Search (25 results, page 2 of 2)

  • × author_ss:"Spink, A."
  • × theme_ss:"Benutzerstudien"
  1. Wilson, T.D.; Ford, N.; Ellis, D.; Foster, A.; Spink, A.: Information seeking and mediated searching : Part 2: uncertainty and Its correlates (2002) 0.00
    0.001577849 = product of:
      0.014200641 = sum of:
        0.014200641 = weight(_text_:of in 5232) [ClassicSimilarity], result of:
          0.014200641 = score(doc=5232,freq=10.0), product of:
            0.061262865 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03917671 = queryNorm
            0.23179851 = fieldWeight in 5232, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=5232)
      0.11111111 = coord(1/9)
    
    Abstract
    In "Part 2. Uncertainty and Its Correlates,'' where Wilson is the primary author, after a review of uncertainty as a concept in information seeking and decision research, it is hypothesized that if the Kuhlthau problem solving stage model is appropriate the searchers will recognize the stage in which they currently are operating. Secondly to test Wilson's contention that operationalized uncertainty would be useful in characterizing users, it is hypothesized that uncertainty will decrease as the searcher proceeds through problem stages and after the completion of the search. A review of pre and post search interviews reveals that uncertainty can be operationalized, and that academic researchers have no difficulty with a stage model of the information seeking process. Uncertainty is unrelated to sex, age, or discipline, but is related to problem stage and domain knowledge. Both concepts appear robust.
    Source
    Journal of the American Society for Information Science and Technology. 53(2002) no.9, S.704-715
  2. Spink, A.; Wilson, T.D.; Ford, N.; Foster, A.; Ellis, D.: Information seeking and mediated searching : Part 3: successive searching (2002) 0.00
    0.0015557801 = product of:
      0.0140020205 = sum of:
        0.0140020205 = weight(_text_:of in 5242) [ClassicSimilarity], result of:
          0.0140020205 = score(doc=5242,freq=14.0), product of:
            0.061262865 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03917671 = queryNorm
            0.22855641 = fieldWeight in 5242, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5242)
      0.11111111 = coord(1/9)
    
    Abstract
    In "Part 3. Successive Searching.'' where Spink is the primary author, after a review of the work on successive searching, a portion of the Texas generated data is reviewed for insights on how frequently successive searching occurred, the motivation for its occurrence, and any distinctive characteristics of the successive search pattern. Of 18 mediated searches, half requested a second search and a quarter a third search. All but one seeker reported a need to refine and enhance the previous results. Second searches while characterized as refinements included a significantly higher number of items retrieved and more search cycles. Third searches had the most cycles but less retrieved items than the second. Number of terms utilized did not change significantly and overlap was limited to about one in five terms between first and second searches. No overlap occurred between the second and third searches. Problem solving stage shifts did occur with 2 moving to a later stage after the first search, 5 remaining in the same stage and one reverting to a previous stage. Precision did not increase over successive searches, but partial relevant judgments decreased between the second and third search.
    Source
    Journal of the American Society for Information Science and Technology. 53(2002) no.9, S.716-727
  3. Spink, A.; Danby, S.; Mallan, K.; Butler, C.: Exploring young children's web searching and technoliteracy (2010) 0.00
    0.0015557801 = product of:
      0.0140020205 = sum of:
        0.0140020205 = weight(_text_:of in 3623) [ClassicSimilarity], result of:
          0.0140020205 = score(doc=3623,freq=14.0), product of:
            0.061262865 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03917671 = queryNorm
            0.22855641 = fieldWeight in 3623, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3623)
      0.11111111 = coord(1/9)
    
    Abstract
    Purpose - This paper aims to report findings from an exploratory study investigating the web interactions and technoliteracy of children in the early childhood years. Previous research has studied aspects of older children's technoliteracy and web searching; however, few studies have analyzed web search data from children younger than six years of age. Design/methodology/approach - The study explored the Google web searching and technoliteracy of young children who are enrolled in a "preparatory classroom" or kindergarten (the year before young children begin compulsory schooling in Queensland, Australia). Young children were video- and audio-taped while conducting Google web searches in the classroom. The data were qualitatively analysed to understand the young children's web search behaviour. Findings - The findings show that young children engage in complex web searches, including keyword searching and browsing, query formulation and reformulation, relevance judgments, successive searches, information multitasking and collaborative behaviours. The study results provide significant initial insights into young children's web searching and technoliteracy. Practical implications - The use of web search engines by young children is an important research area with implications for educators and web technologies developers. Originality/value - This is the first study of young children's interaction with a web search engine.
    Source
    Journal of documentation. 66(2010) no.2, S.191-206
  4. Spink, A.; Du, J.T.: Toward a Web search model : integrating multitasking, cognitive coordination, and cognitive shifts (2011) 0.00
    0.0015557801 = product of:
      0.0140020205 = sum of:
        0.0140020205 = weight(_text_:of in 4624) [ClassicSimilarity], result of:
          0.0140020205 = score(doc=4624,freq=14.0), product of:
            0.061262865 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03917671 = queryNorm
            0.22855641 = fieldWeight in 4624, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4624)
      0.11111111 = coord(1/9)
    
    Abstract
    Limited research has investigated the role of multitasking, cognitive coordination, and cognitive shifts during web search. Understanding these three behaviors is crucial to web search model development. This study aims to explore characteristics of multitasking behavior, types of cognitive shifts, and levels of cognitive coordination as well as the relationship between them during web search. Data collection included pre- and postquestionnaires, think-aloud protocols, web search logs, observations, and interviews with 42 graduate students who conducted 315 web search sessions with 221 information problems. Results show that web search is a dynamic interaction including the ordering of multiple information problems and the generation of evolving information problems, including task switching, multitasking, explicit task and implicit mental coordination, and cognitive shifting. Findings show that explicit task-level coordination is closely linked to multitasking, and implicit cognitive-level coordination is related to the task-coordination process; including information problem development and task switching. Coordination mechanisms directly result in cognitive state shifts including strategy, evaluation, and view states that affect users' holistic shifts in information problem understanding and knowledge contribution. A web search model integrating multitasking, cognitive coordination, and cognitive shifts (MCC model) is presented. Implications and further research also are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1446-1472
  5. Jansen, B.J.; Spink, A.; Saracevic, T.: Real life, real users and real needs : a study and analysis of users queries on the Web (2000) 0.00
    0.0014112709 = product of:
      0.012701439 = sum of:
        0.012701439 = weight(_text_:of in 411) [ClassicSimilarity], result of:
          0.012701439 = score(doc=411,freq=2.0), product of:
            0.061262865 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03917671 = queryNorm
            0.20732689 = fieldWeight in 411, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.09375 = fieldNorm(doc=411)
      0.11111111 = coord(1/9)