The depth of knowledge: surface, shallow or deep?
| Pages | 405-420 |
| Published date | 24 October 2008 |
| DOI | https://doi.org/10.1108/03055720810917679 |
| Date | 24 October 2008 |
| Author | David Bennet,Alex Bennet |
| Subject Matter | Information & knowledge management |
ARTICLES
The depth of knowledge: surface,
shallow or deep?
David Bennet and Alex Bennet
Mountain Quest Institute, Marlinton, West Virginia, USA
Abstract
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.
Keywords Knowledge processes,Knowledge sharing, Knowledgemanagement, Learning,
Decision making
Paper type Research paper
Introduction
A few years ago this might have been considered a paper that added anothe r
perspective to the emerging theory of knowledge, as indeed it does. But today, there is
a crying need in organizations to learn more about deep knowledge. We call this body
of ideas action theory because of the direct link between knowledge and action. The
following is the logic trail. The performance of any organization is determined every
day by the actions taken by every single employee. Decisions drive those actions, and
knowledge empowers good decisions and implements effective actions (see the
definition of knowledge). Thus the knowledge within an organization determines
organizational performance. In addition, meta knowledge (knowledge about
knowledge) occurs at the level of patterns, a notch above pragmatic knowledge in
terms of context and content. This means that it is not tied to a specific conten t or
context, but rather is associated with higher-level patterns suggested by that content
and context that can potentially be transferred to other situations.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0305-5728.htm
The depth of
knowledge
405
VINE: The journal of information and
knowledge management systems
Vol. 38 No. 4, 2008
pp. 405-420
qEmerald Group Publishing Limited
0305-5728
DOI 10.1108/03055720810917679
Acknowledging that any framework or model is an artificial construct, we
nonetheless propose that it is helpful to consider knowledge in terms of three levels:
surface knowledge, shallow knowledge and deep knowledge. The analogy built upon
here is that of exploring the ocean. A pontoon or light sail boat catching the wind skims
rapidly across the waters without concern for that which lies below in the water; as
long as whatever lies below does not come to or affect the surface, it is of little concern
to forward movement. For any boat moving in shallow waters, more attention (and
some understanding) is required of what is beneath the surface, dependent on the
ballast, to ensure forward movement. In deep waters – engaged over longer periods of
time – safety and success require a proven vessel, an experienced capta in, a thorough
understanding of oceanography, a well-honed navigation system sensitive to current
flows and dangers of the ocean, and a well-developed intuition sensitive to deep water
terrain, currents and so forth. Carrying the metaphor a bit further, whether surfing or
moving through shallow or deep waters, a certain amount of skill is involved, although
these also require somewhat different skill sets. The metaphor deals with the level of
involvements with what is below the surface. Further, as a ship moves into deep waters
there is increased reliance on experience and intuition as unforeseen perturbations
move into the situation.
This paper views knowledge from three different fames of reference. First, we look
at the special relationship between knowledge and information (Kn
I
and Kn
P
). Second,
we look at levels of knowledge in terms of surface, shallow and deep. This approach
provides very real insights. If the American automobile industry had understood the
different levels of knowledge, perhaps they would have made a larger investment in
the deep knowledge needed for long-term survival. Third, we explore knowledge types,
the characteristics of knowledge used for different types of work. Following this
discussion of knowledge from these three frames of reference, we move on to use this
same approach to explore similarities in levels of learning, then apply this model to the
complexity of situations, complexity of making decisions and the complexity of
actions.
Definitions
Consistent with our previous work, we embrace Stonier’s (1990, 1997) description of
information as a basic property of the Universe – as fundamental as matter and
energy. Information is the result of organization expressed by any non-random pattern
or set of patterns. Data (a form of information) are simple patterns, and data and
information are both patterns but have no meaning until some organism recognizes
and interprets the patterns (Bennet and Bennet, 2008). Thus knowledge exists in the
human brain in the form of stored or expressed neural patterns that may be selected,
activated, mixed and/or reflected upon through thought. From this mixing process new
patterns are created that may represent understanding, meaning and the capacity to
anticipate (to various degrees) the results of potential actions. Through these processes
the mind is continuously growing, restructuring and creating increased organization
(information) and knowledge. The difference between information and knowledge
highlights the difficulty of knowledge sharing by recognizing that knowledge must be
recreated by a listener and that only information can be transferred between two
people.
VINE
38,4
406
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