Thesis (M.S. in electrical engineering)--Washington State University, December 2009. / Title from PDF title page (viewed on Feb. 4, 2010). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 52-53).

<div>Design is complex and an important way to deal with the difficulties of design is to meet designer needs within the product development process. Many design methodologies are inapplicable and inappropriate in design practice because they were developed to be context-free universal processes. This thesis argues that design involves social and technical context. The social context influences the design process through social factors like negotiation. Negotiation will determine the outcome of major design decisions. Therefor the design process should guide designers in addressing social factors. The technical context influences design through how the design requirements are linked with the non-static environment in which design takes place. Therefor the design process should guide the designer in addressing the technical context as each tool or design methodology will determine the very character of the solution space. This thesis will identify the social and technical designer needs. This Thesis then builds on the core concepts of Collective System Design and Decision Drive Design to create a guideline for conceptual product design. This thesis then applies the guideline to develop a product to show that meeting designer needs will improve conceptual product development. </div><div><br></div>

<div>In 2019, cyber security is considered one of the most significant threats to the global economy and national security. Top U.S. agencies have acknowledged this fact, and provided direction regarding strategic priorities and future initiatives within the domain. However, there is still a lack of basic understanding of factors that impact complexity, scope, and effectiveness of cyber defense efforts. Computer security incident response is the short-term process of detecting, identifying, mitigating, and resolving a potential security threat to a network. These activities are typically conducted in computer security incident response teams (CSIRTs) comprised of human analysts that are organized into hierarchical tiers and work closely with many different computational tools and programs. Despite the fact that CSIRTs often provide the first line of defense to a network, there is currently a substantial global skills shortage of analysts to fill open positions. Research and development efforts from educational and technological perspectives have been independently ineffective at addressing this shortage due to time lags in meeting demand and associated costs. This dissertation explored how to combine the two approaches by considering how human-centered research can inform development of computational solutions toward augmenting human analyst capabilities. The larger goal of combining these approaches is to effectively complement human expertise with technological capability to alleviate pressures from the skills shortage.</div><div><br></div><div>Insights and design recommendations for hybrid systems to advance the current state of security automation were developed through three studies. The first study was an ethnographic field study which focused on collecting and analyzing contextual data from three diverse CSIRTs from different sectors; the scope extended beyond individual incident response tasks to include aspects of organization and information sharing within teams. Analysis revealed larger design implications regarding collaboration and coordination in different team environments, as well as considerations about usefulness and adoption of automation. The second study was a cognitive task analysis with CSIR experts with diverse backgrounds; the interviews focused on expertise requirements for information sharing tasks in CSIRTs. Outputs utilized a dimensional expertise construct to identify and prioritize potential expertise areas for augmentation with automated tools and features. Study 3 included a market analysis of current automation platforms based on the expertise areas identified in Study 2, and used Systems Engineering methodologies to develop concepts and functional architectures for future system (and feature) development.</div><div><br></div><div>Findings of all three studies support future directions for hybrid automation development in CSIR by identifying social and organizational factors beyond traditional tool design in security that supports human-systems integration. Additionally, this dissertation delivered functional considerations for automated technology that can augment human capabilities in incident response; these functions support better information sharing between humans and between humans and technological systems. By pursuing human-systems integration in CSIR, research can help alleviate the skills shortage by identifying where automation can dynamically assist with information sharing and expertise development. Future research can expand upon the expertise framework developed for CSIR and extend the application of proposed augmenting functions in other domains.</div>

<p>The primary research question of this dissertation is, \textit{How do contestants make sequential design decisions under the influence of competition?} To address this question, I study the influence of three factors, that can be controlled by the contest organizers, on the contestants' sequential information acquisition and decision-making behaviors. These factors are (i) a contestant's domain knowledge, (ii) framing of a design problem, and (iii) information about historical contests. The \textit{central hypothesis} is that by conducting controlled behavioral experiments we can acquire data of contestant behaviors that can be used to calibrate computational models of contestants' sequential decision-making behaviors, thereby, enabling predictions about the design outcomes. The behavioral results suggest that (i) contestants better understand problem constraints and generate more feasible design solutions when a design problem is framed in a domain-specific context as compared to a domain-independent context, (ii) contestants' efforts to acquire information about a design artifact to make design improvements are significantly affected by the information provided to them about their opponent who is competing to achieve the same objectives, and (iii) contestants make information acquisition decisions such as when to stop acquiring information, based on various criteria such as the number of resources, the target objective value, and the observed amount of improvement in their design quality. Moreover, the threshold values of such criteria are influenced by the information the contestants have about their opponent. The results imply that (i) by understanding the influence of an individual's domain knowledge and framing of a problem we can provide decision-support tools to the contestants in engineering design contexts to better acquire problem-specific information (ii) we can enable contest designers to decide what information to share to improve the quality of the design outcomes of design contest, and (iii) from an educational standpoint, we can enable instructors to provide students with accurate assessments of their domain knowledge by understanding students' information acquisition and decision making behaviors in their design projects. The \textit{primary contribution} of this dissertation is the computational models of an individual's sequential decision-making process that incorporate the behavioral results discussed above in competitive design scenarios. Moreover, a framework to conduct factorial investigations of human decision making through a combination of theory and behavioral experimentation is illustrated. <br></p>