Cognitive Engineering Considerations in the Development of an Information Retrieval System

Smith, Philip J.; Johnson, Dustin; Pruchnicki, Shawn; Schimmel, Josh; Spencer, Amy; Young, Sarah

doi:10.1177/1555343416654378

Cited by 1 publication

(2 citation statements)

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“…Enacting such change is not easy. Smith et al (2016) noted lessons learned as they advanced their design for general aviation pilots to review safety data. One is that “design is susceptible to cognitive narrowing” (p. 127), learned as they realized that, as developers, they continuously needed to reflect and return to the call “to go beyond providing simple information access and to craft integrated displays that support the user in applying his/her knowledge to more deeply understand the context of the data” (p. 129).…”

Section: Translating Science Into Practicementioning

confidence: 99%

“…Several studies in this past year highlighted some interesting potential connections. The use of prototypes, as demonstrated in Nemeth et al (2016) and Smith et al (2016), for example, creates a tangible, visible representation for the entire design team by which each design team member can assess his or her own measures of performance. Similarly, computer simulations of models of work (Nystrom et al, 2016) or judgment and decision making (Canellas & Feigh, 2016), despite admitting their imperfections, can be useful in assessing early in design whether the most profound aspects of cognitive performance will be supported.…”

Section: Translating Science Into Practicementioning

confidence: 99%

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A Year in Review

Pritchett

2016

Journal of Cognitive Engineering and Decision Making

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Reviewing the articles within this journal in 2016 reveals a diverse set of approaches and applications but consistent themes: first, translating practice to science and, second, translating science to practice. The first theme addresses the difficulty in understanding cognitive performance in complex work environments. For this, we need improved models of the myriad activities of workers in complex operations-recognizing that experts will adapt their behavior and need to respond to unexpected situations. Many of this year's articles note the need for multiple perspectives, for integrating multiple theories, and for recognizing that all parts of cognitive behavior are independent and, thus, no one factor can be isolated. The second theme, translating science to practice, then addresses the difficulty in applying this knowledge to improved designs. Such designs may focus on the worker (e.g., training), on processes and procedures, or on technology-regardless, they serve to translate understanding into implementation. A range of design approaches and insights are proposed in this year's articles, in domains ranging from rugby to aviation, health care, accident analysis, and autonomous systems.In his presidential address at this year's Annual Meeting of the Human Factors and Ergonomics Society (HFES), William Marras discussed the relevance of the HFES to the grand challenges in society. He concluded by stressing the need to translate science into practice, noting the vital insights that we can bring to bear.As editor in chief of this HFES journal, I have reviewed all its articles published this past year through this lens of translation. Although these articles span many methods and application domains, they all share an emphasis on addressing the unique attributes of complex work environments. Thus, JCEDM provides a unique role to the HFES, as well to the broader communities spanning human factors, cognitive engineering, human system integration, and cognition in complex work environments. Furthermore, I argue that JCEDM has a key role in translating the meaning of the "human factor" to society as we grapple with the increasing complexity of informationrich, technology-heavy work, particularly given that human cognition retains authority for sense making, for the outcomes of decisions, and for organizing teams and entire agencies or domains into successful courses of action.This paper frames two forms of this translation. First, the next section reviews recent advances in translating practice into science-studies that fearlessly waded into complex work domains, with all their muddy, multiple confounding factors and dynamics, and demonstrated how to describe (sometimes even predict) cognitive performance; here, the focus is on constructing models and theories that are valued for their content validity and their ability to then inform design. Second, I review recent advances in translating science into practice. If engineering is defined as "the practical application of scientific knowledge to society's benefit," th...

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Section: Translating Science Into Practicementioning

confidence: 99%