研究斯里兰卡教师教AI的自信度，发现情绪状态影响最大。
A Self-Efficacy Theory-based Study on the Teachers Readiness to Teach Artificial Intelligence in Public Schools in Sri Lanka
- 基于班杜拉自我效能理论，调查1300多名教师对AI教学的信心。
- 教师自我效能普遍偏低，受情绪和想象经验影响最显著。
- 适合关注教育AI培训的政策制定者和教研人员参考。
本研究探讨了斯里兰卡信息技术教师在中小学教授人工智能（AI）的准备度，聚焦于自我效能感。通过对超过1300名教师的问卷调查，采用基于班杜拉（Bandura）理论构建的量表评估其自我效能。通过偏最小二乘结构方程模型（PLS-SEM）分析发现，教师的自我效能水平较低，主要受与AI教学相关的情绪和生理状态以及想象体验的影响。掌握性经验的影响较弱，而替代性经验与言语说服均无显著作用。研究强调需采取系统性教师专业发展策略，考虑教师在AI专业知识与社会资源上的不足。建议未来研究从社会技术系统视角探索有效的AI教师培训路径。
原文摘要 · Abstract (English)
This study investigates Sri Lankan ICT teachers' readiness to teach AI in schools, focusing on self-efficacy. A survey of over 1,300 teachers assessed their self-efficacy using a scale developed based on Bandura's theory. PLS-SEM analysis revealed that teachers' self-efficacy was low, primarily influenced by emotional and physiological states and imaginary experiences related to AI instruction. Mastery experiences had a lesser impact, and vicarious experiences and verbal persuasion showed no significant effect. The study highlights the need for a systemic approach to teacher professional development, considering the limitations in teachers' AI expertise and social capital. Further research is recommended to explore a socio-technical systems perspective for effective AI teacher training.
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