Open AccessUsers' conceptual structure, search process and useful information types in the retrieved references
Author(s) -
Vakkari Pertti,
Serola Sami,
Pennanen Mikko
Publication year - 2005
Publication title -
proceedings of the american society for information science and technology
Language(s) - English
Resource type - Journals
eISSN - 1550-8390
pISSN - 0044-7870
DOI - 10.1002/meet.1450420152
Subject(s) - psycinfo , task (project management) , information retrieval , computer science , relevance (law) , field (mathematics) , process (computing) , information needs , cognitive models of information retrieval , outcome (game theory) , psychology , data science , search engine , world wide web , human–computer information retrieval , medline , engineering , mathematics , systems engineering , political science , pure mathematics , law , operating system , mathematical economics
This study focuses on the relationship between students' conceptual understanding of their information need, search process and search outcome in terms of useful information types in the references retrieved for their task. The research subjects were 22 undergraduates of psychology preparing a research proposal. They were asked to make searches in the PsycINFO database in the beginning of their proposal preparation. A pre‐ and post‐search interview was conducted and the search logs were recorded. The students assessed the utility of the references retrieved in terms of given information types useful for their task, i.e. using multidimensional relevance assessments. Students' conceptual structure was both directly and indirectly connected to the number of retrieved references via search tactics, providing certain types of information for the task. Different search tactics led to the retrieving of references containing different types of information. It was observed that certain field codes of PsycINFO fitted in part with the useful information types. Signalling more clearly those field codes related to these dimensions of topicality, could help users in articulating their information needs and consequently in improving search results.