大学学生对高等教育中的创造性艺术的学习意图:SEM-ANN对人类-AI共同创造因素的研究
1College of Fine Arts, Weinan Normal University, Weinan, 714099, China; Department of Industrial Design, Dong-A University, Busan, 49315, Republic of Korea.
Acta psychologica
|December 4, 2025
概括
大学的学生大学生.
科学领域:
- 艺术和设计教育教育教育教育
- 教育中的人工智能
- 人与计算机的交互
背景情况:
- 生成性AI越来越多地用于艺术和设计.
- 了解学生对生成艺术的学习意图对于高等教育至关重要.
- 这项研究解决了在生成艺术教育中需要理论指导的需求.
研究的目的:
- 探索影响大学生学习生成艺术的意图的因素.
- 为改革生成性艺术教育提供理论基础.
- 为学习意图开发一个多维因素预测模型.
主要方法:
- 一种混合分析,将部分最小平方结构方程建模 (PLS-SEM) 和人工神经网络 (ANN) 结合起来.
- 数据收集来自中国58所大学556份有效问卷.
- 分析了包括认知期望 (CE),学习期望 (LE),社会背景影响 (SCI),情感动机 (AM),人与人工智能共同创造体验 (HACE) 和道德责任意识 (ERA) 在内的因素.
主要成果:
- 情感动机 (AM) 和人类-人工智能共同创造体验 (HACE) 是影响学习意图的最重要因素.
- 伦理责任意识 (ERA),学习期望 (LE),认知期望 (CE) 和社会背景影响 (SCI) 也显示出相当大的影响.
- 预测模型表现出强大的预测能力,R2 = 66.3%和Q2 = 0.657.
结论:
- 教导创造性艺术应该优先考虑情感动机和人类-人工智能共同创造.
- 整合道德责任教育对于学生的学习至关重要.
- 清晰的学习路径可以增强创造性的艺术的吸引力,培养学生的意图和创新.
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