测量学生的人工智能能力:开发和验证综合教育心理学视角的多维尺度
Zubair Ahmad1, Almaas Sultana1, Nafilah Abdul Latheef1
1Qatar University Young Scientists Center (QUYSC), Qatar University, 2713, Doha, Qatar.
Acta psychologica
|August 28, 2025
概括
一个新的AI能力表 (AICS) 有效地衡量学生
科学领域:
- 教育技术
- 教育中的人工智能
- 心理测量
背景情况:
- 人工智能 (AI) 在K-12教育中的快速整合需要评估学生的AI能力.
- 联合国教科文组织的AI能力框架强调了AI能力的认知,情感,道德和技术方面.
- 现有的评估差距使教育工作者无法确保学生对人工智能驱动的学习环境的准备.
研究的目的:
- 开发和验证人工智能能力量表 (AICS),用于评估K-12学生的人工智能能力.
- 在四个方面实现人工智能能力:以人为中心的思维,人工智能道德,人工智能技术和应用以及人工智能系统设计.
主要方法:
- 这项研究涉及卡塔尔608名高中生.
- 一个多阶段的验证过程包括专家审查,因子分析 (EFA,CFA),可靠性测试 (Cronbach的alpha,复合可靠性) 和使用SEM的有效性评估.
- 使用结构方程建模 (SEM) 来分析人工智能能力维度之间的关系.
主要成果:
- 人工智能能力尺度 (AICS) 显示出强大的心理测量特性,证实了其有效性和可靠性.
- 研究结果显示,整体人工智能能力与学生对人工智能相关职业的兴趣之间存在显著的积极关联.
- 人工智能能力的四个概念维度得到了实证支持.
结论:
- 经过验证的AICS提供了一个强大的工具来评估学生在K-12教育中的AI能力.
- 该规模支持教育工作者,研究人员和政策制定者制定课程,针对性干预和基于证据的AI教育政策.
- 评估人工智能能力对于培养学生对人工智能的道德和知情参与至关重要.
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