Novak's cmap home
Concept Maps: What the heck is this?
Excerpted, rearranged (and annotated)
from an online manuscript by Joseph D. Novak, Cornell University
original manuscript was revised in 2008-> http://cmap.ihmc.us/Publications/ResearchPapers/TheoryCmaps/TheoryUnderlyingConceptMaps.htm
Concept maps are tools for organizing
and representing knowledge. They include concepts, usually enclosed in
circles or boxes of some type, and relationships between concepts or propositions,
(indicated by a connecting line and linking word)
between two concepts. Linking words
on the line specify the relationship between the two concepts. Joe Novak
defines "concept" as a perceived regularity in events or objects, or records
of events or objects, designated by a label. Think
of the concept "Dog" in your mind, what do you see? You
might see a prototype shape (head, four legs etc) and typical examples
(terrier, collie, sheepdog) and even be able to explain it (give a definition)
in words. The label for most concepts is a word, although sometimes
we use symbols such as + or %. Propositions are statements about some object
or event in the universe, either naturally occurring or constructed. Propositions
contain two or more concepts connected with other words to form a meaningful
statement. Sometimes these are called semantic units,or units of meaning.
Figure 1 shows an example of a concept map that
describes the structure of concept maps and illustrates the above characteristics.
There are two features of concept maps that are important
in the facilitation of creative thinking: the hierarchical structure that
is represented in a good map and the ability to search for and characterize
cross-links. In a concept map the concepts should be represented in a hierarchical
fashion with the most inclusive, most general concepts at the top of the
map and the more specific, less general concepts arranged hierarchically
below. The hierarchical structure for a particular domain of knowledge
also depends on the context in which that knowledge is being applied or
considered. Therefore, it is best to construct concept maps with reference
to some particular question we seek to answer or some situation or event
that we are trying to understand through the organization of knowledge
in the form of a concept map. Another important characteristic of concept
maps is the inclusion of "cross-links." These are relationships (propositions
=linking lines with linking words) between concepts in different domains
of the concept map. Cross-links help us to see how some domains of knowledge
represented on the map are related to each other. In the creation of new
knowledge, cross-links often represent creative leaps on the part of the
knowledge producer. A final features that may be added to concept maps
are specific examples or actual images of events or objects that help to
clarify the meaning of a given concept.
As defined above, concepts and propositons are the building
blocks for knowledge in any domain. We can use the analogy that concepts
are like the atoms of matter and propositions are like the molecules of
matter. There are now about 460,000 words in the English language, and
these can be comibined to form an infinite number of propositions; albeit
most combinations of words might be nonsense, there is still the possibility
of creating an infinite number of valid propositions. We shall never run
out of opportunities to create new knowledge! As people create and observe
new or exisiting objects or events, we will continue to create new knowledge.
Figure 1 A
concept map about concept mapping
Constructing Good Concept Maps
In learning to construct a concept map,
it is important to begin with a domain (an area)
of knowledge that is very familiar to the person constructing the map.
Since concept map structures are dependent on the context in which they
will be used, it is best to identify a segment of a text, a laboratory
activity, or a particular problem or question that one is trying to understand.
This creates a context that will help to determine the hierarchical structure
of the concept map. It is also helpful to select a limited domain of knowledge
for the first concept maps. Once a domain has been selected, the next step
is to identify the
key concepts that apply to this domain. These
could be listed, and then from this list a rank order should be established
from the most general, most inclusive concept, for this particular problem
or situation, to the most specific, least general concept. Although this
rank order may be only approximate, it helps to begin the process of map
The next step is to construct a preliminary concept map.
This can be done by writing all of the concepts on Post-its, or
preferably by using a computer software program. Post-its allow a group
to work on a whiteboard or butcher paper and to move concepts around easily
This is necessary as one begins to struggle with the process of building
a good hierarchical organization. Computer software programs are even better
in that they allow moving of concepts together with linking statements
and also the moving of groups of concepts and links to restructure the
map. They also permit a computer printout, producing a nice product that
can be e-mailed or in other ways easily shared with collaborators or pother
Figure 2 shows a list of concepts
for making a concept map to address the question, "What is a plant?" What
is shown is only one of many possible maps. Simple as this map is, it may
contain some propositions that are new to the reader. It is important to
recognize that a concept map is never finished. After a preliminary map
is constructed, it is always necessary to revise this map. Good maps usually
undergo three to many revisions. This is one reason why computer software
is helpful. After a preliminary map is constructed, cross-links should
be sought. These are links between different domains of knowledge on the
map that help to illustrate how these domains are related to one another.
Finally, the map should be revised, concepts positioned in ways that lend
to clarity, and a "final" map prepared.
Figure 2 Creating
a GOOD MAP
It is important to help students recognize that all concepts
are in some way related to one another. Therefore, it is necessary to be
selective in identifying cross-links, and to be as precise as possible
in identifying linking words that connect concepts. In addition, one should
avoid "sentences in the boxes" since this usually indicates that a whole
subsection of the map could be constructed from the statement in the box.
"String maps" or ("Sentence maps")
illustrate either poor understanding of the material or an inadequate restructuring
of the map. Figure 3 shows an example of a string
Students often comment that it is hard to add linking
words onto their concept map. This is because they only poorly understand
the relationship between the concepts and it is the linking words that
specify this relationship. Once students begin to focus in on good linking
words, and also identification of good cross-links, they can see that every
concept could be related to every other concept. This also produces some
frustration, and they must choose to identify the most prominent and most
useful cross-links. This process involves what Bloom (1956) identified
as high levels of cognitive performance, namely evaluation and synthesis
of knowledge. Concept mapping is an easy way to achieve very high levels
of cognitive performance, when the process is done well. This is one reason
concept mapping can be a very powerful evaluation tool.
Figure 3 Creating
a "String" or "Sentence" map (NOT A GOOD MAP)
Facilitating Cooperative Learning
Using concept maps in planning
a curriculum or instruction on a specific topic helps to make the instruction
"conceptually transparent" to students. Many students have difficulty identifying
and constructing powerful concept and propositional frameworks, leading
them to see science learning as a blur of myriad facts or equations to
be memorized. If concept maps are used in planning instruction and students
are required to construct concept maps as they are learning, previously
unsuccessful students can become successful in making sense out of science
and acquiring a feeling of control over the subject matter (Bascones &
Novak, 1985; Novak, 1991; Novak, 1998). There is a growing body of research
that shows that when students work in small groups and cooperate in striving
to learn subject matter, positive cognitive and affective outcomes result
(Johnson et al., 1981). In our work with both teachers and students, small
groups working cooperatively to construct concept maps have proven to be
useful in many contexts. For example, the concept maps shown in Figure
4 was constructed by faculty working together to plan instruction in
veterinary medicine at Cornell University. In my own classes, and in classes
taught by my students, small groups of students working collectively to
construct concept maps can produce some remarkably good maps. In a variety
of educational settings, concept mapping in small groups has served us
well in tasks as diverse as understanding ideas in assimilation theory
to clarifying job conflicts for conflict resolution in profit and non-profit
corporations. Concept maps are now beginning to be used in corporations
to help teams clarify and articulate the knowledge needed to solve problems
ranging from the design of new products to marketing to administrative
Figure 4 A
map created by a collaborative group
Concept Maps for Evaluation
We are now beginning to see in many
science textbooks the inclusion of concept mapping as one way to summarize
understandings acquired by students after they study a unit or chapter.
Change in school practices is always slow, but it is likely that the use
of concept maps in school instruction will increase substantially in the
next decade or two. When concept maps are used in instruction, they can
also be used for evaluation. There is nothing written in stone that says
multiple choice tests must be used from grade school through university,
and perhaps in time even national achievement exams will utilize concept
mapping as a powerful evaluation tool. This is a chicken-and-egg problem
because concept maps cannot be required on national achievement tests,
if most students have not been given opportunities to learn to use this
knowledge representation tool. On the other hand, if state, regional, and
national achievement exams will utilize concept mapping as a powerful evaluation
tool. This is a chicken-and-egg problem because concept maps cannot be
required on national achievement tests, if most students have not been
given opportunities to learn to use this knowledge representation tool.
On the other hand, if state, regional, and national exams would begin to
include concept maps as a segment of the exam, there would be a great incentive
for teachers to teach students how to use this tool. Hopefully, by the
year 2061, this will come to pass.
Origins and Educational Theory
of Concept Maps (Joe Novak)
Concept maps were developed
in the course of our research program where we sought to follow and understand
changes in childrenÕs know ledge of science. This program was based
on the learning psychology of David Ausubel (1963, 1968, 1978). The fundamental
idea in Ausubel's cognitive psychology is that learning takes place by
the assimilation of new concepts and propositions into existing concept
propositional frameworks held by the learner. The question sometimes arises
as to the origin of the first concepts; these are acquired by children
during the ages of birth to three years, when they recognize regularities
in the world around them and begin to identify language labels or symbols
for these regularities (Macnamara, 1982). This is a phenomenal ability
that is part of the evolutionary heritage of all normal human beings. After
age 3, new concept and propositional learning is mediated heavily by language,
and takes place primarily by a reception learning process where
new meanings are obtained by asking questions and getting clarification
of relationships between old concepts and propositions and new concepts
and propositions. This acquisition is mediated in a very important way
when concrete experiences or props are available; hence the importance
of "hands-on" activity for science learning with young children, but this
is also true with learners of any age and in any subject matter domain.
In addition to the distinction between the discovery learning process,
where the attributes of concepts are identified autonomously by the learner,
and the reception learning process, where attributes of concepts are described
using language and transmitted to the learner, Ausubel made the very important
distinction between rote learning and meaningful learning. Meaningful learning
requires three conditions:
One of the powerful uses of concept maps is not only as a
learning tool but also as an evaluation tool, thus encouraging students
to use meaningful-mode learning patterns (Novak & Gowin, 1984; Novak,
1990, Mintzes, Wandersee and Novak, 2000). Concept maps are also effective
in identifying both valid and invalid ideas held by students. They can
be as effective as more time-consuming clinical interviews (Edwards &
The material to be learned must be conceptually clear and
presented with language and examples relatable to the learner's prior knowledge.
Concept maps can be helpful to meet this condition, both by identifying
large general concepts prior to instruction in more specific concepts,
and by assisting in the sequencing of learning tasks though progressively
more explicit knowledge that can be anchored into developing conceptual
The learner must possess relevant prior knowledge. This condition
is easily met after age 3 for virtually any domain of subject matter, but
it is necessary to be careful and explicit in building concept frameworks
if one hopes to present detailed specific knowledge in any field in subsequent
lessons. We see, therefore, that conditions (1) and (2) are interrelated
and both are important.
The learner must choose to learn meaningfully. The one condition
over which the teacher or mentor has only indirect control is the motivation
of students to choose to learn by attempting to incorporate new meanings
into their prior knowledge, rather than simply memorizing concept definitions
or propositional statements or computational procedures. The control over
this choice is primarily in the evaluation strategies used, and typical
objective tests seldom require more than rote learning (Holden, 1992).
In fact, the worst forms of objective tests, or short-answers tests, require
verbatim recall of statements and this may be impeded by meaningful learning
where new knowledge is assimilated into existing frameworks, making it
difficult to recall specific, verbatim definitions or descriptions. This
kind of problem was recognized years ago in Hoffman's (1962), The Tyranny
Another important advance in our understanding of learning
is that the human memory is not a single "vessel" to be filled, but rather
a complex set of interrelated memory systems. Figure
5 illustrates the three memory systems of the human mind.
Figure 5 The
three memory systems of the human mind
While all memory systems are
interdependent (and have information going in both directions), the most
critical memory system for incorporating knowledge into long-term memory
is the short-term or "working memory." All incoming information is organized
and processed in the working memory by interaction with knowledge in long-term
memory. The limiting feature here is that working memory can process only
a relatively small number (five to nine) of psychological units at any
one moment. This means that relationships among two or three concepts are
about the limit of working memory processing capacity. Therefore, to structure
large bodies of knowledge requires an orderly sequence of iterations between
working memory and long-term memory as new knowledge is being received
(Anderson, 1991). We believe one of the reasons concept mapping is so powerful
for the facilitation of meaningful learning is that it serves as a kind
of template to help to organize knowledge and to structure it, even though
the structure must be built up piece by piece with small units of interacting
concept and propositional frameworks. Many learners and teachers are surprised
to see how this simple tool facilitates meaningful learning and the creation
of powerful knowledge frameworks that not only permit utilization of the
knowledge in new contexts, but also retention of the knowledge for long
periods of time (Novak, 1990; Novak & Wandersee, 1991). There is still
relatively little known about memory processes and how knowledge finally
gets incorporated into our brain, but it seems evident from diverse sources
of research that our brain works to organize knowledge in hierarchical
frameworks and that learning approaches that facilitate this process significantly
enhance the learning capability of all learners.
While it is true that some students have more difficulty
building concept maps and using these, at least early in their experience,
this appears to result primarily from years of rote-mode learning practice
in school settings rather than as a result of brain structure differences
per se. Socalled "learning style" differences are, to a large extent, differences
in the patterns of learning that students have employed varying from high
commitment to continuous rote-mode learning to almost exclusive commitment
to meaningful mode learning. It is not easy to help students in the former
condition move to patterns of learning of the latter type. While concept
maps can help, students also need to be taught something about brain mechanisms
and knowledge organization,and this instruction should accompany the use
of concept maps.
Anderson, O. R. (1992). Some interrelationships between constructivist
models of learning and current neurobiological theory, with implications
for science education. Journal of Research in Science Teaching,
Ausubel, D. P. (1963). The Psychology of Meaningful Verbal Learning.
New York: Grune and Stratton.
Ausubel, D. P. (1968). Educational Psychology: A Cognitive View.
New York: Holt, Rinehart and Winston.
Ausubel, D. P., J. D. Novak, and H. Hanesian. (1978). Educational Psychology:
A Cognitive View, 2nd ed. New York: Holt, Rinehart and Winston. Reprinted,
New York: Warbel & Peck, 1986.
Bascones, J., & J. D. Novak. (1985). Alternative instructional systems
and the development of problem-solving skills in physics. European Journal
of Science Education, 7(3), 253-261.
Bloom, B. S. (1956). Taxonomy of Educational Objectives--The Classification
of Educational Goals. New York: David McKay.
Edwards, J., and K. Fraser. (1983). Concept maps as reflectors of conceptual
understanding. Research in Science Education, 13, 19-26.
Hoffman, B. (1962). The Tyranny of Testing. New York: Corwell-Collier.
Holden, C. (1992). Study flunks science and math tests. Science,
Johnson, D., G. Maruyama, R. Johnson, D. Nelson, and L. Skon. (1981). The
effects of cooperative, competitive and individualistic goal structure
on achievement: A meta-analysis. Psychological Bulletin, 89, 47-62.
Macnamara, J. (1982). Names for Things: A Study of Human Learning.
Cambridge, MA: M.I.T. Press.
Mintzes, J., Wandersee, J. and Novak, J. (1998) Teaching Science For
Understanding. San Diego: Academic Press.
Mintzes, J., Wandersee, J. and Novak, J. (2000) Assessing Science Understanding.
San Diego: Academic Press
Novak, J. D. (1977). A Theory of Education. Ithaca, NY: Cornell
Novak, J. D. (1990). Concept maps and Vee diagrams: Two metacognitive tools
for science and mathematics education. Instructional Science, 19,
Novak, J. D. (1991). Clarify with concept maps. The Science Teacher,
Novak, J. D., & D. B. Gowin. (1984). Learning How to Learn.
New York and Cambridge, UK: Cambridge University Press.
Novak, J. D., & D. Musonda. (1991). A twelve-year longitudinal study
of science concept learning. American Educational Research Journal,
Novak, J. D., & J. Wandersee, 1991. Coeditors, Special Issue on Concept
Mapping of Journal of Research in Science Teaching, 28, 10.