The effects of expertise and feedback on search term selection and subsequent learning: Research Articles

Authors:
Helene A. Hembrooke;Laura A. Granka;Geraldine K. Gay;Elizabeth D. Liddy
Affiliations:
Human Computer Interaction Laboratory, Information Science Building, Cornell University, 301 College Avenue, Ithaca, NY 14853;Human Computer Interaction Laboratory, Information Science Building, Cornell University, 301 College Avenue, Ithaca, NY 14853;Human Computer Interaction Laboratory, Information Science Building, Cornell University, 301 College Avenue, Ithaca, NY 14853;Center for Natural Language Processing, School of Information Studies, Syracuse University, Syracuse, NY.
Venue:
Journal of the American Society for Information Science and Technology
Year:
2005

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Abstract

Query formation and expansion is an integral part of nearly every effort to search for information. In the work reported here we investigate the effects of domain knowledge and feedback on search term selection and reformation. We explore differences between experts and novices as they generate search terms over 10 successive trials and under two feedback conditions. Search attempts were coded on quantitative dimensions such as the number of unique terms and average time per trial, and as a whole in an attempt to characterize the user's conceptual map for the topic under differing conditions of participant-defined domain expertise. Nine distinct strategies were identified. Differences emerged as a function of both expertise and feedback. In addition, strategic behavior varied depending on prior search conditions. The results are considered from both a theoretical and design perspective, and have direct implications for digital library usability and metadata generation, and query expansion systems. © 2005 Wiley Periodicals, Inc.