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 6) create ‘cross-links’, identifying connections between concepts that may be more distant than the simple downward branching of the overall concept map. This cross-linking procedure may even suggest a radical redrawing of the map, thereby simplifying its structure.

7) highlight, or weight, key concepts and links with bold lines or boxes, and use dashed lines and question marks for suspect portions. Am I insulting the reader by suggesting that a high-school or college learning technique such as in Figure 23 is also useful for the professional scientist? Long before the term concept mapping was invented, a very similar flowchart technique was used by scientists and other professionals, for the identical purpose of visualizing the relationships among complex phenomena. For example, Figure 24 [Bronowski, 1973] is a page from the notes of John von Neumann, one of the most outstanding mathematicians of the 20th century; apparently his photographic memory did not preclude the usefulness of conceptual flowcharts. Figures 4 and 22 are additional examples. For the scientist who is analyzing and evaluating a scientific article, or who is trying to work through a complex idea, concept mapping can be a visualization and evaluation aid.

Model/observation tables, outlines, and concept maps are quite different in format but similar in function. Each provides a visual structure that attempts to assure that all relevant information and relationships are considered, that focuses attention on pivotal concerns, and that identifies strengths and weaknesses. Popular memory aids such as underlining, notetaking, and paraphrasing do not fulfill these objectives as reliably.

The scientist who attempts to visualize the entire pattern of evidence risks neglecting a crucial relationship. Writing it in a systematized form may reveal that gap.

Because model/observation tables, outlines, and concept maps compel the scientist to organize knowledge, they are a wonderful first step toward writing up scientific results for publication.