{"title":"The predictors of academics' online information searching strategies: A structural model integrating cognitive absorption and digital literacy","authors":"Betul Tok Kose , Omer Kocak","doi":"10.1016/j.lisr.2024.101299","DOIUrl":null,"url":null,"abstract":"<div><p>Searching for information on online environments is a crucial part of today's academics' work. However, no published research has been identified that comprehensively focuses on academics' online information searching patterns. This study aimed to determine the predictor variables of academics' online information searching strategies. A structural model which seeks to explain the relationship between online information searching strategies and predictor variables was constructed. Data was collected with four different data collection instruments: “Personal Information Form”, “Online Information Searching Strategies Scales”, “Cognitive Absorption Scale”, and “Digital Literacy Scale”, which were collected from 501 academics from 18 different universities. SEM analysis techniques were used in the analysis of the data. Twenty-four hypotheses were tested through SEM analysis. The results of the analysis found that academics' online information search strategies can be predicted by digital literacy. Daily internet usage time has a significant effect on cognitive absorption. In addition, digital literacy has a mediating role between online information searching strategies and cognitive absorption.</p></div>","PeriodicalId":47618,"journal":{"name":"Library & Information Science Research","volume":"46 2","pages":"Article 101299"},"PeriodicalIF":2.4000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Library & Information Science Research","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0740818824000203","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Searching for information on online environments is a crucial part of today's academics' work. However, no published research has been identified that comprehensively focuses on academics' online information searching patterns. This study aimed to determine the predictor variables of academics' online information searching strategies. A structural model which seeks to explain the relationship between online information searching strategies and predictor variables was constructed. Data was collected with four different data collection instruments: “Personal Information Form”, “Online Information Searching Strategies Scales”, “Cognitive Absorption Scale”, and “Digital Literacy Scale”, which were collected from 501 academics from 18 different universities. SEM analysis techniques were used in the analysis of the data. Twenty-four hypotheses were tested through SEM analysis. The results of the analysis found that academics' online information search strategies can be predicted by digital literacy. Daily internet usage time has a significant effect on cognitive absorption. In addition, digital literacy has a mediating role between online information searching strategies and cognitive absorption.
在网络环境中搜索信息是当今学者工作的重要组成部分。然而,目前尚未发现全面关注学者在线信息搜索模式的公开研究。本研究旨在确定学者在线信息搜索策略的预测变量。研究构建了一个结构模型,旨在解释在线信息搜索策略与预测变量之间的关系。使用四种不同的数据收集工具收集数据:数据收集工具包括 "个人信息表"、"在线信息搜索策略量表"、"认知吸收量表 "和 "数字素养量表"。数据分析采用了 SEM 分析技术。通过 SEM 分析检验了 24 个假设。分析结果发现,数字素养可以预测学者的网络信息搜索策略。每天使用互联网的时间对认知吸收有显著影响。此外,数字素养在网络信息搜索策略和认知吸收之间具有中介作用。
期刊介绍:
Library & Information Science Research, a cross-disciplinary and refereed journal, focuses on the research process in library and information science as well as research findings and, where applicable, their practical applications and significance. All papers are subject to a double-blind reviewing process.