Better than Goodenough? Evaluating new computational techniques for finding diagnostic structure in children's drawings

MEMORY & COGNITION(2024)

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摘要
In her 1926 book Measurement of Intelligence by Drawings, Florence Goodenough pioneered the quantitative analysis of children's human-figure drawings as a tool for evaluating their cognitive development. This influential work launched a broad enterprise in cognitive evaluation that continues to the present day, with most clinicians and researchers deploying variants of the checklist-based scoring methods that Goodenough invented. Yet recent work leveraging computational innovations in cognitive science suggests that human-figure drawings possess much richer structure than checklist-based approaches can capture. The current study uses these contemporary tools to characterize structure in the images from Goodenough's original work, then assesses whether this structure carries information about demographic and cognitive characteristics of the participants in that early study. The results show that contemporary methods can reliably extract information about participant age, gender, and mental faculties from images produced over 100 years ago, with no expert training and with minimal human effort. Moreover, the new analyses suggest a different relationship between drawing and mental ability than that captured by Goodenough's highly influential approach, with important implications for the use of drawings in cognitive evaluation in the present day.
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关键词
Human figure drawing (HFD),Convolutional neural networks (CNN),Children's drawings,Child development,Intelligence
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