A Framework for “Just-in-Time Learning” Decision Support in Organizations

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Author(s): Mark Salisbury (University of St. Thomas, Minneapolis, USA)
Copyright: 2021
Pages: 18
Source title: Research Anthology on Artificial Intelligence Applications in Security
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-7705-9.ch022

Keywords: Artificial Intelligence / Computer Science & IT / Cyber and Network Security / Information Science Reference

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Abstract

This article describes an integrated “Just-in-Time Learning” framework for providing decision support in organizations. The framework emerges from years of work with the national laboratories and facilities that are under the direction of the United States Department of Energy. The article begins by describing expert systems technology and how it has been used to provide decision support in organizations. This is followed by a discussion of the strengths and weaknesses of expert systems technology for this purpose. Next, a “Just-in-Time Learning” framework is introduced where the theoretical foundation for the framework is described. Afterwards, the other aspects of the framework including the types of knowledge, learners it serves, and how the framework can be utilized for decision support are detailed. Finally, a discussion section summarizes how a Just-in-Time Learning Framework can achieve some of the strengths -- while overcoming some of the weaknesses -- of expert system technology for providing decision support in organizations.

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A Framework for “Just-in-Time Learning” Decision Support in Organizations

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