Introduction
This presentation is not meant as a review of the use of visualization
in education. What I would like to present here is a discussion of the
types of roles visualization can play in an educational setting and to
draw attention to issues that must be addressed when designing such
visualizations.
Visualization
In short Visualization is the graphical display of
information. The purpose of this graphical display is to provide the
viewer a visual means of processing the information. It is important
to note that for a vizualization to be effective it must draw upon the
knowledge base of the viewer. If the viewer does not posess the
knowledge to understand the graphical entities and the relations
between them the visualization does not achieve its
goal. Visualization has many applications. For the most part they can
be classified into two categories:
- Data Exploration
- Communicating Information
Data Exploration is the practice of using visualization techniques to
find unforseen relationships between data points or sets of points in
large databases. Once a relationship has been found the same
visualization can be used to communicate that relation to
others. Visualization techniques can also be applied to information
that is already known. For a more in depth discussion of information
visualization see Matt
Ward-Data Visualization
Visualization in Education
Education can be viewed as the externally facilitated development of
knowledge. This external influence can take many forms (a teacher,
textbook, article, movie, TV show, computer program, ...). The purpose
of any visualization to be used in an educational context is to
facilitate the learning of some knowledge (idea, concept, fact,
algorithm, relationship, ...). In order to accomplish this a
visualization must make connections between knowledge the learner has
and the knowledge being taught. Therefor in order to design effective
visualizations it is necessary to know (or at least have a theory
about) what the learner knows. This is especially important in the
context of education. As will be discussed shortly the learner
knowledge base for a given concept can take several forms. These
different forms influence how the visualization will be interpreted
and integerated into their knowledge base. Before this issue can be
addressed, however, a framework is needed for discussing knowledge and
how it might be represented internally.
Representation of Knowledge
James Hiebert and Thomas Carpenter in [6] present a framework for
discussing the representation of mathematical concepts in the context
of teaching for understanding. The concepts in there framework,
however, are not specific to mathematics and can be applied to
rpresentation of knowledge in general. Their framework also provides a
useful means for discussing the role that external representations
play in learning. The main points of their framework are:
- Relationships exist between external and internal representations.
- The form of external representation with which the student interacts
influenes how knowledge is represented internally.
- The form in which a student externally represents
knowledge if influenced by their internal representation.
- Internal representations of knowledge are connected to
form networks of knowledge.
- Networks can be hierarchical - some representations
subsume others
- Networks can be graphlike - nodes represent pieces of
information and the arcs represent the relationships between them.
- Most likely a combination of the two.
- Understanding occurs when a idea is well integrated into a
richly connected network
Given this framework we can now address the types of knowledge a
student can have about a given concept that they are trying to
learn. These type of knowledge can be broken into four
categories. Each of these will be discussed below.
- Fragmented & Incorrect
- Fragmented & Correct
- Coherent & Incorrect
- Coherent & Correct
Fragmented Knowledge
Fragmented knowledge (correct or incorrect) results in domains in
which the student has had little or no experience. Often the student
will posess some intuition about the domain but these intuitions have
not been connected. In these case nodes exist in the network but are
not strongly connected to either each other or other knowledge domains
in the network. The role of visualization is then to demonstrate the
relations between nodes in the network. If the original concepts were
incorrect the the visualization must relations between the new correct
nodes and other domains within the network. Teaching a student with
fragmented knowledge, although not trivial, is not a daunting
task. Because there are not many connections from the incorrect nodes
to the rest of the network they can be replaced/removed without
significantly damaging the network. Here we should also include the
case that the student has no knowledge about a domain. Here the
visualization must make connections to other domains in the
network.
Coherent Knowledge
In the case of coherent correct knowledge the visualization has a
wealth of knowledge to draw upon. The case where the sutdent has a
coherent network of incorrect knowledge is the most difficult to
teach. In this case the student is said to have a misconception (see
Carey[1] and diSessa[4][5]for a discussion of misconceptions in
science education) of the concept. The primary problem is this case is
that the student will interpret the information being taught in the
context of their misconception. Here the visualization must not only
make connections to other domains but also demonstrate the
inconsistancies in the students misconception. This demonstration of
inconsistancies is often referred as inducing disequilibrium in the
misconception of the student.