ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 2007, Gifu, Japan

Abstract

With limited cognitive resource, the quantity of information can be processed by a person is limited. If the limitation is broken, the whole cognitive process would be affected, so did the final decision. The research of effective ways to reduce the cognitive load is launched from two aspects: cutting down the number of alternatives and directing the user to allocate his limited attention resource based on the selective visual attention theory. Decision-making is such a complex process that people usually have difficulties to express their requirements completely. An effective method to get user's hidden requirements is put forward in this paper. With more requirements be caught, the destination decision system can filtering more quantity of inappropriate alternatives. Different information piece has different utility, if the information with high utility would get attention easily, the decision might be made more easily. After analyzing the current selective visual attention theory, a new presentation style based on user's visual attention also put forward in this paper. This model arranges information presentation according to the movement of sightline. Through visual attention, the user can put their limited attention resource on the important information. Hidden requirements catching and presenting information based on the selective visual attention are effective ways to reducing the cognitive load.

Citation Download Citation

Chunhua Wu, Cong Wang, Qien Jiang, Jian Wang, and Hong Chen "Cognitive load reducing in destination decision system", Proc. SPIE 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 67944H (9 January 2008); https://doi.org/10.1117/12.784057

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KEYWORDS

Visualization

Data hiding

Brain

Visual analytics

Cognitive modeling

Data processing

Visual process modeling

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