!这是一个很棒的节目! 情境中的认知能力:一种创新的多模式框架,用于实时分析压力和社会情感功能
Rony Moortgat1, Pieter Verbeke2, Athur d'Hooge3
1Bachelor of Education in Primary Education (BALO), Howest University of Applied Sciences, (Howest), Brugge, Belgium; Multidisciplinary Institute for Teacher Education (MILO), Vrije Universiteit Brussel (VUB), Brussels, Belgium.
Acta psychologica
|November 21, 2025
概括
这项研究引入了一种新的人工智能驱动的方法,以全面评估学生的福祉,整合生理学,自我报告和调查数据. 它提供有针对性的干预措施,特别是对于认知强的学生 (CSS),以改善福祉和学术成功.
科学领域:
- 教育心理学教育心理学
- 教育中的人工智能
- 学生心理健康 学生心理健康
背景情况:
- 学生的福祉是多方面的,包括身体和心理健康.
- 目前的评估方法是分散的,未能捕捉到不同的学生经验.
- 认知能力强的学生 (CSS) 面临着独特的挑战,这些挑战往往被传统方法所忽视.
研究的目的:
- 开发一个整体的方法来评估学生的福祉使用多式联络数据.
- 确定影响学生福祉和学业成绩的关键模式.
- 为有针对性的干预提供可操作的见解.
主要方法:
- 一个整合生理测量 (心率变化,睡眠),自我报告和调查的框架.
- 利用文献综述和Delphi方法来开发框架.
- 强调对CSS特定压力因素的评估.
主要成果:
- 用大型语言模型 (LLM) 分析定性和定量数据进行情绪分析.
- 经典机器学习应用于综合生理和调查数据.
- 确定了压力和应对机制的模式,以提高福祉洞察力.
结论:
- 介绍了一个可扩展的,以道德为基础的方法,用于人工智能支持的学生福祉评估.
- 支持促进健康学生发展的干预措施.
- 具体地解决了认知强的学生 (CSS) 的需求.
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