Search (20 results, page 1 of 1)

0.024858989 = product of:
  0.049717978 = sum of:
    0.010194084 = product of:
      0.040776335 = sum of:
        0.040776335 = weight(_text_:based in 2265) [ClassicSimilarity], result of:
          0.040776335 = score(doc=2265,freq=6.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.28829288 = fieldWeight in 2265, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2265)
      0.25 = coord(1/4)
    0.039523892 = product of:
      0.079047784 = sum of:
        0.079047784 = weight(_text_:assessment in 2265) [ClassicSimilarity], result of:
          0.079047784 = score(doc=2265,freq=2.0), product of:
            0.25917634 = queryWeight, product of:
              5.52102 = idf(docFreq=480, maxDocs=44218)
              0.04694356 = queryNorm
            0.30499613 = fieldWeight in 2265, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.52102 = idf(docFreq=480, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2265)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

This article reports on a field study of the information behavior of Grade 8 students researching an inquiry-based class history project. Kuhlthau's 7-stage Information Search Process (ISP) model forms the conceptual framework for the study. The aim of the study was to define an end game for the ISP model by answering the following question: How do the student participants' feelings, thoughts, and information behavior lead to the construction of new knowledge? Study findings tentatively indicate that knowledge construction results from an iterative process between the student and information, which can be divided into 3 phases. In the first phase, the students formulate questions from their previous knowledge to start knowledge construction; in the second phase, newly found topic information causes students to ask questions; and in the third phase, the students answer the questions asked by this newly found topic information. Based on these results and Kuhlthau's own ISP stage 7 assessment definition of the ISP model end game, we propose a model of knowledge construction inserted as an extra row in the ISP model framework.

0.014115169 = product of:
  0.056460675 = sum of:
    0.056460675 = weight(_text_:term in 1237) [ClassicSimilarity], result of:
      0.056460675 = score(doc=1237,freq=2.0), product of:
        0.21904005 = queryWeight, product of:
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.04694356 = queryNorm
        0.25776416 = fieldWeight in 1237, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1237)
  0.25 = coord(1/4)

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.

0.014115169 = product of:
  0.056460675 = sum of:
    0.056460675 = weight(_text_:term in 2575) [ClassicSimilarity], result of:
      0.056460675 = score(doc=2575,freq=2.0), product of:
        0.21904005 = queryWeight, product of:
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.04694356 = queryNorm
        0.25776416 = fieldWeight in 2575, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2575)
  0.25 = coord(1/4)

0.011292135 = product of:
  0.04516854 = sum of:
    0.04516854 = weight(_text_:term in 2389) [ClassicSimilarity], result of:
      0.04516854 = score(doc=2389,freq=2.0), product of:
        0.21904005 = queryWeight, product of:
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.04694356 = queryNorm
        0.20621133 = fieldWeight in 2389, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.66603 = idf(docFreq=1130, maxDocs=44218)
          0.03125 = fieldNorm(doc=2389)
  0.25 = coord(1/4)

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.

0.0047701527 = product of:
  0.019080611 = sum of:
    0.019080611 = product of:
      0.038161222 = sum of:
        0.038161222 = weight(_text_:22 in 3675) [ClassicSimilarity], result of:
          0.038161222 = score(doc=3675,freq=2.0), product of:
            0.16438834 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04694356 = queryNorm
            0.23214069 = fieldWeight in 3675, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3675)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

22. 5.1999 14:51:49

0.003975128 = product of:
  0.015900511 = sum of:
    0.015900511 = product of:
      0.031801023 = sum of:
        0.031801023 = weight(_text_:22 in 667) [ClassicSimilarity], result of:
          0.031801023 = score(doc=667,freq=2.0), product of:
            0.16438834 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04694356 = queryNorm
            0.19345059 = fieldWeight in 667, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=667)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

22. 3.2013 19:41:17

0.003180102 = product of:
  0.012720408 = sum of:
    0.012720408 = product of:
      0.025440816 = sum of:
        0.025440816 = weight(_text_:22 in 642) [ClassicSimilarity], result of:
          0.025440816 = score(doc=642,freq=2.0), product of:
            0.16438834 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04694356 = queryNorm
            0.15476047 = fieldWeight in 642, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=642)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

19. 1.2007 12:55:22

0.0029427784 = product of:
  0.011771114 = sum of:
    0.011771114 = product of:
      0.047084454 = sum of:
        0.047084454 = weight(_text_:based in 4814) [ClassicSimilarity], result of:
          0.047084454 = score(doc=4814,freq=8.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.33289194 = fieldWeight in 4814, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4814)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

The authors present a study of the real-life information needs of 59 McGill University undergraduates researching essay topics for either a history or psychology course, interviewed just after they had selected their essay topic. The interview's purpose was to transform the undergraduate's query from general topic terms, based an vague conceptions of their essay topic, to an information need-based query. To chart the transformation, the authors investigate N. J. Belkin, R. N. Oddy, and H. M. Brooks' Anomalous States of Knowledge (ASK) hypothesis (1982a, 1982b), which links the user's ASK to a relevant document set via a common code based an structural facets. In the present study an interoperable structural code based an eight essay styles is created, then notions of structural facets compatible with a highimpact essay structure are presented. The important findings of the study are: (a) the undergraduates' topic statements and terms derived from it do not constitute an effective information need statement because for most of the subjects in the study the topic terms conformed to a low-impact essay style; (b) essay style is an effective interoperable structural code for charting the evolution of the undergraduate's knowledge state from ASK to partial resolution of the ASK in an information need statement.

0.002548521 = product of:
  0.010194084 = sum of:
    0.010194084 = product of:
      0.040776335 = sum of:
        0.040776335 = weight(_text_:based in 460) [ClassicSimilarity], result of:
          0.040776335 = score(doc=460,freq=6.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.28829288 = fieldWeight in 460, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=460)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

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.

0.0020808585 = product of:
  0.008323434 = sum of:
    0.008323434 = product of:
      0.033293735 = sum of:
        0.033293735 = weight(_text_:based in 1078) [ClassicSimilarity], result of:
          0.033293735 = score(doc=1078,freq=4.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.23539014 = fieldWeight in 1078, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1078)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

In this article and two other articles which conceptualize a future stage of the research program (Leide, Cole, Large, & Beheshti, submitted for publication; Cole, Leide, Large, Beheshti, & Brooks, in preparation), we map-out a domain novice user's encounter with an IR system from beginning to end so that appropriate classification-based visualization schemes can be inserted into the encounter process. This article describes the visualization of a navigation classification scheme only. The navigation classification scheme uses the metaphor of a ship and ship's navigator traveling through charted (but unknown to the user) waters, guided by a series of lighthouses. The lighthouses contain mediation interfaces linking the user to the information store through agents created for each. The user's agent is the cognitive model the user has of the information space, which the system encourages to evolve via interaction with the system's agent. The system's agent is an evolving classification scheme created by professional indexers to represent the structure of the information store. We propose a more systematic, multidimensional approach to creating evolving classification/indexing schemes, based on where the user is and what she is trying to do at that moment during the search session.

0.0020808585 = product of:
  0.008323434 = sum of:
    0.008323434 = product of:
      0.033293735 = sum of:
        0.033293735 = weight(_text_:based in 1819) [ClassicSimilarity], result of:
          0.033293735 = score(doc=1819,freq=4.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.23539014 = fieldWeight in 1819, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1819)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

The article reports a field study investigating the temporality of the information behavior of 44 grade 8 students from initiation to completion of their school inquiry-based history project. The conceptual framework for the study is Kuhlthau's 6-stage information-search process (ISP) model. The objective of the study is to test and extend ISP model concepts. As per other ISP model studies, our study measured the evolution of the feelings, thoughts, and actions of the study participants over the 3-month period of their class project. The unique feature of this study is the unlimited access the researchers had to a real-life history class, resulting in 12 separate measuring periods. We report 2 important findings of the study. First, through factor analysis, we determined 5 factors that define the temporality of completing an inquiry-based project for these grade 8 students. The second main finding is the importance of the students' consultations with their classmates, siblings, parents, and teachers in the construction of the knowledge necessary to complete their project.

0.002059945 = product of:
  0.00823978 = sum of:
    0.00823978 = product of:
      0.03295912 = sum of:
        0.03295912 = weight(_text_:based in 627) [ClassicSimilarity], result of:
          0.03295912 = score(doc=627,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.23302436 = fieldWeight in 627, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0546875 = fieldNorm(doc=627)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

When assisting undergraduate students in accessing materials, academic librarians must balance the task of conducting reference interviews with instructing students on how to use databases (OPACs, CD-ROM and online databases). Presents a method for connecting these tasks via the construction of a search strategy which is wholly dependent on the user's information needs. Using this method, the librarian assesses and explicitly labels the student's information need (using a diagnostoc tool based on Kuhlthau's and Taylor's concept of 'focus'), then assigns the most appropriate online search strategy for the satisfaction of this need

0.002059945 = product of:
  0.00823978 = sum of:
    0.00823978 = product of:
      0.03295912 = sum of:
        0.03295912 = weight(_text_:based in 837) [ClassicSimilarity], result of:
          0.03295912 = score(doc=837,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.23302436 = fieldWeight in 837, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0546875 = fieldNorm(doc=837)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

This paper outlines the relation between philosophy of information (PI) and human information behavior (HIB). In this paper, we first briefly outline the basic constructs and approaches of PI and HIB. We argue that a strong relation exists between PI and HIB, as both are exploring the concept of information and premise information as a fundamental concept basic to human existence. We then exemplify that a heuristic approach to PI integrates the HIB view of information as a cognitive human-initiated process by presenting a specific cognitive architecture for information initiation based on modular notion from HIB/evolutionary psychology and the vacuum mechanism from PI.

0.0017656671 = product of:
  0.0070626684 = sum of:
    0.0070626684 = product of:
      0.028250674 = sum of:
        0.028250674 = weight(_text_:based in 2125) [ClassicSimilarity], result of:
          0.028250674 = score(doc=2125,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.19973516 = fieldWeight in 2125, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.046875 = fieldNorm(doc=2125)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

The article analyzes user-IR system interaction from the broad, socio-cognitive perspective of lessons we can learn about human brain evolution when we compare the Neanderthal brain to the human brain before and after a small human brain mutation is hypothesized to have occurred 35,000-75,000 years ago. The enhanced working memory mutation enabled modern humans (i) to decode unfamiliar environmental stimuli with greater focusing power on adaptive solutions to environmental changes and problems, and (ii) to encode environmental stimuli in more efficient, generative knowledge structures. A sociological theory of these evolving, more efficient encoding knowledge structures is given. These new knowledge structures instilled in humans not only the ability to adapt to and survive novelty and/or changing conditions in the environment, but they also instilled an imperative to do so. Present day IR systems ignore the encoding imperative in their design framework. To correct for this lacuna, we propose the evolutionary-based socio-cognitive framework model for designing interactive IR systems. A case study is given to illustrate the functioning of the model.

0.0014713892 = product of:
  0.005885557 = sum of:
    0.005885557 = product of:
      0.023542227 = sum of:
        0.023542227 = weight(_text_:based in 5161) [ClassicSimilarity], result of:
          0.023542227 = score(doc=5161,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.16644597 = fieldWeight in 5161, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5161)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

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

0.0014713892 = product of:
  0.005885557 = sum of:
    0.005885557 = product of:
      0.023542227 = sum of:
        0.023542227 = weight(_text_:based in 4915) [ClassicSimilarity], result of:
          0.023542227 = score(doc=4915,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.16644597 = fieldWeight in 4915, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4915)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

For millennia humans have sought, organized, and used information as they learned and evolved patterns of human information behaviors to resolve their human problems and survive. However, despite the current focus an living in an "information age," we have a limited evolutionary understanding of human information behavior. In this article the authors examine the current three interdisciplinary approaches to conceptualizing how humans have sought information including (a) the everyday life information seeking-sense-making approach, (b) the information foraging approach, and (c) the problem-solution perspective an information seeking approach. In addition, due to the lack of clarity regarding the rote of information use in information behavior, a fourth information approach is provided based an a theory of information use. The use theory proposed starts from an evolutionary psychology notion that humans are able to adapt to their environment and survive because of our modular cognitive architecture. Finally, the authors begin the process of conceptualizing these diverse approaches, and the various aspects or elements of these approaches, within an integrated model with consideration of information use. An initial integrated model of these different approaches with information use is proposed.

0.0014713892 = product of:
  0.005885557 = sum of:
    0.005885557 = product of:
      0.023542227 = sum of:
        0.023542227 = weight(_text_:based in 4474) [ClassicSimilarity], result of:
          0.023542227 = score(doc=4474,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.16644597 = fieldWeight in 4474, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4474)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

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.

0.0011771114 = product of:
  0.0047084456 = sum of:
    0.0047084456 = product of:
      0.018833783 = sum of:
        0.018833783 = weight(_text_:based in 637) [ClassicSimilarity], result of:
          0.018833783 = score(doc=637,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.13315678 = fieldWeight in 637, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.03125 = fieldNorm(doc=637)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

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.

0.0011771114 = product of:
  0.0047084456 = sum of:
    0.0047084456 = product of:
      0.018833783 = sum of:
        0.018833783 = weight(_text_:based in 625) [ClassicSimilarity], result of:
          0.018833783 = score(doc=625,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.13315678 = fieldWeight in 625, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.03125 = fieldNorm(doc=625)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Abstract

The article reports a field study which examined the mental models of 80 undergraduates seeking information for either a history or psychology course essay when they were in an early, exploration stage of researching their essay. This group is presently at a disadvantage when using thesaurus-type schemes in indexes and online search engines because there is a disconnect between how domain novice users of IR systems represent a topic space and how this space is represented in the standard IR system thesaurus. The study attempted to (a) ascertain the coding language used by the 80 undergraduates in the study to mentally represent their topic and then (b) align the mental models with the hierarchical structure found in many thesauri. The intervention focused the undergraduates' thinking about their topic from a topic statement to a thesis statement. The undergraduates were asked to produce three mental model diagrams for their real-life course essay at the beginning, middle, and end of the interview, for a total of 240 mental model diagrams, from which we created a 12-category mental model classification scheme. Findings indicate that at the end of the intervention, (a) the percentage of vertical mental models increased from 24 to 35% of all mental models; but that (b) 3rd-year students had fewer vertical mental models than did 1st-year undergraduates in the study, which is counterintuitive. The results indicate that there is justification for pursuing our research based on the hypothesis that rotating a domain novice's mental model into a vertical position would make it easier for him or her to cognitively connect with the thesaurus's hierarchical representation of the topic area.

8.8283356E-4 = product of:
  0.0035313342 = sum of:
    0.0035313342 = product of:
      0.014125337 = sum of:
        0.014125337 = weight(_text_:based in 480) [ClassicSimilarity], result of:
          0.014125337 = score(doc=480,freq=2.0), product of:
            0.14144066 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.04694356 = queryNorm
            0.09986758 = fieldWeight in 480, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.0234375 = fieldNorm(doc=480)
      0.25 = coord(1/4)
  0.25 = coord(1/4)

Footnote

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)"