通过DeepSeek了解中国大学生继续学习的意图:一个集成的TAM-SOR模型
1School of Law, Yunnan Minzu University, Kunming, Yunnan Province, China.
Acta psychologica
|November 16, 2025
概括
大学的学生大学生.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 高等教育 高等教育
背景情况:
- 中国的高等教育正在通过像DeepSeek这样的AI工具进行现代化.
- 大学学生正在转向智能学习方法.
- 现有的人工智能研究忽视了学生学习中的关键情感和动机因素.
研究的目的:
- 分析影响大学生采用DeepSeek的情感感知.
- 调查推动在高等教育中持续使用生成AI的因素.
- 识别人工智能学习平台采用的障碍和促进因素.
主要方法:
- 结合技术接受模型 (TAM) 和刺激-生物体-反应 (SOR) 模型.
- 通过在线问卷调查收集了476个有效的答案.
- 分析了情感感知及其对人工智能工具使用的影响.
主要成果:
- 感知到的情绪和持续的动机是采用生成性AI学习工具的关键.
- 工具的方便性提高了实用性,可用性和积极的情绪.
- 学习习惯一致的设计增加了控制和快乐,推动了持续的使用.
- 高自我效率通过培养与AI功能的情感联系来降低使用障碍.
结论:
- 情感感知和持续的动机对于大学生采用人工智能学习技术至关重要.
- 方便性,可用性和与习惯一致的设计促进了积极的情绪和持续的使用.
- 自我有效性在克服生成性AI学习平台的采用障碍方面发挥着至关重要的作用.
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