Invention of Concept Mapping

Concept maps were first developed in 1972 in the course of Novak’s research program at Cornell University where his team sought to follow and understand changes in children’s knowledge of science (Novak & Musonda, 1991). During the course of this study the researchers interviewed many children, and they found it was difficult to identify specific changes in the children’s understanding of science concepts by examination of interview transcripts. This program was based on the learning psychology of David Ausubel (Ausubel, 1963, 1968; Ausubel, Novak, & Hanesian, 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 and propositional frameworks held by the learner. This knowledge structure as held by a learner is also referred to as the individual’s cognitive structure. Out of the necessity to find a better way to represent children’s conceptual understanding emerged the idea of representing children’s knowledge in the form of a concept map. Concept maps are a representation that shows explicit relationships between concepts using linking words between concepts and arranging the ideas expressed in a hierarchical form. Figure 1 shows a concept map that illustrates the key features of concept maps.

Figure 1. A concept map showing the key features of concept maps.
(click on an image for a larger view)

We discovered that concept maps were not only useful for graduate students to represent the knowledge of children, but for the graduate students to express their own understanding about a domain. The power of concept maps as a means for a teacher to assess the changes in the knowledge of students became apparent, and concept mapping took off worldwide as a learning tool. Novak and Gowin's Learning How to Learn book (1984), translated to 9 languages, became the main reference to concept mapping as its popularity grew. Thus was born a new tool not only for use in research, but also for many other uses.

Development of Computer-based Concept Mapping Tools

For many years, concept map were drawn by hand. Iterating through revisions of a concept map was cumbersome and time consuming. Group concept mapping sessions would be handled by using post-it notes. The introduction of personal computers enabled the development of software programs that facilitated the construction of concept maps. Initial versions of concept mapping programs, however, did not enhance the power of the tool – they were limited to displaying a concept map on the screen. Programs like Inspiration popularized the use of concept mapping in elementary school education by allowing children to easily add pictures and clipart to concepts. Other software program like Knowledge Manager and Smart Ideas have also taken advantage of technology to facilitate the construction of concept maps. However, it was the marriage of the concept map and the Internet that launched a completely new world of applications and uses for concept mapping, as exemplified by the CmapTools software (Cañas et al., 2004).

In 1987, Novak began his association with the University of West Florida and with the Institute for Human and Machine Cognition (IHMC), then part of the University. By the late 1980’s and beginning of the 1990’s concept mapping was being used at IHMC as a tool for knowledge elicitation (Ford et al., 1991,1996) and as the explanation component of expert systems (Ford et al., 1993). We started using concept maps to organize and navigate through large amounts of information via hyperlinks before the World Wide Web was developed (Cañas et al., 1994); and developing tools to enable collaborative concept mapping across a network. These efforts led to the development of CmapTools, a client-server software tool to facilitate the construction and sharing of concept maps. CmapTools (the latest version of the software can be downloaded at no cost at: http://cmap.ihmc.us) exemplifies how, by leveraging the Internet and the WWW, the concept map goes beyond a knowledge representation tool, becoming also a mechanism to structure and navigate through large amounts of information by serving both as an organization medium as a well as the launching pad for searching and mining the WWW and visualizing information (Cañas et al., 2005), and resulting in the development of a framework for collaborative work and learning. The integration of new technology with concept mapping has triggered innovative applications and extensions to the tool, and we expect this to trend to continue.

References and Further Readings

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., Novak, J. D., & Hanesian, H. (1978). Educational Psychology: A Cognitive View (2nd ed.). New York: Holt, Rinehart and Winston.

Cañas A. J., Ford K. M., and Coffey J. W. (1994) Concept Maps as a Hypermedia Navigational Tool. Seventh Florida Artificial Intelligence Research Symposium. Pensacola, FL: FLAIRS.

Cañas, A. J., Hill, G., Carff, R., Suri, N., Lott, J., Eskridge, T., et al. (2004). CmapTools: A Knowledge Modeling and Sharing Environment. In A. J. Cañas, J. D. Novak & F. M. González (Eds.), Concept Maps: Theory, Methodology, Technology. Proceedings of the First International Conference on Concept Mapping (Vol. I, pp. 125-133). Pamplona, Spain: Universidad Pública de Navarra.

Cañas, A. J., Carff, R., Hill, G., Carvalho, M., Arguedas, M., Eskridge, T., et al. (2005). Concept Maps: Integrating Knowledge and Information Visualization. In S.-O. Tergan & T. Keller (Eds.), Knowledge and Information Visualization: Searching for Synergies (pp. 205-219). Heidelberg/NY: Springer Lecture Notes in Computer Science.

Ford, K. M., Cañas, A. J., Jones, J., Stahl, H., Novak, J. D., & Adams-Webber, J. (1991). ICONKAT: An integrated constructivist knowledge acquisition tool. Knowledge Acquisition, 3, 215-236.

Ford, K. M., Cañas, A. J., & Coffey, J. W. (1993). Participatory Explanation. In D. D. Dankel & J. Stewman (Eds.), Proceedings of the Sixth Florida Artificial Intelligence Research Symposium (pp. 111-115). Ft. Lauderadale, FL: FLAIRS.

Ford, K. M., Coffey, J. W., Cañas, A. J., Andrews, E. J., & Turner, C. W. (1996). Diagnosis and Explanation by a Nuclear Cardiology Expert System. International Journal of Expert Systems, 9, 499-506.

Novak, J. D. (1998). Learning, Creating, and Using Knowledge: Concept Maps as Facilitative Tools in Schools and Corporations. Mahwah, NJ: Lawrence Erlbaum Associates.

Novak, J. D., & Gowin, D. B. (1984). Learning How to Learn. New York, NY: Cambridge University Press.

Novak, J. D., & Musonda, D. (1991). A Twelve-Year Longitudinal Study of Science Concept Learning. American Educational Research Journal, 28(1), 117-153.

Last update: August 28, 2009