个人创新力,自我效能和对媒体学生人工智能采用感知风险的配置效应
Yanling Lan1, Sihang Liu1, Hao Chen2
1School of Film and Communication, Xiamen University of Technology, Xiamen, China.
Scientific reports
|January 19, 2026
概括
媒体学生的生成人工智能 (G-AI) 采用受到个人创新和AI自我效能的影响. 感知到的有用性,易用性和风险共同塑造了AI的行为意图,揭示了不同的采用途径.
科学领域:
- 媒体研究 媒体研究
- 教育技术的教育技术
- 人工智能的人工智能
背景情况:
- 生成型人工智能 (G-AI) 正在改变媒体行业和高等教育课程.
- 未来的媒体专业人士需要人工智能思维和数字智能技能.
- 关于媒体学生采用人工智能技术的知识差距存在.
研究的目的:
- 扩展技术接受模型 (TAM) 以了解媒体学生的AI采用.
- 将个人创新能力,人工智能自我效能和感知风险纳入一个全面的模型.
- 确定影响AI行为意图的关键决定因素和途径.
主要方法:
- 在588名媒体学生中进行调查.
- 使用部分最小平方结构方程建模 (PLS-SEM) 进行数据分析.
- 使用模糊集定性比较分析 (fsQCA) 的分析.
主要成果:
- 个人创新能力和人工智能自我有效性对感知到的实用性和易用性产生了积极的影响.
- 感知到的有用性和易用性是AI行为意图的关键调解因素.
- 感知风险负面地调节了感知易用性和AI行为意图之间的关系.
- 人工智能行为意图是由交叉因素决定的,形成自动驱动的,以有效性为导向的和耐风险的途径.
结论:
- 该研究通过整合人工智能采用心理和风险构造来推进TAM.
- 研究结果提供了对媒体学生中人工智能采用的驱动因素的理论见解.
- 可以制定实用策略,以提高人工智能能力在媒体教育.
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