In one of his first papers, Thomas Kuhn (1959) addressed the “essential tension” implicit in scientific research, i.e., the contrast between convergent and divergent thinking. He considered both to be central to the advance of science. Convergent thinking is what scientists do in their daily “normal research projects,” where the “scientist is not an innovator but a solver of puzzles, and the puzzles upon which he concentrates are just those which he believes can be both stated and solved within the existing scientific tradition” (ibid., p. 234). The convergent mode is “neither intended nor likely to produce fundamental discoveries or revolutionary changes in scientific theory” (ibid., p. 233). As he would describe in greater detail in The Structure of Scientific Revolutions (1970), this is because students are already discouraged from developing divergent-thinking abilities, partly because their education is based on textbooks, which “exhibit concrete problem solutions that the profession has come to accept as paradigms… Nothing could be better calculated to produce ‘mental sets’ or Einstellungen” (Kuhn, 1959, p. 229). Clearly, from this perspective, mental sets (or “mental inertia”) play an important role in paradigms as they prevent the normal scientist from gazing beyond the limits of her paradigm. Kuhn also emphasized the importance of convergent thinking as “no part of science progressed very far or very rapidly before this convergent education and correspondingly convergent normal practice became possible” (ibid., p. 237). However, Kuhn also recognized the divergent method because in order to assimilate new ­discoveries and theories “the scientist must usually rearrange the intellectual and manipulative equipment he has previously relied upon, discarding some elements of his prior belief” (ibid., p. 226).


Divergent Thinking Radical Constructivism Autopoietic System Reality Construction Convergent Thinking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I wish to express my gratitude to Marco Bettoni, Jeremy Burman and Armin Scholl for their helpful comments on a previous draft version of this article. Furthermore, I acknowledge the financial support from the Research Foundation - Flanders (FWO).


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Authors and Affiliations

  1. 1.Centre for Logic and Philosophy of Science and Leo Apostel Center for Interdisciplinary StudiesVrije Universiteit BrusselBrusselsBelgium

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