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Specifics of Interrelations among Emotional, Personal and Intellectual Characteristics in Preschool Children: Data Mining

机译:学龄前儿童情感,个人和智力特征之间的相互关系的细节:数据挖掘

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The relationships of intellectual signs with self-esteem and emotional characteristics of 5-7-year old preschoolers are studied. For this purpose, traditional methods of diagnostics were used: "Method of Express Diagnostics of Intellectual Abilities (MEDIA)", "Ladder", "House. Tree. Man", "Choose the right person". The research was based on preschool institutions in Moscow and Cheboksary. Correlation, factor analysis, and artificial neural networks were used to process psychological testing data and evaluate the relationships between different psychological indicators. It is shown that even with a small sample of respondents, such a comprehensive data mining allows detecting new features in the conditions when the results of testing of preschool children have integer scales with a limited range of values. Some gender features in intellectual indicators and their interrelations with emotional and personal characteristics are revealed. On the basis of quantitative data analysis, the most significant subtests and symptom complexes from the used methods were identified. The results obtained allow demonstrating the possibilities and advantages of using artificial neural networks for processing psychodiagnostic data. The tools used are available to practical psychologists because they are part of most modern software packages for statistical data processing.
机译:研究了具有5-7岁学龄前儿童自尊和情感特征的知识迹象的关系。为此目的,使用了传统的诊断方法:“智力能力的表达诊断方法(媒体)”,“梯子”,“房子。树。男人”,“选择合适的人”。该研究是基于莫斯科和切博的学龄前机构。相关,因子分析和人工神经网络用于处理心理测试数据,评价不同心理指标的关系。结果表明,即使有一个小的受访者样本,这种综合数据挖掘允许在幼儿园的测试结果具有有限的值范围内的整数尺度时检测到条件中的新功能。揭示了智力指标中的一些性别特征及其与情感和个人特征的相互关系。在定量数据分析的基础上,确定了来自二手方法的最显着的子阶和症状复合物。得到的结果允许展示使用人工神经网络来加工精神诊断数据的可能性和优点。使用的工具可用于实用心理学家,因为它们是统计数据处理最多的最现代软件包的一部分。

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