Search (8 results, page 1 of 1)

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Abstract

Keeping up to date with research developments is a central activity of academic researchers, but researchers face difficulties in managing the rapid growth of available scientific information. This study examined how researchers stay up to date, using the information journey model as a framework for analysis and investigating which dimensions influence information behaviors. We designed a 2-round study involving semistructured interviews and prototype testing with 61 researchers with 3 levels of seniority (PhD student to professor). Data were analyzed following a semistructured qualitative approach. Five key dimensions that influence information behaviors were identified: level of seniority, information sources, state of the project, level of familiarity, and how well defined the relevant community is. These dimensions are interrelated and their values determine the flow of the information journey. Across all levels of professional expertise, researchers used similar hard (formal) sources to access content, while soft (interpersonal) sources were used to filter information. An important "pain point" that future information tools should address is helping researchers filter information at the point of need.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.1, S.22-35

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Abstract

An increasing number of tools are being developed to help academics interact with information, but little is known about the benefits of those tools for their users. This study evaluated academics' receptiveness to information proposed by a mobile app, the SerenA Notebook: information that is based in their inferred interests but does not relate directly to a prior recognized need. The evaluated app aimed at creating the experience of serendipitous encounters: generating ideas and inspiring thoughts, and potentially triggering follow-up actions, by providing users with suggestions related to their work and leisure interests. We studied how 20 academics interacted with messages sent by the mobile app (3 per day over 10 consecutive days). Collected data sets were analyzed using thematic analysis. We found that contextual factors (location, activity, and focus) strongly influenced their responses to messages. Academics described some unsolicited information as interesting but irrelevant when they could not make immediate use of it. They highlighted filtering information as their major struggle rather than finding information. Some messages that were positively received acted as reminders of activities participants were meant to be doing but were postponing, or were relevant to ongoing activities at the time the information was received.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.8, S.1883-1903

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Abstract

Purpose - This research seeks to gain a detailed understanding of how researchers come across information serendipitously, grounded in real-world examples. This research was undertaken to enrich the theoretical understanding of this slippery phenomenon. Design/methodology/approach - Semi-structured critical incident interviews were conducted with 28 interdisciplinary researchers. Interviewees were asked to discuss memorable examples of coming across information serendipitously from their research or everyday life. The data collection and analysis process followed many of the core principles of grounded theory methodology. Findings - The examples provided were varied, but shared common elements (they involved a mix of unexpectedness and insight and led to a valuable, unanticipated outcome). These elements form part of an empirically grounded process model of serendipity. In this model, a new connection is made that involves a mix of unexpectedness and insight and has the potential to lead to a valuable outcome. Projections are made on the potential value of the outcome and actions are taken to exploit the connection, leading to an (unanticipated) valuable outcome. Originality/value - The model provides researchers across disciplines with a structured means of understanding and describing serendipitous experiences.

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Abstract

Purpose - In "Coming across information serendipitously - Part 1: a process model" the authors identified common elements of researchers' experiences of "coming across information serendipitously". These experiences involve a mix of unexpectedness and insight and lead to a valuable, unanticipated outcome. In this article, the authors aim to show how the elements of unexpectedness, insight and value form a framework for subjectively classifying whether a particular experience might be considered serendipitous and, if so, just how serendipitous. Design/methodology/approach - The classification framework was constructed by analysing 46 experiences of coming across information serendipitously provided by 28 interdisciplinary researchers during critical incident interviews. "Serendipity stories" were written to summarise each experience and to facilitate their comparison. The common elements of unexpectedness, insight and value were identified in almost all the experiences. Findings - The presence of different mixes of unexpectedness, insight and value in the interviewees' experiences define a multi-dimensional conceptual space (which the authors call the "serendipity space"). In this space, different "strengths" of serendipity exist. The classification framework can be used to reason about whether an experience falls within the serendipity space and, if so, how "pure" or "dilute" it is. Originality/value - The framework provides researchers from various disciplines with a structured means of reasoning about and classifying potentially serendipitous experiences.

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Abstract

Serendipity occurs when unexpected circumstances and an "aha" moment of insight result in a valuable, unanticipated outcome. Designing digital information environments to support serendipity can not only provide users with new knowledge, but also propel them in directions they might not otherwise have traveled in-surprising and delighting them along the way. As serendipity involves unexpected circumstances it cannot be directly controlled, but it can be potentially influenced. However, to the best of our knowledge, no previous work has focused on providing a rich empirical understanding of how it might be influenced. We interviewed 14 creative professionals to identify their self-reported strategies aimed at increasing the likelihood of serendipity. These strategies form a framework for examining ways existing digital environments support serendipity and for considering how future environments can create opportunities for it. This is a new way of thinking about how to design for serendipity; by supporting the strategies found to increase its likelihood rather than attempting to support serendipity as a discrete phenomenon, digital environments not only have the potential to help users experience serendipity but also encourage them to adopt the strategies necessary to experience it more often.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.11, S.2179-2194

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Abstract

The motivation for this study was to better understand academics' searching and sensemaking processes when solving exploratory tasks for which they lack pre-existing frames. We focus on "influence" tasks because, although they appear to be unfamiliar, they arise in much academic discourse, at least tacitly. We report the processes of academics at different levels of seniority when completing exploratory search tasks that involved identifying influential members of their academic community and "rising stars," and similarly for an unfamiliar academic community. 11 think-aloud sessions followed by semi-structured interviews were conducted to investigate the roles of specific and general domain expertise in shaping information seeking and knowledge construction. Academics defined and completed the tasks through an iterative and interactive process of seeking and sensemaking, during which they constructed an understanding of their communities and determined qualities of "being influential". The Data/Frame Theory of Sensemaking was used to provide sensitising theoretical constructs. The study shows that both external and internal knowledge resources are essential to define a starting point or frame, make and support decisions, and experience satisfaction. Ill-defined or non-existent initial frames may cause unsubstantial or arbitrary decisions, and feelings of uncertainty and lack of confidence.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.8, S.1576-1593

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Abstract

Purpose - This research aims to identify some requirements for supporting user interactions with electronic current-awareness alert systems based on data from a professional work environment. Design/methodology/approach - Qualitative data were gathered using contextual inquiry observations with 21 workers at the London office of an international law firm. The analysis uses CASSM ("Concept-based Analysis of Surface and Structural Misfits"), a usability evaluation method structured around identifying mismatches, or "misfits", between user-concepts and concepts represented within a system. Findings - Participants were frequently overwhelmed by e-mail alerts, and a key requirement is to support efficient interaction. Several misfits, which act as barriers to efficient reviewing and follow-on activities, are demonstrated. These relate to a lack of representation of key user-concepts at the interface and/or within the system, including alert items and their properties, source documents, "back-story", primary sources, content categorisations and user collections. Research limitations/implications - Given these misfits, a set of requirements is derived to improve the efficiency with which users can achieve key outcomes with current-awareness information as these occur within a professional work environment. Originality/value - The findings will be of interest to current-awareness providers. The approach is relevant to information interaction researchers interested in deriving design requirements from naturalistic studies.

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Abstract

This paper reports findings from a study designed to gain broader understanding of sensemaking activities using the Data/Frame Theory as the analytical framework. Although this theory is one of the dominant models of sensemaking, it has not been extensively tested with a range of sensemaking tasks. The tasks discussed here focused on making sense of structures rather than processes or narratives. Eleven researchers were asked to construct understanding of how a scientific community in a particular domain is organized (e.g., people, relationships, contributions, factors) by exploring the concept of "influence" in academia. This topic was chosen because, although researchers frequently handle this type of task, it is unlikely that they have explicitly sought this type of information. We conducted a think-aloud study and semistructured interviews with junior and senior researchers from the human-computer interaction (HCI) domain, asking them to identify current leaders and rising stars in both HCI and chemistry. Data were coded and analyzed using the Data/Frame Model to both test and extend the model. Three themes emerged from the analysis: novices and experts' sensemaking activity chains, constructing frames through indicators, and characteristics of structure tasks. We propose extensions to the Data/Frame Model to accommodate structure sensemaking.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.4, S.841-858