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  • × author_ss:"Cole, C."
  1. Spink, A.; Cole, C.: ¬A multitasking framework for cognitive information retrieval (2005) 0.02
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    Abstract
    Information retrieval (IR) research has developed considerably since the 1950's to include consideration of more cognitive, interactive and iterative processes during the interaction between humans and IR or Web systems (Ingwersen, 1992, 1996). Interactive search sessions by humans with IR systems have been depicted as interactive IR models (Saracevic, 1997). Human-IR system interaction is also modeled as taking place within the context of broader human information behavior (HIB) processes (Spink et al., 2002). Research into the human or cognitive (user modeling) aspects of IR is a growing body of research on user interactivity, task performance and measures for observing user interactivity. The task context and situational characteristics of users' searches and evaluation have also been identified as key elements in a user's interaction with an IR system (Cool and Spink, 2002; Vakkari, 2003). Major theorized interactive IR models have been proposed relating to the single search episode, including Ingwersen's (1992,1996) Cognitive Model of IR Interaction, Belkin et al.'s (1995) Episodic Interaction Model, and Saracevic's (1996,1997) Stratified Model of IR Interaction. In this chapter we examine Saracevic's Stratified Model of IR Interaction and extend the model within the framework of cognitive IR (CIR) to depict CIR as a multitasking process. This chapter provides a new direction for CIR research by conceptualizing IR with a multitasking context. The next section of the chapter defines the concept of multitasking in the cognitive sciences and Section 3 discusses the emerging understanding of multitasking information behavior. In Section 4, cognitive IR is depicted within a multitasking framework using Saracevic's (1996, 1997) Stratified Model of IR Interaction. In Section 5, we link information searching and seeking models together, via Saracevic's Stratified Model of IR Interaction, but starting with a unitask model of HIB. We begin to model multitasking in cognitive IR in Section 6. In Sections 7 and 8, we increase the complexity of our developing multitasking model of cognitive IR by adding coordinating mechanisms, including feedback loops. Finally, in Section 9, we conclude the chapter and indicate future directions for further research.
    Date
    19. 1.2007 12:55:22
    Series
    The information retrieval series, vol. 19
    Source
    New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole
  2. Spink, A.; Cole, C.: New directions in cognitive information retrieval : introduction (2005) 0.01
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    Abstract
    Humans have used electronic information retrieval (IR) systems for more than 50 years as they evolved from experimental systems to full-scale Web search engines and digital libraries. The fields of library and information science (LIS), cognitive science, human factors and computer science have historically been the leading disciplines in conducting research that seeks to model human interaction with IR systems for all kinds of information related behaviors. As technology problems have been mastered, the theoretical and applied framework for studying human interaction with IR systems has evolved from systems-centered to more user-centered, or cognitive-centered approaches. However, cognitive information retrieval (CIR) research that focuses on user interaction with IR systems is still largely under-funded and is often not included at computing and systems design oriented conferences. But CIR-focused research continues, and there are signs that some IR systems designers in academia and the Web search business are realizing that user behavior research can provide valuable insights into systems design and evaluation. The goal of our book is to provide an overview of new CIR research directions. This book does not provide a history of the research field of CIR. Instead, the book confronts new ways of looking at the human information condition with regard to our increasing need to interact with IR systems. The need has grown due to a number of factors, including the increased importance of information to more people in this information age. Also, IR was once considered document-oriented, but has now evolved to include multimedia, text, and other information objects. As a result, IR systems and their complexity have proliferated as users and user purposes for using them have also proliferated. Human interaction with IR systems can often be frustrating as people often lack an understanding of IR system functionality.
    Series
    The information retrieval series, vol. 19
    Source
    New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole
  3. Cole, C.: Activity of understanding a problem during interaction with an 'enabling' information retrieval system : modeling information flow (1999) 0.01
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    Abstract
    This article is about the mental coding processes involved in the flow of 'information' when the user is interacting with an 'enabling' information retrieval system. An 'enabling' IR system is designed to stimulate the user's grasping towards a higher understanding of the information need / problem / task that brought the user to the IR system. C. Shannon's (1949/1959) model of the flow of information and K.R. Popper's (1975) 3 worlds concept are used to diagram the flow of information between the user and system when the user receives a stimulating massage, with particluar emphasis on the decoding and encoding operations involved as the user processes the message. The key difference between the model of information flow proposed here and the linear transmission, receiver-oriented model now in use is that we assume that users of a truly interactive, 'enabling' IR system are primarily message senders, not passive receivers of the message, because they must create a new message back to the system, absed on a reconceptualization of their information need, while they are 'online' interacting with the system
    Date
    22. 5.1999 14:51:49
    Source
    Journal of the American Society for Information Science. 50(1999) no.6, S.544-552
    Theme
    Information
  4. Cole, C.: Information need : a theory connecting information search to knowledge formation (2012) 0.01
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    Content
    Inhalt: The importance of information need -- The history of information need -- The framework for our discussion -- Modeling the user in information search -- Information seeking's conceptualization of information need during information search -- Information use -- Adaptation : internal information flows and knowledge generation -- A theory of information need -- How information need works -- The user's situation in the pre-focus search -- The situation of user's information need in pre-focus information search -- The selection concept -- A review of the user's pre-focus information search -- How information need works in a focusing search -- Circles 1 to 5 : how information need works -- Corroborating research -- Applying information need -- The astrolabe : an information system for stage 3 information exploration -- Conclusion.
    LCSH
    Information behavior
    Information retrieval
    Information storage and retrieval systems
    Human information processing
    Information theory
    RSWK
    Informationsverhalten / Information Retrieval / Informationstheorie
    Subject
    Informationsverhalten / Information Retrieval / Informationstheorie
    Information behavior
    Information retrieval
    Information storage and retrieval systems
    Human information processing
    Information theory
  5. Cole, C.: Intelligent information retrieval : Part IV: Testing the timing of two information retrieval devices in a naturalistic setting (2001) 0.01
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    Source
    Information processing and management. 37(2001) no.1, S.163-182
  6. Yi, K.; Beheshti, J.; Cole, C.; Leide, J.E.; Large, A.: User search behavior of domain-specific information retrieval systems : an analysis of the query logs from PsycINFO and ABC-Clio's Historical Abstracts/America: History and Life (2006) 0.01
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    Abstract
    The authors report the findings of a study that analyzes and compares the query logs of PsycINFO for psychology and the two history databases of ABC-Clio: Historical Abstracts and America: History and Life to establish the sociological nature of information need, searching, and seeking in history versus psychology. Two problems are addressed: (a) What level of query log analysis - by individual query terms, by co-occurrence of word pairs, or by multiword terms (MWTs) - best serves as data for categorizing the queries to these two subject-bound databases; and (b) how can the differences in the nature of the queries to history versus psychology databases aid in our understanding of user search behavior and the information needs of their respective users. The authors conclude that MWTs provide the most effective snapshot of user searching behavior for query categorization. The MWTs to ABC-Clio indicate specific instances of historical events, people, and regions, whereas the MWTs to PsycINFO indicate concepts roughly equivalent to descriptors used by PsycINFO's own classification scheme. The average length of queries is 3.16 terms for PsycINFO and 3.42 for ABC-Clio, which breaks from findings for other reference and scholarly search engine studies, bringing query length closer in line to findings for general Web search engines like Excite.
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.9, S.1208-1220
  7. Large, A.; Beheshti, J.; Cole, C.: Information architecture for the Web : the IA matrix approach to designing children's portals (2002) 0.01
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    Abstract
    The article presents a matrix that can serve as a tool for designing the information architecture of a Web portal in a logical and systematic manner. The information architect begins by inputting the portal's objective, target user, and target content. The matrix then determines the most appropriate information architecture attributes for the portal by filling in the Applied Information Architecture portion of the matrix. The article discusses how the matrix works using the example of a children's Web portal to provide access to museum information.
    Footnote
    Teil eines Themenschwerpunktes Information architecture
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.10, S.831.838
  8. Cole, C.: Intelligent information retrieval: diagnosing information need : Part I: the theoretical framework for developing an intelligent IR tool (1998) 0.01
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    Source
    Information processing and management. 34(1998) no.6, S.709-720
  9. Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998) 0.01
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    Source
    Information processing and management. 34(1998) no.6, S.721-731
  10. Spink, A.; Cole, C.: Introduction (2004) 0.01
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    Abstract
    This is the second part of a two-part special topic JASIST issue an information seeking. The first part presented papers an the topics of health information seeking and everyday life information seeking or ELIS (i.e., information seeking outside of work or school). This second issue presents papers an the topics of information retrieval and information seeking in industry environments. Information retrieval involves a specific kind of information seeking, as the user is in direct contact with an information interface and with potential sources of information from the system's database. The user conducts the search using various strategies, tactics, etc., but there is also the possibility that information processes will occur resulting in a change in the way the user thinks about the topic of the search. If this occurs, the user is, in effect, using the found data, turning it into an informational element of some kind. Such processes can be facilitated in the design of the information retrieval system. Information seeking in industry environments takes up more and more of our working day. Even companies producing industrial products are in fact mainly producing informational elements of some kind, often for the purpose of making decisions or as starting positions for further information seeking. While there may be company mechanisms in place to aid such information seeking, and to make it more efficient, if better information seeking structures were in place, not only would workers waste less time in informational pursuits, but they would also find things, discover new processes, etc., that would benefit the corporation's bottom line. In Figure l, we plot the six papers in this issue an an information behavior continuum, following a taxonomy of information behavior terms from Spink and Cole (2001). Information Behavior is a broad term covering all aspects of information seeking, including passive or undetermined information behavior. Information-Seeking Behavior is usually thought of as active or conscious information behavior. Information-Searching Behavior describes the interactive elements between a user and an information system. Information-Use Behavior is about the user's acquisition and incorporation of data in some kind of information process. This leads to the production of information, but also back to the broad range of Information Behavior in the first part of the continuum. Though we plot all papers in this issue along this continuum, they take into account more than their general framework. The three information retrieval reports veer from the traditional information-searching approach of usersystem interaction, while the three industry environment articles veer from the traditional information-seeking approach of specific context information-seeking studies.
    Footnote
    Einführung zum Themenheft: Information seeking research
    Source
    Journal of the American Society for Information Science and Technology. 55(2004) no.9, S.767-768
  11. Cole, C.: ¬A theory of information need for information retrieval that connects information to knowledge (2011) 0.01
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    Abstract
    This article proposes a theory of information need for information retrieval (IR). Information need traditionally denotes the start state for someone seeking information, which includes information search using an IR system. There are two perspectives on information need. The dominant, computer science perspective is that the user needs to find an answer to a well-defined question which is easy for the user to formulate into a query to the system. Ironically, information science's best known model of information need (Taylor, 1968) deems it to be a "black box"-unknowable and nonspecifiable by the user in a query to the information system. Information science has instead devoted itself to studying eight adjacent or surrogate concepts (information seeking, search and use; problem, problematic situation and task; sense making and evolutionary adaptation/information foraging). Based on an analysis of these eight adjacent/surrogate concepts, we create six testable propositions for a theory of information need. The central assumption of the theory is that while computer science sees IR as an information- or answer-finding system, focused on the user finding an answer, an information science or user-oriented theory of information need envisages a knowledge formulation/acquisition system.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1216-1231
    Theme
    Information
  12. Spink, A.; Cole, C.: New directions in cognitive information retrieval : conclusion and further research (2005) 0.01
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    Abstract
    New Directions in Cognitive Information Retrieval (IR) gathers user or cognitive approaches to IR research into one volume. The group of researchers focus on a middleground perspective between system and user. They ask the question: What is the nexus between the wider context of why and how humans behave when seeking information and the technological and other constraints that determine the interaction between user and machine? These researchers' concern for the application of user/cognitive-oriented research to IR system design thus serves as a meeting ground linking computer scientists with their largely system performance concerns and the social science research that examines human information behavior in the wider context of how human perception and cognitive mechanisms function, and the work and social frameworks in which we live. The researchers in this volume provide an in-depth revaluation of the concepts that form the basis of current IR retrieval system design. Current IR systems are in a certain sense based on design conceptualizations that view - the user's role in the user-system interaction as an input and monitoring mechanism for system performance; - the system's role in the user-system interaction as a data acquisition system, not an information retrieval system; and - the central issue in the user-system interaction as the efficacy of the system's matching algorithms, matching the user request statement to representations of the document set contained in the system's database. But the era of matching-focused approaches to interactive IR appears to be giving way to a concern for developing interactive systems to facilitate collaboration between users in the performance of their work and social tasks. There is room for cognitive approaches to interaction to break in here.
    Series
    The information retrieval series, vol. 19
    Source
    New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole
  13. Cole, C.: Interaction with an enabling information retrieval system : modeling the user's decoding and encoding operations (2000) 0.01
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    Abstract
    With new interactive technology, we can increase user satisfaction by designing information retrieval systems that inform the user while the user is on-line interacting with the system. The purpose of this article is to model the information processing operations of a generic user who has just received an information message from the system and is stimulated by the message into grasping at a higher understanding of his or her information task or problem. The model consists of 3 levels, each of which forms a separate subsystem. In the Perseption subsystem, the user perceives the system message in a visual sense; in the Comprehension subsystem, the user must comprehend the system message; and in the Application subsystem, the user must (a) interpret the system message in terms of the user's task at hand, and (b) create and send a new message back to the system to complete the interaction. Because of the information process stimulated by the interaction, the user's new message forms a query to the system that more accurately represents the user's information need than would have been the case if the interaction had not taken place. This article proposes a device to enable clarification of the user's task, and thus his/her information need at the Application subsystem level of the model
    Source
    Journal of the American Society for Information Science. 51(2000) no.5, S.417-426
    Theme
    Information
  14. Cole, C.; Leide, J.E.; Large, A,; Beheshti, J.; Brooks, M.: Putting it together online : information need identification for the domain novice user (2005) 0.01
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    Abstract
    Domain novice users in the beginning stages of researching a topic find themselves searching for information via information retrieval (IR) systems before they have identified their information need. Pre-Internet access technologies adapted by current IR systems poorly serve these domain novice users, whose behavior might be characterized as rudderless and without a compass. In this article we describe a conceptual design for an information retrieval system that incorporates standard information need identification classification and subject cataloging schemes, called the INIIReye System, and a study that tests the efficacy of the innovative part of the INIIReye System, called the Associative Index. The Associative Index helps the user put together his or her associative thoughts-Vannevar Bush's idea of associative indexing for his Memex machine that he never actually described. For the first time, data from the study reported here quantitatively supports the theoretical notion that the information seeker's information need is identified through transformation of his/her knowledge structure (i.e., the seeker's cognitive map or perspective an the task far which information is being sought).
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.684-694
  15. Cole, C.; Mandelblatt, B.: Using Kintsch's discourse comprehension theory to model the user's coding of an informative message from an enabling information retrieval system (2000) 0.01
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    Abstract
    With new interactive technology, information science can use its traditional information focus to increase user satisfaction by designing information retrieval systems (IRSs) that inform the user about her task, and help the user get the task done, while the user is on-line interacting with the system. By doing so, the system enables the user to perform the task for which the information is being sought. In previous articles, we modeled the information flow and coding operations of a user who has just received an informative IRS message, dividing the user's processing of the IRS message into three subsystem levels. In this article, we use Kintsch's proposition-based construction-integration theory of discourse comprehension to further detail the user coding operations that occur in each of the three subsystems. Our enabling devices are designed to facilitate a specific coding operation in a specific subsystem. In this article, we describe an IRS device made up of two separate parts that enable the user's (1) decoding and (2) encoding of an IRS message in the Comprehension subsystem
    Source
    Journal of the American Society for Information Science. 51(2000) no.11, S.1033-1046
    Theme
    Information
  16. Cole, C.; Mandelblatt, B.; Stevenson, J.: Visualizing a high recall search strategy output for undergraduates in an exploration stage of researching a term paper (2002) 0.00
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    Abstract
    When accessing an information retrieval system, it has long been said that undergraduates who are in an exploratory stage of researching their essay topic should use a high recall search strategy; what prevents them from doing so is the information overload factor associated with showing the undergraduate a long list of citations. One method of overcoming information overload is summarizing and visualizing the citation list. This paper examines five summarization and visualization schemes for presenting information retrieval (IR) citation output, then discusses whether these schemes are appropriate for undergraduates and other domain novice users. We ask and answer four questions: (1) What is the message these schemes try to communicate and (2) is this message appropriate for domain novice users like undergraduates? (3) How do these schemes communicate their message and (4) is how they communicate the message appropriate for a domain novice? We conclude that (i) the most appropriate message for information space visualizations for domain novice users is associative thinking, and (ii) the message should be communicated with a standardized look that remains relatively constant over time so that the shape and form of the visualization can become familiar and thus useful to students as they navigate their way through the information space produced by a high recall search strategy.
    Source
    Information processing and management. 38(2002) no.1, S.37-54
  17. Leide, J.E.; Cole, C.; Beheshti, J.; Large, A.; Lin, Y.: Task-based information retrieval : structuring undergraduate history essays for better course evaluation using essay-type visualizations (2007) 0.00
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    Abstract
    When domain novices are in C.C. Kuhlthau's (1993) Stage 3, the exploration stage of researching an assignment, they often do not know their information need; this causes them to go back to Stage 2, the topic-selection stage, when they are selecting keywords to formulate their query to an Information Retrieval (IR) system. Our hypothesis is that instead of going backward, they should be going forward toward a goal state-the performance of the task for which they are seeking the information. If they can somehow construct their goal state into a query, this forward-looking query better operationalizes their information need than does a topic-based query. For domain novice undergraduates seeking information for a course essay, we define their task as selecting a high-impact essay structure which will put the students' learning on display for the course instructor who will evaluate the essay. We report a study of first-year history undergraduate students which tested the use and effectiveness of "essay type" as a task-focused query-formulation device. We randomly assigned 78 history undergraduates to an intervention group and a control group. The dependent variable was essay quality, based on (a) an evaluation of the student's essay by a research team member, and (b) the marks given to the student's essay by the course instructor. We found that conscious or formal consideration of essay type is inconclusive as a basis of a task-focused query-formulation device for IR.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1227-1241
  18. Cole, C.; Beheshti, J.; Leide, J. E.; Large, A.: Interactive information retrieval : bringing the user to a selection state (2005) 0.00
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    Abstract
    There have been various approaches to conceptualizing interactive information retrieval (IR), which can be generally divided into system and user approaches (Hearst, 1999; cf. also Spink, 1997). Both system and user approaches define user-system interaction in terms of the system and the user reacting to the actions or behaviors of the other: the system reacts to the user's input; the user to the output of the system (Spink, 1997). In system approach models of the interaction, e.g., Moran (1981), "[T]he user initiates an action or operation and the system responds in some way which in turn leads the user to initiate another action and so on" (Beaulieu, 2000, p. 433). In its purest form, the system approach models the user as a reactive part of the interaction, with the system taking the lead (Bates, 1990). User approaches, on the other hand, in their purest form wish to insert a model of the user in all its socio-cognitive dimensions, to the extent that system designers consider such approaches impractical (Vakkari and Jarvelin, 2005, Chap. 7, this volume). The cognitive approach to IR interaction attempts to overcome this divide (Ruthven, 2005, Chap. 4, this volume; Vakkari and Jarvelin, 2005 Chap. 7, this volume) by representing the cognitive elements of both system designers and the user in the interaction model (Larsen and Ingwersen, 2005 Chap. 3, this volume). There are cognitive approach researchers meeting in a central ground from both the system and user side. On the system side, are computer scientists employing cognitive research to design more effective IR systems from the point of view of the user's task (Nathan, 1990; Fischer, Henninger, and Redmiles, 1991; O'Day and Jeffries, 1993; Russell et al., 1993; Kitajima and Polson, 1996; Terwilliger and Polson, 1997). On the user side are cognitive approach researchers applying methods, concepts and models from psychology to design systems that are more in tune with how users acquire information (e.g., Belkin, 1980; Ford (2005, Chap. 5, this volume); Ingwersen (Larsen and Ingwersen, 2005, Chap. 3, this volume); Saracevic, 1996; Vakkari (Vakkari and Jarvelin, 2005, Chap. 7, this volume)).
    Series
    The information retrieval series, vol. 19
    Source
    New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole
  19. Cole, C.: ¬The consciousness' drive : information need and the search for meaning (2018) 0.00
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    Abstract
    What is the uniquely human factor in finding and using information to produce new knowledge? Is there an underlying aspect of our thinking that cannot be imitated by the AI-equipped machines that will increasingly dominate our lives? This book answers these questions, and tells us about our consciousness - its drive or intention in seeking information in the world around us, and how we are able to construct new knowledge from this information. The book is divided into three parts, each with an introduction and a conclusion that relate the theories and models presented to the real-world experience of someone using a search engine. First, Part I defines the exceptionality of human consciousness and its need for new information and how, uniquely among all other species, we frame our interactions with the world. Part II then investigates the problem of finding our real information need during information searches, and how our exceptional ability to frame our interactions with the world blocks us from finding the information we really need. Lastly, Part III details the solution to this framing problem and its operational implications for search engine design for everyone whose objective is the production of new knowledge. In this book, Charles Cole deliberately writes in a conversational style for a broader readership, keeping references to research material to the bare minimum. Replicating the structure of a detective novel, he builds his arguments towards a climax at the end of the book. For our video-game, video-on-demand times, he has visualized the ideas that form the book's thesis in over 90 original diagrams. And above all, he establishes a link between information need and knowledge production in evolutionary psychology, and thus bases his arguments in our origins as a species: how we humans naturally think, and how we naturally search for new information because our consciousness drives us to need it.
    Footnote
    Rez. in: JASIST 71(2020) no.1, S.118-120 (Heidi Julien). - Vgl. auch den Beitrag: Cole, C.: A rebuttal of the book review of the book titled "The Consciousness' Drive: Information Need and the Search for Meaning": mapping cognitive and document spaces. In: Journal of the Association for Information Science and Technology. 71(2020) no.2, S.242.
    Weitere Rez. unter: https://crl.acrl.org/index.php/crl/article/view/17830/19659: "Author Charles Cole's understanding of human consciousness is built foundationally upon the work of evolutionary psychologist Merlin Donald, who visualized the development of human cognition in four phases, with three transitions. According to Donald's Theory of Mind, preceding types of cognition do not cease to exist after human cognition transitions to a new phase, but exist as four layers within the modern consciousness. Cole's narrative in the first part of the book recounts Donald's model of human cognition, categorizing episodic, mimetic, mythic, and theoretic phases of cognition. The second half of the book sets up a particular situation of consciousness using the frame theory of Marvin Minsky, uses Meno's paradox (how can we come to know that which we don't already know?) in a critique of framing as Minsky conceived it, and presents group and national level framing and shows their inherent danger in allowing information avoidance and sanctioning immoral actions. Cole concludes with a solution of information need being sparked or triggered that takes the human consciousness out of a closed information loop, driving the consciousness to seek new information.
    Cole's reliance upon Donald's Theory of Mind is limiting; it represents a major weakness of the book. Donald's Theory of Mind has been an influential model in evolutionary psychology, appearing in his 1991 book Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition (Harvard University Press). Donald's approach is a top-down, conceptual model that explicates what makes the human mind different and exceptional from other animal intelligences. However, there are other alternative, useful, science-based models of animal and human cognition that begin with a bottom-up approach to understanding the building blocks of cognition shared in common by humans and other "intelligent" animals. For example, in "A Bottom-Up Approach to the Primate Mind," Frans B.M. de Waal and Pier Francesco Ferrari note that neurophysiological studies show that specific neuron assemblies in the rat hippocampus are active during memory retrieval and that those same assemblies predict future choices. This would suggest that episodic memory and future orientation aren't as advanced a process as Donald posits in his Theory of Mind. Also, neuroimaging studies in humans show that the cortical areas active during observations of another's actions are related in position and structure to those areas identified as containing mirror neurons in macaques. Could this point to a physiological basis for imitation? ... (Scott Curtis)"
    LCSH
    Information Storage and Retrieval
    Subject
    Information Storage and Retrieval
    Theme
    Information
  20. Cole, C.; Leide, J.E.: Using the user's mental model to guide the integration of information space into information need (2003) 0.00
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    Abstract
    The study reported here tested the efficacy of an information retrieval system output summary and visualization scheme for undergraduates taking a Vietnam War history who were in Kuhlthau's Stage 3 of researching a history essay. The visualization scheme consisted of (a) the undergraduate's own visualization of his or her essay topic, drawn by the student an the bottom half of a sheet of paper, and (b) a visualization of the information space (determined by index term counting) an the tophalf of the same page. To test the visualization scheme, students enrolled in a Vietnam War history course were randomly assigned to either the visualization scheme group, who received a high recall search output, or the nonvisualization group, who received a high precision search output. The dependent variable was the mark awarded the essay by the course instructor. There was no significant difference between the mean marks for the two groups. We were pleasantly surprised with this result given the bad reputation of high recall as a practical search strategy. We hypothesize that a more proactive visualization system is needed that takes the student through the process of using the visualization scheme, including steps that induce student cognition about task-subject objectives.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.1, S.39-46