| The communication of precautionary information through symbols or pictorials has the potential to overcome language and educational barriers. Language independent communication is particularly important for populations that may not have otherwise received a text-based warning, such as non-English speaking immigrant workers. The primary objective of this research was to develop, implement, and evaluate a novel approach to symbol development utilizing interactive evolutionary computation (IEC) to expand end-users participation in the design process. At present, graphic designers, guided by their own intuition and creativity and usually working in isolation from the intended audience, develop the symbols used in warnings. Symbols are often not adequately evaluated prior to their introduction and may not be well suited for communicating their intended message. The use of the production method, where user input is incorporated in the design process, increases the level of participation and includes subjective preference to a limited extent.; IEC is one computer-based method for increasing the involvement of end-users in design that explores many possible solutions to a given design problem through human-computer collaboration. Specifically, this class of algorithms exploits an analogy between the design process and biological evolution (i.e., natural selection). A human designer guides the evolutionary process by judging the quality of novel solutions generated by the IEC algorithm, which evolve from one generation to the next based upon the user's input.; In this study, three participant groups, comprised of students as well as immigrant and non-immigrant industrial workers, used the IEC algorithm to develop 120 symbols conveying precautionary information. The symbols were evenly divided between two distinct referents, a laceration injury and awkward postures during MMH. These symbols were used to form composite symbols using three different methods: taking the median angles from stratification based on personal characteristics; stratification based on k-means cluster analysis; and stratification based on factor analysis in combination with k-means clustering. The quality, appropriateness, and comprehensibility of the resulting symbols was judged by the design group as well as a validation participant group. The symbols were evaluated in terms of preference rankings (relative comparisons) and comprehension estimates (independent scores).; The results suggest that IEC algorithms can be successfully integrated into a user-centered process of symbol design. (Abstract shortened by UMI.)... |
