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The effects of domain knowledge on search tactic formulation

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  • Barbara M. Wildemuth

Abstract

A search tactic is a set of search moves that are temporally and semantically related. The current study examined the tactics of medical students searching a factual database in microbiology. The students answered problems and searched the database on three occasions over a 9‐month period. Their search moves were analyzed in terms of the changes in search terms used from one cycle to the next, using two different analysis methods. Common patterns were found in the students' search tactics; the most common approach was the specification of a concept, followed by the addition of one or more concepts, gradually narrowing the retrieved set before it was displayed. It was also found that the search tactics changed over time as the students' domain knowledge changed. These results have important implications for designers in developing systems that will support users' preferred ways of formulating searches. In addition, the research methods used (the coding scheme and the two data analysis methods—zero‐order state transition matrices and maximal repeating patterns [MRP] analysis) are discussed in terms of their validity in future studies of search tactics.

Suggested Citation

  • Barbara M. Wildemuth, 2004. "The effects of domain knowledge on search tactic formulation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 55(3), pages 246-258, February.
    • Handle: RePEc:bla:jamist:v:55:y:2004:i:3:p:246-258
    DOI: 10.1002/asi.10367
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    Cited by:

    1. Iris Xie & Soohyung Joo, 2010. "Tales from the Field: Search Strategies Applied in Web Searching," Future Internet, MDPI, vol. 2(3), pages 1-23, August.
    2. Ling-Ling Wu & Mu-Hsuan Huang & Ching-Yi Chen, 2012. "Citation patterns of the pre-web and web-prevalent environments: The moderating effects of domain knowledge," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2182-2194, November.
    3. Yong‐Mi Kim, 2010. "The adoption of university library Web site resources: A multigroup analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(5), pages 978-993, May.
    4. Lynda Tamine & Cécile Chouquet & Thomas Palmer, 2015. "Analysis of biomedical and health queries: Lessons learned from TREC," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2626-2642, December.
    5. Sanna Kumpulainen & Elina Late, 2022. "Struggling with digitized historical newspapers: Contextual barriers to information interaction in history research activities," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(7), pages 1012-1024, July.
    6. K A Dowsland & M Gilbert & G Kendall, 2007. "A local search approach to a circle cutting problem arising in the motor cycle industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(4), pages 429-438, April.

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