对有特殊需求的个人进行快速有效的评估形式优化和预测模型
Bilal Baris Alkan1, Muhammet Kumartas2, Serafettin Kuzucuk3
1Measurement and Evaluation in Education, Faculty of Education, University of Akdeniz, Dumlupınar Boulevard, Campus, Antalya, 07058, Turkey. bbalkan@akdeniz.edu.tr.
BMC psychology
|April 23, 2025
概括
本研究确定了用于对儿童 (6-12岁) 特殊需求进行分类的关键心理评估项目. 开发了机器学习模型,以简化诊断过程,为专家和个人节省时间.
科学领域:
- 儿童心理学 儿童心理学
- 发展心理学 发展心理学
- 教育心理学教育心理学
背景情况:
- 准确的特殊需求分类对于有效的干预至关重要.
- 当前的心理评估表格可能包含多余的项目,影响效率.
- 需要优化评估工具来加快诊断过程.
研究的目的:
- 确定心理评估表格中的有效项目,以对特殊需求进行分类.
- 开发基于机器学习的预测模型,用于特殊需求诊断.
- 优化评估表格,以实现更快,更有效的评估.
主要方法:
- 分析了来自1814名 (6-12岁) 儿童的心理评估请求表格.
- 机器学习技术的应用以开发预测模型.
- 根据心理和发育评估对个人进行分类.
主要成果:
- 确定特定的心理评估项目,这些项目对于特殊需求的分类非常有效.
- 开发新的机器学习模型,证明预测准确性.
- 对效率的优化评估方法的验证.
结论:
- 某些项目显著提高了特殊需求分类的准确性.
- 机器学习为开发高效的诊断工具提供了一个有希望的途径.
- 优化评估表格可以提高资源配置,减少评估时间.
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