Uncertainty in information seeking and retrieval: A study in an academic environment

Chowdhury, Sudatta; Gibb, Forbes; Landoni, Monica

doi:10.1016/j.ipm.2010.09.006

Cited by 62 publications

(44 citation statements)

References 28 publications

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“…Using the Czech data from the Program for International Student Assessment (PISA) 2006, Kubiatko and Vlckova (2010) found that students who had used computers the longest attained higher scores for a test of ICT knowledge. Chowdhury, Gibb, and Landoni (2011) came to the conclusion that experience of university staff members of searching for information on the Internet depended on their age. From these studies, we can derive that age might have some influence on mastering ICT skills.…”

Section: Introductionmentioning

confidence: 99%

“…Many publications have shown that girls and women are less keen to work with a computer or to apply ICT programs or ICT instruments compared with boys and men (Volman & van Eck, 2001;Losh, 2004;Becker, 2006;Madigan et al, 2007;Kubiatko, 2010;Zhao et al, 2010;van Deursen & van Dijk, 2015). However, research (Bovée, Voogt, & Meelissen, 2007;Wang, Wu, & Wang, 2009;Verhoeven et al, 2010;De Wit et al, 2012) has also demonstrated that the gap between male and female actors is not common to all types of use of ICT applications and not in all countries (Spiezia, 2010), and that women (researchers) are more proficient in some ICT skills than men are (Chowdhury et al, 2011). With regard to the link between gender and ICT and research in secondary education, Hohlfeld, Ritzhaupt, and Barron (2013) even concluded "that the gender gap for demonstrated technology skills has closed", although this observation was not confirmed by the longitudinal study among adults by van Deursen and van Dijk (2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploring the Self-Reported ICT Skill Levels of Undergraduate Science Students

Heerwegh¹,

Wit

Verhoeven

2016

JITE:Research

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Computers have taken an important place in the training of science students and in the professional life of scientists. It is often taken for granted that most students have mastered basic Information and Communication Technologies (ICT) skills; however, it has been shown that not all students are equally proficient in this regard. Starting from theories of socialization and technology acceptance we report how we constructed a structural equation model (SEM) to explore the variance in the basic ICT skill levels of science students. We also present the results of a test of this model with university bachelor's science students. Basic ICT skills were measured using a new, elaborate instrument allowing students to rate their skills in detail. Our results show that science students score high on basic ICT skills and that our SEM explains a large part of the variation in the ICT skill levels of these students. The most explanatory power is coming from four variables: the perceived ease of use and the perceived usefulness of a personal computer, the anxiety for using a personal computer, and students' belief that ICT is necessary for scientific research.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the Self-Reported ICT Skill Levels of Undergraduate Science Students

Heerwegh¹,

Wit

Verhoeven

2016

JITE:Research

View full text Add to dashboard Cite

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“…The results showed that uncertainty persisted and that there were no correlations between the participants' task and/or topic familiarity and the degree of uncertainty with regard to specific information-seeking activities and information-seeking problems (Chowdhury et al, 2011). Participants were found to have felt an average to a high level of positive impact from uncertainty during the IS&R process, and that uncertainty shifted over …”

Section: Jdoc 704mentioning

confidence: 90%

“…In order to gather data in relation to RQ1, a nation-wide online survey was conducted (Chowdhury et al, 2011). The quantitative data obtained was analysed to see if any correlations existed between the information-seeking activities and information-seeking problems that cause uncertainty in IS&R. Details of the findings of that study appear in Chowdhury and Gibb (2009); and some are discussed later in this paper.…”

Section: Jdoc 704mentioning

confidence: 99%

A model of uncertainty and its relation to information seeking and retrieval (IS&R)

Chowdhury

Gibb

Landoni

2014

Journal of Documentation

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Purpose -The purpose of this paper is to show that uncertainty may be caused not only by a knowledge gap in the mind of a user with respect to a given subject or topic, but also by the various complexities associated with the information seeking and retrieval (IS&R) process in a digital environment. Design/methodology/approach -Both quantitative and qualitative studies were conducted to collect data from users in the higher education sector regarding whether or not they experienced uncertainty in relation to the IS&R process. Analysis: a correlation analysis was undertaken to establish whether there were any relationships between information-seeking activities and information-seeking problems. Findings -The findings of this research show that uncertainty existed at different stages of the IS&R process amongst users. It was established that uncertainty was caused by a number of information-seeking activities and information-seeking problems, and that such uncertainty could continue over the course of successive search sessions, leading to the proposal of a new model of uncertainty.Research limitations/implications -The proposed model of uncertainty should contribute to a better understanding of the issues related to IS&R in a digital environment. Practical implications -A number of benefits could be realised in systems design from the application of this model in terms of reducing the negative impact of uncertainty, while at the same time helping users to gain from the positive aspects of uncertainty in IS&R. Originality/value -The general consensus is that uncertainty is a mental state of users reflecting a gap in knowledge which triggers an IS&R process, and that the gap is reduced as relevant information is found, and thus that the uncertainty disappears as the search process concludes. However, in the present study it is argued that some form of uncertainty is always associated with some part of the IS&R process and that it also fluctuates throughout the IS&R process. Users may therefore feel uncertain at any stage of the IS&R process and this may be related to: the initial information need and expression of that need, the search process itself, including identification of relevant systems, services and resources; and the assessment of, and reaction to, the results produced by the search process. Uncertainty may be unresolved, or even increase, as the user progresses, often iteratively, through the IS&R process and may remain even after its completion, resulting in what may be called a persistent uncertainty. In other words, this research hypothesises that, in addition to the uncertainty that triggers the information search process , users suffer from varying degrees of uncertainty at every stage of the information search and retrieval process, and that in turn, triggers different information-seeking behaviours.

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“…Those include: three types of uncertainty related to knowledge deficiency -indeterminacy, ignorance, and incommensurability [12]; positive uncertainty to generate creativity [13]; correlations among information seeking activities and information seeking problems that cause uncertainty [14]; the effects of physicians' attitudes toward uncertainty on their use of electronic information resources [15]; use of online tutorials to reduce uncertainty in information seeking behavior [16]; a review of the literature with a focus on emotion (i.e., uncertainty) of healthcare professionals [17]; uncertainty of work task in stage-driven information seeking process [18]; uncertainty in the virtual playground of generation Y students [19]; information seeking activities and information seeking problem as the causes of uncertainty [20]; the effects of task uncertainty on the scope of external information seeking [21]; three different types(task, A few studies investigated user perceptions of uncertainty, yet in different stages from the stage of results evaluation as the present study does. Those different stages include the selection of information systems [6] and the selection of search terms [7].…”

Section: Literature Reviewmentioning

confidence: 99%