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Search effort degrades search output but improves task outcome

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  • Pertti Vakkari
  • Saila Huuskonen

Abstract

We analyzed how effort in searching is associated with search output and task outcome. In a field study, we examined how students' search effort for an assigned learning task was associated with precision and relative recall, and how this was associated to the quality of learning outcome. The study subjects were 41 medical students writing essays for a class in medicine. Searching in Medline was part of their assignment. The data comprised students' search logs in Medline, their assessment of the usefulness of references retrieved, a questionnaire concerning the search process, and evaluation scores of the essays given by the teachers. Pearson correlation was calculated for answering the research questions. Finally, a path model for predicting task outcome was built. We found that effort in the search process degraded precision but improved task outcome. There were two major mechanisms reducing precision while enhancing task outcome. Effort in expanding Medical Subject Heading (MeSH) terms within search sessions and effort in assessing and exploring documents in the result list between the sessions degraded precision, but led to better task outcome. Thus, human effort compensated bad retrieval results on the way to good task outcome. Findings suggest that traditional effectiveness measures in information retrieval should be complemented with evaluation measures for search process and outcome.

Suggested Citation

  • Pertti Vakkari & Saila Huuskonen, 2012. "Search effort degrades search output but improves task outcome," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(4), pages 657-670, April.
  • Handle: RePEc:bla:jamist:v:63:y:2012:i:4:p:657-670
    DOI: 10.1002/asi.21683
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    Cited by:

    1. Tuukka Ruotsalo & Giulio Jacucci & Samuel Kaski, 2020. "Interactive faceted query suggestion for exploratory search: Whole‐session effectiveness and interaction engagement," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(7), pages 742-756, July.
    2. Pertti Vakkari & Michael Völske & Martin Potthast & Matthias Hagen & Benno Stein, 2021. "Predicting essay quality from search and writing behavior," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(7), pages 839-852, July.

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