数字自我效能作为高等教育教师专业实践中的生成式人工智能使用框架的基础
Digital self-Efficacy as a foundation for a generative AI usage framework in faculty's professional practices
AI总结：
本研究提出一个基于数字自我效能的生成式人工智能使用框架，通过验证三维量表和三种用户档案，为高等教育教师提供个性化支持和适应性配置。
摘要：
本研究探讨了数字自我效能在高等教育教师使用生成式人工智能（GAI）中的作用。基于班杜拉的社会认知理论和弗利希的使用框架概念，我们的研究考察了数字自我效能水平与GAI使用档案之间的关系。对265名教师的调查确定了三种用户档案（投入型、反思保留型、批判抵制型）并验证了三维数字自我效能量表。结果表明，自我效能档案与GAI获取模式之间存在显著关联。基于这些发现，我们提出一个差异化使用框架，整合四种社会技术配置、适应自我效能档案的获取轨迹以及个性化的机构支持机制。
英文摘要：
This research explores the role of digital self-efficacy in the appropriation of generative artificial intelligence (GAI) by higher education faculty. Drawing on Bandura's sociocognitive theory and Flichy's concept of usage framework, our study examines the relationships between levels of digital self-efficacy and GAI usage profiles. A survey of 265 faculty members identified three user profiles (Engaged, Reflective Reserved, Critical Resisters) and validated a three-dimensional digital self-efficacy scale. Results reveal a significant association between self-efficacy profiles and GAI appropriation patterns. Based on these findings, we propose a differentiated usage framework integrating four sociotechnical configurations, appropriation trajectories adapted to self-efficacy profiles, and personalized institutional support mechanisms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
