The Word-sentence construction (Woseco) task versus the verbal fluency task: Capturing features of scientific creativity via semantic networks
preprint
OA: closed
Abstract
Scientific creativity involves creating novel links between distant scientific and non-scientific concepts. Such creative linking can be captured with the novel Word-sentence-construction (Woseco) task. The Woseco task emphasises syntactic and context-related connections (e.g. “teacher” and “blackboard” being syntactically and contextually connected in the sentence “The teacher writes on the blackboard.”) which may be relevant for achieving remote associations and problem-solving, key aspects of scientific creativity. This paper tests the Woseco task as a network-building process, capturing individuals ́ ability in linking concepts across contexts. We compare Woseco networks against verbal fluency networks from 169 students enrolled in middle schools and academic secondary schools in Austria. Of these students, 90 participated in a Scientific Creativity in Practice (SCIP) program previously shown to promote scientific creative thinking. For the concepts of “school” and “chemistry”, the Woseco networks showed more prominent features of creativity than verbal fluency networks, i.e., higher node clustering (t = 14.88, p < .001), lower network distances separating concepts (t = -9.95, p < .001), and overall lower network modularity (t = -23.93, p < .001). Additionally, significant differences in semantic network structure were observed between the intervention and control groups (p < .022), with the intervention group showing more interconnected networks after creativity training in both their Woseco and fluency networks. In conclusion, the Woseco task represents a promising contribution to creativity research for measuring cognitive processes relevant for scientific creativity.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.
Source provenance
- europepmc
- last seen: 2026-05-20T01:45:00.602351+00:00