This paper aims to report selective findings of a wider study on interaction of users with web‐based search tools to underline the importance of context in information seeking on the web and to introduce some of the contextual elements of web search context.
A series of intensive and in‐depth interviews was carried out with a sample of the Biology Community at the University of Sheffield. Critical Incident Technique (CIT) was employed in the interview protocol and the collected data was inductively analyzed in the light of Grounded Theory approach.
The results strongly suggest that considering the context of search is a pivotal factor in understanding users' behaviours, feelings, and thoughts during the period of information seeking in an online environment. Five categories have been identified as the main contextual elements which affect search performance of end users. These categories include web users' characteristics; type of the employed search tool; search topic; search situation; and features of the retrieved information resources. Each category has its subcategories which have been illustrated in the paper.
This study was carried out based on a relatively small sample of academia and therefore the results cannot be easily generalized to the wide community of web users. The results of this study should be able to make information literacy education more effective by using information seeking behaviour research discoveries. This study demonstrated that the outcome of any information literacy courses would be more efficient if the contextual factors – which have been identified and illuminated in this study – were considered in the educational agenda.
The study possesses three characteristics that make it different from other studies in the related areas. First of all, it took an in‐depth insight to the interaction of end users with the web in real situations. Secondly it focused on a specific targeted group, the academic biology community. Thirdly the study adopted a qualitative approach, in contrast with mainly quantitative web research.
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