Don't Throw the "Bad" Ideas Away! Multidimensional Top Scoring Increases Reliability of Divergent Thinking Tasks

Scoring divergent thinking tasks opens multiple avenues and possibilities-decisions researchers have to make. While some scholars postulate that scoring should focus on the best ideas provided, the measurement of the best responses (e.g., "top scoring") comes along with challenges. More specifically, compared to the average quality across all responses, top scoring uses less information-the "bad" ideas are thrown away-which decreases reliability. To resolve this issue, this article introduces a multidimensional top-scoring approach analogous to linear growth modeling which retains information provided by all responses (best ideas and "bad" ideas). Across two studies, using both subjective human ratings and semantic distance originality scoring of responses to over a dozen divergent thinking tasks, we demonstrated that Maximum (the best idea) and Top2 Scoring (two best ideas) could surpass typically applied average scoring in measurement precision when the "bad" ideas' originality is used as auxiliary information (i.e., additional information in the analysis). We thus recommend retaining all ideas when scoring divergent thinking tasks, and we discuss the potential this new approach holds for creativity research and practice.