大学生中的任务复杂性和人工智能依赖:认知负载,未来焦虑和任务动机的调解作用
Hanhui Li1, Fan Yang2, Jinpeng Liu3
1School of Foreign Languages, Fuzhou University of International Studies and Trade Fuzhou, Fujian, 350202, China.
BMC psychology
|March 5, 2026
概括
大学的学生大学生.
科学领域:
- 教育心理学教育心理学
- 人与计算机的交互
- 教育中的人工智能
背景情况:
- 了解学生对人工智能 (AI) 的依赖在高等教育中至关重要.
- 影响人工智能依赖的因素,如任务特征和心理状态,需要进行调查.
研究的目的:
- 为了研究任务复杂性和大学生对人工智能 (AI) 的依赖之间的关系.
- 探索认知负载,未来的焦虑和任务动机在这种关系中的调解作用.
主要方法:
- 在442名大学生中进行了一项调查.
- 收集了有关任务复杂性,人工智能依赖,认知负载,未来焦虑和任务动机的数据.
- 用结构方程建模来分析这些关联.
主要成果:
- 更高的任务复杂性与人工智能依赖度增加有积极的关联.
- 认知负载和未来的焦虑调解了任务复杂性和AI依赖之间的联系.
- 任务动机与人工智能依赖相反,特别是在复杂的任务中.
结论:
- 任务的复杂性通过认知负载,未来的焦虑和动机影响AI依赖.
- 教育策略应侧重于管理任务的复杂性,并支持学生对平衡人工智能使用的动机.
- 调查结果为课程设计提供了信息,以促进自主学习与AI集成一起.
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