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比古德诺夫更好?评估用于在儿童绘画中寻找诊断结构的新计算技术。

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

作者信息

Jensen Clint A, Rogers Timothy T, Rosengren Karl S

机构信息

Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA.

Department of Brain and Cognitive Science and Department of Psychology, University of Rochester, Rochester, NY, USA.

出版信息

Mem Cognit. 2025 Jan;53(1):200-218. doi: 10.3758/s13421-024-01557-0. Epub 2024 Apr 26.

Abstract

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.

摘要

在1926年出版的《通过绘画测量智力》一书中,弗洛伦斯·古德伊纳夫开创了对儿童人物画进行定量分析的方法,将其作为评估儿童认知发展的一种工具。这项具有影响力的工作开启了一项广泛的认知评估事业,一直延续至今,大多数临床医生和研究人员都采用古德伊纳夫发明的基于清单的评分方法的变体。然而,最近利用认知科学中的计算创新开展的研究表明,人物画所具有的结构比基于清单的方法所能捕捉到的要丰富得多。当前的这项研究使用这些当代工具来描述古德伊纳夫原始研究中的图像结构,然后评估这种结构是否携带了关于该早期研究中参与者的人口统计学和认知特征的信息。结果表明,当代方法无需专家培训且只需极少的人力,就能可靠地从100多年前生成的图像中提取有关参与者年龄、性别和智力的信息。此外,新的分析表明,绘画与心理能力之间的关系与古德伊纳夫极具影响力的方法所捕捉到的关系不同,这对当今认知评估中绘画的使用具有重要意义。

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