Search (30 results, page 2 of 2)

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Abstract

Purpose - This paper aims to report findings from an exploratory study investigating the web interactions and technoliteracy of children in the early childhood years. Previous research has studied aspects of older children's technoliteracy and web searching; however, few studies have analyzed web search data from children younger than six years of age. Design/methodology/approach - The study explored the Google web searching and technoliteracy of young children who are enrolled in a "preparatory classroom" or kindergarten (the year before young children begin compulsory schooling in Queensland, Australia). Young children were video- and audio-taped while conducting Google web searches in the classroom. The data were qualitatively analysed to understand the young children's web search behaviour. Findings - The findings show that young children engage in complex web searches, including keyword searching and browsing, query formulation and reformulation, relevance judgments, successive searches, information multitasking and collaborative behaviours. The study results provide significant initial insights into young children's web searching and technoliteracy. Practical implications - The use of web search engines by young children is an important research area with implications for educators and web technologies developers. Originality/value - This is the first study of young children's interaction with a web search engine.

Type

a

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Abstract

This book provides practical strategies which enable the advanced web user to locate information effectively and to form a precise evaluation of the accuracy of that information. Although the book provides a brief but thorough review of the technologies which are currently available for these purposes, most of the book concerns practical `future-proof' techniques which are independent of changes in the tools available. For example, the book covers: how to retrieve salient information quickly; how to remove or compensate for bias; and tuition of novice Internet users.

Content

Key Features - Importantly, the book enables readers to develop strategies which will continue to be useful despite the rapidly-evolving state of the Internet and Internet technologies - it is not about technological `tricks'. - Enables readers to be aware of and compensate for bias and errors which are ubiquitous an the Internet. - Provides contemporary information an the deficiencies in web skills of novice users as well as practical techniques for teaching such users. The Authors Dr Alison Stacey works at the Learning Resource Centre, Cambridge Regional College. Dr Adrian Stacey, formerly based at Cambridge University, is a software programmer. Readership The book is aimed at a wide range of librarians and other information professionals who need to retrieve information from the Internet efficiently, to evaluate their confidence in the information they retrieve and/or to train others to use the Internet. It is primarily aimed at intermediate to advanced users of the Internet. Contents Fundamentals of information retrieval from the Internet - why learn web searching technique; types of information requests; patterns for information retrieval; leveraging the technology: Search term choice: pinpointing information an the web - why choose queries carefully; making search terms work together; how to pick search terms; finding the 'unfindable': Blas an the Internet - importance of bias; sources of bias; usergenerated bias: selecting information with which you already agree; assessing and compensating for bias; case studies: Query reformulation and longer term strategies - how to interact with your search engine; foraging for information; long term information retrieval: using the Internet to find trends; automating searches: how to make your machine do your work: Assessing the quality of results- how to assess and ensure quality: The novice user and teaching internet skills - novice users and their problems with the web; case study: research in a college library; interpreting 'second hand' web information.

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Abstract

Previous studies have examined various aspects of user behavior on the Web, including general information-seeking patterns, search engine use, and revisitation habits. Little research has been conducted to study how users navigate and interact with their Web browser across different information-seeking tasks. We have conducted a field study of 21 participants, in which we logged detailed Web usage and asked participants to provide task categorizations of their Web usage based on the following categories: Fact Finding, Information Gathering, Browsing, and Transactions. We used implicit measures logged during each task session to provide usage measures such as dwell time, number of pages viewed, and the use of specific browser navigation mechanisms. We also report on differences in how participants interacted with their Web browser across the range of information-seeking tasks. Within each type of task, we found several distinguishing characteristics. In particular, Information Gathering tasks were the most complex; participants spent more time completing this task, viewed more pages, and used the Web browser functions most heavily during this task. The results of this analysis have been used to provide implications for future support of information seeking on the Web as well as direction for future research in this area.

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Abstract

Information extraction systems discover structured information in natural language text. Having information in structured form enables much richer querying and data mining than possible over the natural language text. However, information extraction is a computationally expensive task, and hence improving the efficiency of the extraction process over large text collections is of critical interest. In this paper, we focus on an especially valuable family of text collections, namely, the so-called deep-web text collections, whose contents are not crawlable and are only available via querying. Important steps for efficient information extraction over deep-web text collections (e.g., selecting the collections on which to focus the extraction effort, based on their contents; or learning which documents within these collections-and in which order-to process, based on their words and phrases) require having a representative document sample from each collection. These document samples have to be collected by querying the deep-web text collections, an expensive process that renders impractical the existing sampling approaches developed for other data scenarios. In this paper, we systematically study the space of query-based document sampling techniques for information extraction over the deep web. Specifically, we consider (i) alternative query execution schedules, which vary on how they account for the query effectiveness, and (ii) alternative document retrieval and processing schedules, which vary on how they distribute the extraction effort over documents. We report the results of the first large-scale experimental evaluation of sampling techniques for information extraction over the deep web. Our results show the merits and limitations of the alternative query execution and document retrieval and processing strategies, and provide a roadmap for addressing this critically important building block for efficient, scalable information extraction.

Type

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Abstract

Journalists were chosen for study because it was felt that they would be, as information seekers and packagers par excellence, in the advanced guard of Internet users and setting the pace. As it turned out this was not to be case. Despite what appear to be the considerable and direct benefits for them, after having interviewed approximately 150 journalists and observed the action in a variety of news rooms, it appears that less than one in five national journalist use the Internet and the proportion is much less than that for regional journalists. If this poor Internet take up in the workplace was unexpected, another surprise is the characteristics of those who have actually taken the Internet route. Far from being the stereotypical young and male, most are well practised journalist into their thirties/forties, which, of course, runs counter to all that we have been led to believe. Surprisingly, the study showed as much, if not more, interest in using the Internet from the supposedly `busy' senior managers and editors than in the rank and file.

Type

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Abstract

Conventional wisdom holds that queries to information retrieval systems will yield more relevant results if they contain multiple topic-related terms and use Boolean and phrase operators to enhance interpretation. Although studies have shown that the users of Web-based search engines typically enter short, term-based queries and rarely use search operators, little information exists concerning the effects of term and operator usage on the relevancy of search results. In this study, search engine users formulated queries on eight search topics. Each query was submitted to the user-specified search engine, and relevancy ratings for the retrieved pages were assigned. Expert-formulated queries were also submitted and provided a basis for comparing relevancy ratings across search engines. Data analysis based on our research model of the term and operator factors affecting relevancy was then conducted. The results show that the difference in the number of terms between expert and nonexpert searches, the percentage of matching terms between those searches, and the erroneous use of nonsupported operators in nonexpert searches explain most of the variation in the relevancy of search results. These findings highlight the need for designing search engine interfaces that provide greater support in the areas of term selection and operator usage

Type

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Abstract

In using the Internet to solve everyday problems, older adults tend to find fewer correct answers compared to younger adults. Some authors have argued that these differences could be explained by age-related decline. The present study aimed to analyze the relationship between web-searching navigation and users' age, considering the Intelligence Quotient (IQ) and frequency of Internet and personal computer use. The intent was to identify differences due to age and not to other variables (that is, cognitive decline, expertise with the tool). Eighteen students (18-30?years) and 18 older adults (60-75?years) took part in the experiment. Inclusion criteria were the frequent use of computers and a web-searching activity; the older adults performed the Mini-Mental State Examination to exclude cognitive impairment. Participants were requested to perform the Kaufman Brief Intelligence Test 2nd ed. to measure their IQ level, and nine everyday web-searching tasks of differing complexity. The results showed that older participants spent more time on solving tasks than younger participants, but with the same accuracy as young people. Furthermore, nonverbal IQ improved performance in terms of time among the older participants. Age did not influence web-searching behavior in users with normal expertise and intelligence.

Type

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