Search (3 results, page 1 of 1)

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Abstract

Many scientific fields share common interests for research and education. Yet, very often, these fields do not communicate to each other and are unaware of the work in other fields. Understanding the commonalities and differences among related fields can broaden our understanding of the interested phenomena from various perspectives, better utilize resources, enhance collaboration, and eventually move the related fields forward together. In this article, we present a conceptual framework, namely the Information-Model or I-model, to describe various aspects of information related fields. We consider this a timely effort in light of the evolutions of several information related fields and a set of questions related to the identities of these fields. It is especially timely in defining the newly formed Information Field from a community of twenty some information schools. We posit that the information related fields are built on a number of other fields but with their own unique foci and concerns. That is, core components from other fundamental fields interact and integrate with each other to form dynamic and interesting information related fields that all have to do with information, technology, people, and organization/society. The conceptual framework can have a number of uses. Besides providing a unified view of these related fields, it can be used to examine old case studies, recent research projects, educational programs and curricula concerns, as well as to illustrate the commonalities and differences with the information related fields.

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Abstract

Throughout an information search, a user needs to make sense of the information found to create an understanding. This requires cognitive effort that can be demanding. Building on prior sensemaking models and expanding them with ideas from learning and cognitive psychology, we examined the use of cognitive mechanisms during individual sensemaking. We conducted a qualitative user study of 15 students who searched for and made sense of information for business analysis and news writing tasks. Through the analysis of think-aloud protocols, recordings of screen movements, intermediate work products of sensemaking, including notes and concept maps, and final reports, we observed the use of 17 data-driven and structure-driven mechanisms for processing new information, examining individual concepts and relationships, and detecting anomalies. These cognitive mechanisms, as the basic operators that move sensemaking forward, provide in-depth understanding of how people process information to produce sense. Meaningful learning and sensemaking are closely related, so our findings apply to learning as well. Our results contribute to a better understanding of the sensemaking process-how people think-and this better understanding can inform the teaching of thinking skills and the design of improved sensemaking assistants and mind tools.

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Date

22. 8.2014 16:55:39