European Journal of Education Studies
ISSN: 2501 - 1111
ISSN-L: 2501 - 1111
Available on-line at: www.oapub.org/edu
10.5281/zenodo.168088 Volume 2│Issue 9│2016
UTILIZATION OF KNOWLEDGE MIND MAPPING
TO ESTABLISH STRONG DEPARTMENTS IN UNIVERSITIES
Namasaka Fred1i, Omoro Alfred1, Lina Kamuren2, Winnie Namasaka3
1Department of Curriculum, Instruction & Educational Technology,
Pwani University, P.O. Box 195-80108, Kilifi, Kenya
2Racecourse High School, P.O.Box, 5308, Eldoret, Kenya
3 Catholic University of Eastern Africa, GABA Campus, P.O. Box, 5308, Eldoret, Kenya
Abstract:
The problem of managing knowledge is receiving considerable attention with the
increased generation of new knowledge derived from meaningful information globally
and daily. Knowledge management should thus not be seen as a means to an end but
an end in itself. According to Mike (1996), knowledge management is important only to
the extent that it enhances an organization s ability and capacity to deal with and
develop in four dimensions namely: mission, competition, performance and change.
The value of knowledge management therefore relates directly to the effectiveness with
which the managed knowledge enables the members of the institution/organization to
deal with today s situations and effectively envision and create their future. This paper
examines how knowledge mapping can be utilized to portray a perspective of the
players, sources, flows, constraints, and sinks of knowledge within an organization. A
knowledge map (k-map) is a navigation aid to both explicit information and tacit
knowledge, showing the importance and the relationships between knowledge stores
and the dynamics. The authors focus is on how knowledge mapping could help
discover the constraints, assumptions, location, ownership, value and use of knowledge
assets, artifacts, people and their expertise, uncover blocks to knowledge creation and
find opportunities to leverage existing knowledge. This is done with specific reference
to universities as institutions of higher learning in Kenya. We shall use data collected
from archives, interviews, newspapers and published reports. This paper challenges the
current set up of knowledge management in Kenyan universities.
i Correspondence: email fnamasaka@yahoo.co.uk
Copyright © The Author(s). All Rights Reserved 150
Published by Open Access Publishing Group ©2015.
Namasaka Fred, Omoro Alfred, Lina Kamuren, Winnie Namasaka -
UTILIZATION OF KNOWLEDGE MIND MAPPINGTO ESTABLISH
STRONG DEPARTMENTS IN UNIVERSITIES
Keywords: knowledge, knowledge generation, knowledge management, knowledge
mapping
Introduction
Knowledge management has emerged as the hottest subject of debate today. In this
article, the term knowledge is used to refer to that meaningful information that is
derived from raw data. This article attempts to address pertinent issues pertaining to
knowledge and its management. Key among them include: meaning, properties,
sources, types, production, distribution, uses and benefits of knowledge; challenges or
problems related to knowledge management; mapping and conclusion. Before
commencing to address the Question of knowledge management using K-maps, it is
probably appropriate to develop some framework regarding knowledge itself as
described in the text that follows.
The Origin and Growth of Human Knowledge
Review of Literature suggests that knowledge originate from three sources namely:
providence, instruction and selection. According to Plato, a Greek Philosopher who
lived in Athens during the fourth and fifth centuries BC, knowledge goes beyond what
we can learn about the world through our senses. Scholars refer to this source as
knowledge by recollection. This perspective leads us to two kinds of knowledge, that is;
factual knowledge and conceptual knowledge. Plato s thought represents a view that is
known in philosophy as the doctrine of recollection or to use the Greek word, anamnesis
which means that all knowledge is in essence remembered or recollected. Plato,
therefore, proposed a view that the origin of knowledge is a providential one, believing
that knowledge is provided by a benevolent God. According to Simmons (2003), this
view was supported by Rene Descartes, who lived from 9 to .
However, three British Philosophers who lived during the 17th and 18th centuries
developed epistemological theories contrary to the providential perspective held by
Plato and Descartes. The first was John Locke (1632 – 1704), who completely rejected
and suggested that all knowledge has its origin in sensory experience provided by
sight, hearing, touch and smell that then become our knowledge of the world. Not
assuring that senses provide accurate knowledge concerning all aspects of the external
world, Locke made a distinction between what he called the Primary and Secondary
Qualities of things Bennet, 9 . Locke s idea of secondary Qualities was a significant
recognition that not all our perceptions of the external world necessarily indicate to us
the actual state of the world.
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UTILIZATION OF KNOWLEDGE MIND MAPPINGTO ESTABLISH
STRONG DEPARTMENTS IN UNIVERSITIES
That admission opened the way for other Philosophers to re-look at the theory of
knowledge instructed by our senses. One such philosopher was George Berkeley, an
Irish born Anglican Bishop who lived from 1685 to 1753. According to Berkeley, what
we experience by way of our senses is due to the direct action of God; it consequently
follows that through the senses, God communicates with us and informs us (Bennet,
9 . We therefore see that Berkeley s epistemology is both providential, that is all
knowledge is provided by God, and instructionist, in that all knowledge is transmitted
through our senses. David Hume (1711 – 1776), a Scottish Philosopher was the last of
the three British empiricists and probably the most interesting and influential. He was
very much fascinated by Newton s success in discovering laws of Physics and thus
attempted to apply Newton s experimental method to deepen and broaden
understanding of the content and abilities of the human mind and to create a method of
generating or producing knowledge (discovering truth).
Hume reasoned and recognized that we can never know the external world
directly since all that we know of the world is a product of our own sensory perceptions
of it and the ideas that these perceptions generate. His conclusion is that we cannot
establish an empirical basis for knowledge by use of induction (Hampton 1995).
Induction refers to the process by which we can derive general knowledge based on
observation of a limited number of cases or instances such as samples in research. It is
rightly so because perceptions of the same object can vary from person to person, and
even within the same person. His ultimate conclusion was that all human knowledge is
fallible and therefore no kind of amount of experience, logic or reasoning could be
trusted to eliminate the possibility of error. Use of instruments in gathering raw data
which is converted to meaningful information to yield knowledge probably serves to
help minimize the errors.
In pursuit of a naturalistic, non-miraculous account of the knowledge that
appears to be prior to our sensory experience, Konrad Lorenz made a significant
contribution to epistemology. In a paper published in 1941, Lovenz argued that prior
knowledge does not result from a limited experience of an individual but rather a
product of a long process of evolution of the human species.
According to Lovenz (2007), biological evolution endowed us with the central
nervous system (CNS) that reflects past knowledge acquired through the natural
selection of our past generations. Fortunately some post-modern philosophers such as
sir Karl Popper and Donald Campbell have extended Darwinian cumulative variation
and selection to knowledge processes occurring among humankind and thus advanced
the selectionist view of knowledge and thought.
In conclusion, to this sub-section, it should be noted that according to the
sociology of knowledge, human knowledge is distributed within and among humans,
the level of education not withstanding, thus need to manage it well. The implication is
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STRONG DEPARTMENTS IN UNIVERSITIES
that each human being of person has some form of knowledge, either tacit or explicit.
The process of generating knowledge is discussed in the text that follows.
Generation of Human Knowledge
Did you know that there is an established relationship between data, information,
knowledge, wisdom and truth? The following diagram attempts to explain the basis for
thought relating to the aforementioned concepts.
Figure 1.1
Wisdom
Knowledge
Understanding principles
Information
Knowledge
Understanding patterns
Understanding relationships/
relations
Data Understanding
(adopted from Fleming, 2008)
Based on the diagram shown, the main idea is that information, knowledge and
wisdom are seldom were collections but represent much more the sum of its
component. Data refers to any occurrence of something, either an object or event.
Accordingly, data represents a phenomenon out of context, that is, without a
meaningful relation to anything else. The first step in generation of knowledge is
usually an attempt to devise a way to attribute meaning to it, thus creating a context.
The second and probably the most crucial step is to convert data into information. This
can be achieved simply by understanding the relationships between pieces of data and
other information.
The third step is to create knowledge by understanding the pattern that exists
between data and information. The pattern so established embodies consistency,
completeness, repeatability and predictability. Then finally and forth step, wisdom
arises when the interpreter understands the foundational principle responsible for the
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STRONG DEPARTMENTS IN UNIVERSITIES
established patterns representing knowledge. These foundational principles are
external truths that are universal and extremely context independent. To sum it up, the
following associations can be acceptably made:
Data is an occurrence out of context;
Information relates to definition, description or perspective (what, who, where,
when);
Knowledge comprise approach / strategy, method or practice (how);
Wisdom embodies insight, moral or principle (why).
Note should be taken that though data is a discrete entity, its conversion to
information, then to knowledge, and ultimately to wisdom does not usually progress in
discrete stages of development. A continuum emerges as understanding develops by
deepening and broadening awareness and familiarity. The implication is that one can
have partial understanding of the relations that constitute information, partial
understanding of the patterns that comprise knowledge as well as the principles which
are the foundation of wisdom. Since most of us in our work environments, usually find
ourselves operating at the partial understanding stage, there is needed to extend the
concept. This can be done by connecting new information to pattern that we already
understand or have. Csikszentuihalyi (1994) designed a model to help simplify the
otherwise complex knowledge, hence need for knowledge management. This is
discussed in the text that follows.
Knowledge Management
The brief discussion on knowledge as a concept has undoubtedly laid a foundation for
discourse on its management. Knowledge management is crucial only to the extent that
in enhances on institution s ability to develop in her mission and deal with competition,
performance and manage change.
According to Mike (1996), knowledge management relates to finding answers to
the following questions:
(i) What is the institution trying to accomplish? (Mission);
(ii) How does the institution gain a competitive edge? (competition);
(iii) How does the institution deliver the results? (Performance);
(iv) How does the institution cope with change? (Change).
One last Question and probably the most troubling of all: What is the real value
of information and knowledge if it is not utilized and what does it mean to manage
knowledge? A strong argument is made that without associations we seldom
understand anything (Bateson, 1988). It is therefore true to say that our understanding
of things is based on the associations that we are able to discern in that particular
context. However, the trap that many managers and administrators fall into is that of
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STRONG DEPARTMENTS IN UNIVERSITIES
not utilizing the knowledge available in an appropriate manner. Many of them make
crucial decisions based on data but without understanding that data alone does not
predict trends of data is the activity that is responsible for the data.
For example, if someone asks what the University enrolment is apt to be in the
next academic year for the privately sponsored students programmes (PSSP) the
admissions office would have to say “it depends. It is rightly so because although the
officer has data and information, she/he does not have the knowledge. In order for
him/her to estimate the enrolment for the next academic year, she/he would need
information concerning the catchment area, competition, available vacancies, student
satisfaction, with regard to content/curriculum delivery, current backlog and absorption
in job market among other things. The administrator will have to obtain sufficient
amount of data and information in order to form a complete pattern that she/he
understands and that will be his/her knowledge. This will then enable him/her to
comfortably make estimation of enrolment in the next year of study.
From the example given, it can be noted that what needs to be managed to create
value is the data and information that defines past results, associated with the
institution, it s catchment, it s potential clients, and its competitors, and the patterns
that relate all these items to ensure a reliable degree of predictability of the future.
According to Kebao and Junxun (2008), knowledge management would simply refer to
the capture, retention, and utilization of the foundation for creating an understanding
of how all these pieces fit together and how to convey then meaningfully to someone
else.
In conclusion, to this sub-section, the authors state that the real value of
knowledge management relates directly to the effectiveness with which the managed
knowledge enables the members of the institution to deal with the current situation and
effectively envision and create their future. When access to managed knowledge is
made possible in an institution, every situation, pleasant or painful is addressed with
the sum total of everything anybody in the institution has ever learned concerning the
situation of a similar nature. This strengthens the need for knowledge mapping using k-
map as a tool for effective knowledge management. The text that follows will discuss
knowledge mapping and K-map tools in detail.
Knowledge Mapping and K-Maps
Knowledge mapping is a strong instrument used in the analysis of knowledge. It helps
team workers to fully grasp the context, situation and prevailing circumstances by
getting a bird s eye view of it, that is, 3600 meaning all round (Bellinger, 1997).
Knowledge can now be defined as a set of data and information, to which is added
expert opinion and experience, to result in a valuable asset which can be utilized or
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applied to help in decision making and problem solving. Knowledge may be explicit
and /or tacit, individual and/or collective.
Knowledge mapping on the other hand is all about keeping a record of
information and knowledge so as to effectively operate, whether as an individual or in a
group. Some issues involved include; where information and knowledge can be
obtained from, who holds it, whose expertise is it and so on. This is now where K-maps
becomes handy and give details of every bit of knowledge that exists within the
institution including location, quality, and accessibility, and the knowledge required for
the smooth running of the institution. It therefore helps one to find out the required
knowledge easily and effectively. Knowledge mapping illustrates how knowledge
flows throughout an organization thus making it available in a transparent manner
(George, 2006). It helps an organization to appreciate how the loss of staff influences
intellectual capital. It ensures best utilization of resources, independent of form on
source. In summary, it describes who has what knowledge (tacit), where the knowledge
resides (infrastructure), and how the knowledge is transferred or distributed (social).
Procedure for creating knowledge maps (K-maps)
K-maps are made by representing tacit and explicit knowledge into graphical formats
that are easy to grasp and interpret by the users or interested parties such as directors,
managers, heads of departments, system and programme developers among others.
Basic steps to follow in knowledge mapping
1. Identify the objects to be mapped. These include:
(a) Explicit or formal knowledge (documented /coded knowledge; specify;
Subject (discipline, area);
Purpose;
Location (people, intellectual assets, faculty,
Department, library.
Format (codified, personalized, internal, external)
Ownership (people, departments, documents)
Users (managers, program/system developers,
implementers)
Access right (copyright, access fee)
(b) Tacit or informal knowledge (Implicit/undocumented/uncoded) specify;
Expertise;
Experience;
Skill;
Location – Islands of expertise;
Contact address;
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UTILIZATION OF KNOWLEDGE MIND MAPPINGTO ESTABLISH
STRONG DEPARTMENTS IN UNIVERSITIES
Accessibility;
Networks / relationships.
2. Determine where the knowledge resides or where it is found. That is, identify the
sources or stores of knowledge within the organization.
For example:
Internal documents in files;
Library;
Correspondences;
Archives (Past proposals & report documents);
Experience (Past work records);
Minutes of meetings;
Best practices;
Corporate memory (processes, people, policies, relationships,
documents, conversations, partners, links & contexts).
3. Establish / Determine the flows of knowledge from the various sources to the
Respective sinks (where the knowledge is used = end user). For example, web designer
(source) to Registrar admissions (sink or end user). Also, identify the channels to be
used in order to access the knowledge and the paths of knowledge exchange.
4. Envision and determine the constraints to the free flow of knowledge along the
established paths of exchange. For example; Pervasion of truths in the swamps of
bureaucracy; managerial blind spots in the work environment, Negligence, inefficiency,
poor attitude, lack of support, poor coordination and loss of a member of staff.
5. Identify the knowledge gaps, that is, what we know we don t know and figure
out the dynamics.
6. Determine the knowledge life-cycle. Ensure that knowledge is up-to-date and
accurate.
7. Design a graphical format on representation to show linkage of all objects and
that will be the ultimate K-map ready for use. A good K-map has the following salient
features:
The outcomes of all processes and their contribution to key organizational
activities.
Logical sequence of all resources and activities required to achieve institutional
goal.
Actual knowledge although deficiencies always occur
Human resource required to undertake each activity. Helps to reflect whether
recruitment is needed.
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Benefits of K-Maps
According to Fleming (2008), the benefits of K-maps include the following:
(i) Helps to find crucial information quickly;
(ii) To single out Islands of expertise;
(iii) To create an inventory and assessment of intangible and intellectual assets;
(iv) To enhance decision-making and problem solving by highlighting applicable
information;
(v) To identify main sources of knowledge generation;
(vi) To foster re-use of knowledge and prevent reinvention;
(vii) To provide insights into corporate knowledge;
(viii) To continually evolve institutional memory, capturing and integrating main
and new knowledge of an institution;
(ix) K-maps enrich employee s know-what and know-how base;
(x) They enable employees learn through intuitive navigation and interrogation
of the information thus create new network for efficient working.
Applications of K-Maps
a. Competency mapping. To create competency profile with skills, positions and
even career path of an individual. It acts as an institution s yellow pages thus enabling
employees to find much needed expertise among people within the institution (Senge,
1990).
b. Conceptual knowledge mapping in didactics and mathematics. Also referred
to as taxonomy. This is a way of arranging and classifying content from the major
concept to the subordinate or minor concepts. This kind of K-maps involves labeling
pieces of knowledge and their hierarchical relationships between them. They can relate
similar kind of knowledge housed by two different departments thus making them
more integrated.
c. Process-based knowledge mapping. This type of K-maps shows knowledge and
sources/ stores of knowledge for both internal and external organizational procedures &
processes. They involve explicit knowledge (codified as found in documents) and tacit
knowledge (knowledge in people such as experience and technical know-how.)
Department as basic functional unit of a University
Most universities recognize both in philosophy and in practice that a department is the
basic functional unit of the university just like a cell is to a human body. However, in
some cases, other entities such as schools, divisions and directorates may serve as a
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functional unit equivalent to a department. Strong academic departments are thus
desirable to enable the university archive her overall mission.
Consequently, the commitment of a department to academic excellence must be
predicated upon full participation of all members of department as well as students.
The recognition of this necessity rests upon the assumption that total involvement
confers obligations upon those who assume positions in order to serve humanity.
On this premise, the department is undoubtedly the primary focus of operation for all
stake holders of the university community. The departments should thus embrace
efficiency and effectiveness to customer satisfaction standards.
The authors of this paper perceive that members of department based on their
qualification and experience have a rich reservoir of knowledge. Both explicit tacit
knowledge can be rapped out for the benefit of all in need of it. Knowledge mapping
therefore become an appropriate strategy for harnessing and utilizing the rich
knowledge base housed in the department.
This calls for identification of all areas of departmental operation. The
organizational structure will then provide for effective determination and mapping of
knowledge that each member possesses. The knowledge could be helpful in governing
curriculum, personal, facility maintenance, and administrative as well as whole
relationships. The department as a whole can autonomously carry out its functions
using the knowledge mapping approach. Knowledge maps will help in locating people
and offices that have knowledge which others seek for decision-making and solving
problems. An illustration of knowledge map for a typical academic department of a
university is given in figure1.2
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UTILIZATION OF KNOWLEDGE MIND MAPPINGTO ESTABLISH
STRONG DEPARTMENTS IN UNIVERSITIES
Figure 1.2
Conclusion
In many institutions of Higher learning such as Universities there is often lack of
transparency in the organization of the vast range of knowledge at their disposal.
Invaluable knowledge is seldom used because people do not know it exists and even
when they know it exists, they still cannot figure out where it resides. These are
pertinent issues which are well addressed by knowledge mapping. K-maps provide an
assessment of existing and required knowledge and information in critical areas of
operation of the institution. They help to answer Questions such as: what knowledge is
required for work to be done? Who has it? Who needs what? Is the knowledge explicit
or tacit? And so on. Universities should therefore make sure that K-Maps are used in
the best interest of the institutions. The K-maps once prepared should be accessible to
all who work in those institutions. They should also be easy to understand, update.
Evolution of the Universities K-maps should be an ongoing process since knowledge
landscapes are dynamic. Shoved knowledge can propel our universities to peak
performance both locally and globally.
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