Indicative Title

Men may be more effective internet searchers than women.

Abstract

Abstracted from: Ford, N., Miller, D. and Moss, N. (2001) The Role of Individual Differences in Internet Searching: an empirical study, Journal of the American Society for Information Science and Technology, 52 (12), 1049–66.

Objective

This exploratory study aimed to investigate the role of ‘individual differences’ in internet searching. In particular, the authors wanted to determine whether there was any statistically based evidence that retrieval effectiveness is affected by:

(a) psychological differences between individuals, consisting of:

(b) demographic differences (age and gender).

Setting

Department of Information Studies, University of Sheffield, England.

Participants

Volunteers drawn from two cohorts (1999 and 2000 entry) of three taught Masters programmes (MA Librarianship, MSc Information Management and MSc Information Systems). The two cohorts consisted of 250 students.

Method

Students were asked to search for information on a prescribed topic using the AltaVista search engine via the Netscape Navigator browser. The following scenario was used:

A technician cuts his finger badly in the Information Studies departmental office. What are the legal implications of this for the university? Find relevant information on the web.

Searchers were free to choose the simple search option, which provides best match (or keyword) searching, and/or the advanced search option. A JavaScript front-end recorded all search data submitted to the search engine, and this was automatically sent to the researchers. There was no time limit or restriction on the number of queries students could submit.

Outcome measures

A 63-item self-completed ‘individual differences’ questionnaire, based on several different scales (e.g. Tait and Entwistle, 1995; Ford and Miller, 1996). Riding's (1991) psychometric measure, Cognitive Styles Analysis.

Details of age and gender were obtained via a form on the opening screen of the web-based search interface.

Data analysis

The first two screens of retrieved items resulting from each successive query were categorized using a dichotomous ‘relevant/not relevant’ classification. A single relevance estimate was calculated in relation to each participant's search across all queries. Multiple regression and factor analysis were applied to the data.