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Classroom Assessment Techniques
Concept Mapping

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Theory and Research
Concept mapping emerges directly from David P. Ausubel's Assimilation Theory of meaningful verbal learning (Ausubel, Novak, and Hanesian, 1978). The underlying basis of the theory is that meaningful (as opposed to rote) human learning occurs when new knowledge is consciously and purposively linked to an existing framework of prior knowledge in a non-arbitrary, substantive fashion. In rote (or memorized) learning, new concepts are added to the learner's framework in an arbitrary and verbatim way, producing a weak and unstable structure that quickly degenerates. The result of meaningful learning is a change in the way individuals experience the world; a conceptual change. Joseph D. Novak and his colleagues at Cornell University developed the concept mapping technique in the early 1970s. Concept maps have been used for over 25 years in research and classroom practice to reveal and assess the structure and complexity of knowledge held by students in the sciences and other disciplines (Novak and Gowin, 1984).

The core element of a concept map is a proposition, which consists of two or more concepts connected by a labeled link. In a concept map, propositions are connected to each other to form a hierarchical, branching, and dendritic structure that represents the organization of knowledge in long-term memory. The basic assumption of the concept map is that "interrelatedness" is an essential property of knowledge, and that "understanding" can be represented through a rich set of relations among important concepts in a discipline.

More than two hundred studies in science education have employed concept mapping in one form or another (Novak, 1998; Novak and Wandersee, 1990; Mintzes, Wandersee and Novak, 1998). Several of these investigations have examined the reliability and validity of the technique as a way of representing knowledge in scientific disciplines (Markham, Mintzes and Jones, 1994; Pearsall, Skipper, and Mintzes, 1997; Ruiz-Primo and Shavelson, 1994; Songer and Mintzes, 1994; Wallace and Mintzes, 1990). In general, these and other studies suggest that the technique has many of the desirable characteristics that testing and measurement experts look for in new assessment tools. For example, in one study (Markham, et al., 1994) it was shown that the conceptual frameworks revealed by concept maps reflect essentially the same structure as that seen in much more time-consuming techniques, such as interviews and picture sorting tasks. In another study (Pearsall, et al., 1997), successive concept mapping conducted over the course of a full semester in introductory college biology, revealed a cumulative, step-wise growth in knowledge that one would expect to see if the technique taps into students' expanding conceptual frameworks.

Several studies suggest that concept map scores do not correlate significantly with traditional measures of learning such as multiple choice tests. Novak, Gowin, and Johansen (1983) showed that mapping scores were not significantly related to students' SAT scores. These findings suggest that a concept map taps into a substantially different dimension of learning than conventional classroom assessment techniques. It is likely that many techniques commonly used in college science courses focus largely on rote aspects of learning. On the other hand, Schau and Mattern (1997) found that posttest scores on "Select and Fill-in" maps drawn by graduate students in introductory statistics correlated significantly with final course grades (correlation coefficient, r=0.85; N=15). Among novice astronomy students, Zeilik, et al. (1998) reported a substantially weaker relationship (r 0.4; N 700). The interpretation from this study is that traditional evaluation tools (quizzes, tests, final grades) capture some aspects of conceptual structure, and concept maps capture other aspects.


Angelo, Thomas A. and Cross, K. Patricia (1993). Classroom assessment techniques: A handbook for college teachers. 2nd edition. San Francisco: Jossey-Bass Publishers.

Austin, L.B. and Shore, B.M. (1995). Using concept mapping for assessment in physics. Physics Education 30 (1): 41-45.

Markham, K., Mintzes, J. and Jones, G. (1994). The concept map as a research and evaluation tool: Further evidence of validity. Journal of Research in Science Teaching, 31(1): 91-101.

Mintzes, J.J., Wandersee,J.H. & Novak, J.D. (1998). Teaching science for understanding: A human constructivist view. San Diego, CA: Academic Press.

Novak, J.D. (1998). Learning, creating and using knowledge: Concept maps as facilitative tools in schools and corporations. Mahwah, NJ: Lawrence Erlbaum.

Novak, J.D. & Gowin, D.B. (1984). Learning how to learn. Cambridge University Press.

Novak, J.D. & Wandersee, J.D., (Eds.), (1990). Perspectives on concept mapping. Journal of Research in Science Teaching, 20 (10); Special Issue.

Pearsall, R., Skipper, J., and Mintzes, J. Knowledge restructuring in the life sciences: A longitudinal study of conceptual change in biology. Science Education, 81, 193-215.

Pendley, B.D., Bretz, R.L. & Novak, J.D. (1994). Concept maps as a tool to assess learning in chemistry. Journal of Chemical Education, 71 (1): 9-15.

Ruiz-Primo, M. and Shavelson, R. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33 (6): 569-600.

Schau, C. and Mattern, N. (1997). Use of map techniques in teaching statistics courses. The American Statistician, 51 (2): 171-175.

Wallace, J. and Mintzes, J. (1990). The concept map as a research tool: Exploring conceptual change in biology. Journal of Research in Science Teaching, 27(10): 1033-1052.

Zeilik, M., Schau, C. and Mattern, N. (1998). Conceptual astronomy II: Replicating conceptual gains, probing attitude changes across three semesters. Submitted to The American Journal of Physics.

Zeilik, M, Schau, C., Mattern, N., Hall, S., Teague, K. & Bisard, W. (1997). Conceptual astronomy: A novel model for teaching postsecondary science courses. American Journal of Physics, 65 (10): 987-996.

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