Idea Generation and Goal-Derived Categories
- Richard Hass, College of Humanities and Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, United States
- Colin Long, College of Humanities and Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, United States
- Joshua Pierce, College of Humanities and Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, United States
AbstractSemantic search and retrieval of information plays an important role in creative idea generation. This study was designed to examine how semantic and temporal clustering varies when asking participants to generate ideas about uses for objects compared with generating members of goal-derived categories. Participants generated uses for three objects: brick, hammer, picture frame, and also generated members of the following goal-derived categories: things to take in case of a fire, things to sell at a garage sale, and ways to spend lottery winnings. Using response-time analysis and semantic analysis, results illustrated that all six prompts generally led to exponential cumulative response-time distributions. However, the proportion of temporally clustered responses, defined using the slope-difference algorithm, was higher for goal-derived category responses compared with object uses. Despite that, overall pairwise semantic similarity was higher for object uses than for goal derived exemplars. The effect of prompt on pairwise semantic similarity is likely the result of context-dependency of exemplars from goal-derived categories. However, the current analysis contains a potential confound such that special instructions to give ``common and uncommon'' responses were provided only for the object-uses prompts. The confound is likely minimal, but future work is necessary to verify that these results would hold when the confound is removed.
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