Handling complex real-world data with two cognitive engineering tools: COGENT and MacSHAPA

The ultimate concern of cognitive engineering is how complex sociotechnical systems might be designed so that humans can work within them and control them safely and effectively. Because of this, large amounts of observational data analysis and knowledge elicitation are incorporated in cognitive engineering. At many points, these two methodologies coalesce. In this paper, we describe two complementary cognitive engineering software tools—MacSHAPA and COGENT—that are being developed alongside each other. MacSHAPA is designed for observational data analysis, and COGENT is designed for knowledge elicitation and cognitive engineering, but both sup-port requirements gathering. We first outline current trends in cognitive engineering that have given rise to the need for tools like MacSHAPA and COGENT. We then describe the two tools in more detail, and point to their similarities and differences. Finally, we show how the two tools are complementary, and how they can be used together in engineering psychology research.

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