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  • × author_ss:"Large, A."
  1. Leide, J.E.; Large, A.; Beheshti, J.; Brooks, M.; Cole, C.: Visualization schemes for domain novices exploring a topic space : the navigation classification scheme (2003) 0.03 
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    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.
    Source
    Information processing and management. 39(2003) no.6, S.923-940
  2. Large, A.; Beheshti, J.; Breuleux, A.: ¬A comparison of information retrieval from print and CD-ROM versions of an encyclopedia by elementary school students (1994) 0.02 
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    Source
    Information processing and management. 30(1994) no.4, S.499-513
  3. Cole, C.; Beheshti, J.; Leide, J. E.; Large, A.: Interactive information retrieval : bringing the user to a selection state (2005) 0.01 
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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)).
  4. Large, A.; Beheshti, J.; Rahman, T.: Gender differences in collaborative Web searching behavior : an elementary school study (2002) 0.01 
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    Source
    Information processing and management. 38(2002) no.3, S.427-443
  5. Large, A.; Beheshti, J.; Rahman, T.: Design criteria for children's Web portals : the users speak out (2002) 0.01 
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    Date
    2. 6.2005 10:34:22
  6. Cole, C.; Behesthi, J.; Large, A.; Lamoureux, I.; Abuhimed, D.; AlGhamdi, M.: Seeking information for a middle school history project : the concept of implicit knowledge in the students' transition from Kuhlthau's Stage 3 to Stage 4 (2013) 0.01 
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    Date
    22. 3.2013 19:41:17
  7. 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.
  8. Beheshti, J.; Bowler, L.; Large, A.; Nesset, V.: Towards an alternative information retrieval system for children (2005) 0.00 
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  9. Cole, C.; Lin, Y.; Leide, J.; Large, A.; Beheshti, J.: ¬A classification of mental models of undergraduates seeking information for a course essay in history and psychology : preliminary investigations into aligning their mental models with online thesauri (2007) 0.00 
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    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.

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