A key challenge in creativity research is assessment.
Objectively scored tests of creativity are highly reliable and valid but are slow and expensive to administer and score. As a result, many creativity researchers default to faster self-report measures of creativity, however, there are obvious weaknesses associated with both approaches. Recent research has begun to explore the use of computational approaches to address these limitations. This presentation will present research demonstrating that algorithms can assess creativity as accurately as human judges but with quicker speeds and at a fraction of the cost. Thus addressing the weaknesses associated with assessment and demonstrating the practicality of automated creativity assessment.
Project Lead: Dr. Rebecca Marrone
