Section III Theoretical Perspectives in Cognitive-Collaborative Systems

Methodological Techniques and Approaches to Developing Empirical Insights of Cognition during Collaborative Information Seeking

Nathan J. McNeese, Mustafa Demir, and Madhu C. Reddy


Over the years, the benefits of teamwork have been identified, especially its potential ability to positively increase efficiency and outcomes (Salas et al. 2008). For these reasons, teams are becoming embedded in almost every modern work domain. Domains such as education, homeland security, health care, and emergency crisis management are just a few that are dependent on high performing teamwork. The process of achieving effective teamwork is complex and complicated, relying on interactions among social, cognitive, and technical variables. Consequently, to better understand teams and the differences between high and low performing teams, researchers must seek to understand the many processes that are associated with teamwork. One process that is directly tied to teamwork is collaboration.

In response to growth of teams, collaboration and methods to support collaborative efforts are becoming increasingly important. Collaboration requires team members to communicate/coordinate and effectively work with each other. Historically, collaboration is conceptualized by variables of time and space (Schmidt and Bannon 1992). Collaborative efforts may occur instantaneously in real time (synchronous), or span over an extended time-period where communication is disparate and not instantaneous (asynchronous). Likewise, collaboration can occur within a physically isolated space (colocated), or via people communicating in multiple different spaces (distributed). Traditional means of collaboration are rooted in synchronous and colocated environments, but as technology continues to make advances, asynchronous and distributed collaboration is becoming more frequent. Modern day collaboration is dependent on varying levels of both synchronous/colocated and asynchronous/ distributed efforts.

To better understand teamwork, and more specifically, team decision making, it is important to understand the role of collaboration during this process. A specific type of collaboration that we view as fundamentally important to team decision making is CIS. Foster (2006) defines CIS as “the study of the systems and practices that enable individuals to collaborate during the seeking, searching, and retrieval of information.” In terms of team decision making, CIS is critically important. A team must first identify and articulate their problem set, and then seek to find information to achieve solving their problem. Therefore, if a team fails to collaboratively seek information, it is very possible that they will fail to solve their problem. CIS is a process that occurs early on during team decision making and continues throughout the team’s lifespan.

When considering CIS during team decision making, there are two specific research gaps. First, some of the most prominent team decision making theories/ models: Functional Theory of Group Decision-Making (Orlitzky and Hirokawa 2001), Multi-level Theory of Team Decision-Making (Hollenbeck et al. 1998), and Macrocognition in Teams Model (Letsky et al. 2007) fail to explicitly acknowledge the role and importance of CIS. Although information sharing is often identified as an overall step within the team decision-making process, there is little emphasis on information seeking activities. Second, and of particular importance to this chapter, the cognitive aspects of CIS have not been studied in depth.

CIS has been studied in both library/information sciences and computer-supported cooperative work (CSCW) mainly through two streams of research: social and technical (Karunakaran et al. 2010). The social stream focuses on examining how people perform CIS activities, seeking to understand the interactions that occur within their work domain. The technical stream focuses on translating many of the findings learned from the social stream and then developing systems or tools to support CIS-based activities or tasks. In both streams, the role of cognition during CIS is not widely discussed. When cognition has been studied within the context of CIS, it is a secondary goal and studied at the level of the individual and not the team (Shah and Gonzalez-Ibanez 2011). If the CIS research community is to fully understand and conceptualize CIS it is important to take a broader perspective that accounts for the social, technical, and cognitive streams. Searching, retrieving, and sharing information is dependent on both individual and team level cognition, so future research should account for understanding and articulating the role of cognition during CIS. Recent work by McNeese and Reddy (2013, 2015a, 2015b, 2015c) has sought to understand the impact that cognition has on CIS. Specifically, their work focuses on understanding how the concept of team cognition (see Mohammed et al. 2010, Cooke et al. 2013 for review) develops during CIS activities. In general, their research has indicated that team cognition does develop during CIS and that it greatly impacts to overall process of CIS. Further review of their work will be presented later in this chapter.

Although, it is important to acknowledge that future CIS research needs to focus on both individual and team cognition, it is also equally important that researchers know how to study cognition within the context of human behavior and performance. Without appropriate methods and theoretical understandings, it will be difficult to study cognition during CIS activities. Although eliciting and understanding cognition is complicated, understanding the specific methods to studying cognition is necessary to (1) appropriately capture cognitive activities and (2) understand these activities within the scope of context, tasks, and emerging demands. The purpose of this chapter is to provide researchers with multiple cognitively focused research methods and approaches to study cognition during CIS activities. Specifically, we look to the research domain of cognitive systems engineering (CSE) to identify different methodological techniques and approaches aligned with understanding cognition in the context of human behavior and performance.

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