Methodological techniques and approaches to developing empirical insights of cognition during collaborative information seeking

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

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The chapter is organized as follows. First, we will review collaborative information seeking (CIS) literature with the purpose of explaining how CIS is conceptually viewed and studied, highlighting the lack of cognitive research. Next, we will present a set of cognitively oriented methodologies that can be used in CIS research. We present a metafamily of cognitive-elicitation techniques known as knowledge elicitation (KE). KE is a prominent set of methods and techniques for understanding both individual and team-level cognition. In the KE section, we will provide a high-level overview of the methodologies that fall under KE. We will then provide subsections outlining how to specifically use KE methods in CIS, concluding with the presentation of a case study. Next, we turn our attention to cognitive task analysis (CTA). CTA is a goal-specific approach (often employing KE methods) to understand cognition during the performance of a task. Similar to the KE section, we will provide an overview of CTA, present a section on how to apply CTA to CIS, and conclude with a case study. Finally, we present the living laboratory (LL) approach. The LL is a holistic cognitively based research approach that attempts to understand cognition in context, further understand it in the lab, and then develop technologies/recommendations to improve performance in the real-world context. Sections relating to how the LL can be applied to CIS, and a case study will be presented.

Original languageEnglish (US)
Title of host publicationCognitive Systems Engineering
Subtitle of host publicationAn Integrative Living Laboratory Framework
PublisherCRC Press
Pages105-130
Number of pages26
ISBN (Electronic)9781498782319
ISBN (Print)9781498782296
DOIs
StatePublished - Jan 1 2017

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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