免费绘画可以预见书写困难吗?一项纵向研究

L. Dui, Simone Toffoli, Christopher Speziale, C. Termine, Matteo Matteucci, Simona Ferrante
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引用次数: 2

摘要

书写困难需要尽早解决,以避免在学校和日常生活中给孩子带来一些问题,但书写困难的诊断不能在书写成熟之前进行。为了解决这个问题,我们假设对识字前阶段的绘画进行分析可以预测数年后会出现的书写问题。我们设计了一项为期三年的纵向研究,从幼儿园的最后一年到二年级结束,有两个目的:(1)纵向评估绘画特征的演变,(2)了解识字前收集的特征是否可以预测未来的书写问题。因此,在可用的五个时间点之间对特征进行了统计显著性变化的测试,以评估它们在时间上的纵向演变。此外,我们训练机器学习模型来选择识字前收集的最重要的特征,并评估它们的预测能力,在二年级结束时评估书写困难的风险。202名儿童完成了这项纵向研究。我们发现81%的特征对纵向成熟度敏感,并且在精确召回率曲线为0.72的加权面积下可以预测困难。这是朝着早期干预书写问题迈出的一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Can Free Drawing Anticipate Handwriting Difficulties? A Longitudinal Study
Handwriting difficulties need to be addressed early to avoid several problems to children, both at school and in everyday life, but dysgraphia diagnosis cannot be performed before handwriting maturation. To solve this issue, we hypothesize that the analysis of drawings produced in a pre-literacy stage can predict handwriting problems that will occur years later. We designed a three-year longitudinal study from the last year of kindergarten to the end of second grade with two aims: (1) to longitudinally assess the evolution of drawing features, and (2) to understand if the features collected at pre-literacy can predict future handwriting problems. Hence, features were tested for statistically significant variation among the five time points available to assess their longitudinal evolution in time. Moreover, we trained machine learning models to select the most important features collected at pre-literacy and to assess their predictive capabilities, with dysgraphia risk assessed at the end of second grade. 202 children completed the longitudinal study. We found that 81% of the feature was sensitive to longitudinal maturation and that it is possible to predict the difficulties with a weighted area under the precision-recall curve of 0.72. This is a step forward towards an early intervention for handwriting problems.
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