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Knowledge Representation and Relation Nets introduces a fresh
approach to knowledge representation that can be used to organize
study material in a convenient, teachable and learnable form. The
method extends and formalizes concept mapping by developing
knowledge representation as a structure of concepts and the
relationships among them. Such a formal description of analogy
results in a controlled method of modeling `new' knowledge in terms
of `existing' knowledge in teaching and learning situations, and
its applications result in a consistent and well-organized approach
to problem solving. Additionally, strategies for the presentation
of study material to learners arise naturally in this
representation. While the theory of relation nets is dealt with in
detail in part of this book, the reader need not master the formal
mathematics in order to apply the theory to this method of
knowledge representation. To assist the reader, each chapter starts
with a brief summary, and the main ideas are illustrated by
examples. The reader is also given an intuitive view of the formal
notions used in the applications by means of diagrams, informal
descriptions, and simple sets of construction rules. Knowledge
Representation and Relation Nets is an excellent source for
teachers, courseware designers and researchers in knowledge
representation, cognitive science, theories of learning, the
psychology of education, and structural modeling.
Knowledge Representation and Relation Nets introduces a fresh
approach to knowledge representation that can be used to organize
study material in a convenient, teachable and learnable form. The
method extends and formalizes concept mapping by developing
knowledge representation as a structure of concepts and the
relationships among them. Such a formal description of analogy
results in a controlled method of modeling new' knowledge in terms
of existing' knowledge in teaching and learning situations, and its
applications result in a consistent and well-organized approach to
problem solving. Additionally, strategies for the presentation of
study material to learners arise naturally in this representation.
While the theory of relation nets is dealt with in detail in part
of this book, the reader need not master the formal mathematics in
order to apply the theory to this method of knowledge
representation. To assist the reader, each chapter starts with a
brief summary, and the main ideas are illustrated by examples. The
reader is also given an intuitive view of the formal notions used
in the applications by means of diagrams, informal descriptions,
and simple sets of construction rules. Knowledge Representation and
Relation Nets is an excellent source for teachers, courseware
designers and researchers in knowledge representation, cognitive
science, theories of learning, the psychology of education, and
structural modeling.
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