The depth of knowledge: surface, shallow or deep?

计算机科学 动作(物理) 知识管理 独创性 透视图(图形) 简单(哲学) 价值(数学) 帧(网络) 知识价值链 个人知识管理 人工智能 数据科学 组织学习 机器学习 认识论 心理学 创造力 量子力学 哲学 物理 社会心理学 电信
作者
David Bennet,Alex Bennet
出处
期刊:Vine [Emerald (MCB UP)]
卷期号:38 (4): 405-420 被引量:45
标识
DOI:10.1108/03055720810917679
摘要

Purpose The purpose of this paper is to consider knowledge from a new perspective that permits a rational analysis and interpretation of knowledge as it applies to learning and action in simple, complicated and complex situations. Design/methodology/approach This paper provides a fine‐grain analysis of knowledge. Specifically it looks at: the special relationship between knowledge and information (Kn I and Kn P ); knowledge types, the characteristics of knowledge used for different types of work; and levels of knowledge in terms of surface, shallow and deep. Following a discussion of knowledge from the these three frames of reference, this model is used to explore similarities in levels of learning, then it is applied to the complexity of situations, the complexity of making decisions and the complexity of actions. Findings There appears to be a correlation among the levels of knowledge and the corresponding levels of learning and action. In addition, the breakdown of systems into the classic three areas of simple, complicated and complex carry over into the three corresponding levels (surface, shallow and deep) as applied to learning and knowledge. Originality/value This is a new frame of reference for considering knowledge. This analysis can be used to ask relevant questions about specific levels of knowledge. It also enables managers to recognize the scope and depth of knowledge available to maximize problem solving, decision making and action in simple, complicated and complex situations. Further, it permits knowledge developers to tailor learning and knowledge to improve knowledge sharing and conservation.
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