调查候选教师对各种学科的生成人工智能和人工智能素养的接受程度之间的相关性
Berker Kurt1, Gözdegül Arık Karamık2, Ali Özkaya2
1Department of Turkish Language and Social Sciences Education, Faculty of Education, Akdeniz University, Antalya, Türkiye.
PloS one
|March 5, 2026
概括
未来的教师表现出不同程度的生成人工智能 (GenAI) 接受和人工智能识字 (AIL). 诸如部门,年级和人工智能工具使用等因素显著影响这些水平,突出了针对性人工智能教育的需要.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 教师培训 培训教师培训
背景情况:
- 生成型人工智能 (GenAI) 正在迅速发展,需要教育工作者对其接受度和人工智能素养 (AIL) 的理解.
- 未来的教师将成为未来的教学工作人员,他们的AI能力对于将技术纳入课堂至关重要.
- 现有的研究往往侧重于一般的人工智能,更不重视具体的GenAI及其对教师教育的影响.
研究的目的:
- 在未来的教师中评估生成人工智能 (GenAI) 的接受度和人工智能识字 (AIL) 的水平.
- 确定影响GenAI接受和AIL的人口和使用相关变量.
- 探索有助于在教师教育中接受GenAI和AIL的定性因素.
主要方法:
- 采用了一种解释性的顺序混合方法方法,将定量和定性数据结合起来.
- 从723名潜在教师那里收集了定量数据,使用GenAI接受度和AIL的比例表,以及人口统计信息.
- 通过采访,从48名未来教师那里获得的定性数据被用来详细阐述定量发现,并根据主题进行分析.
主要成果:
- 根据性别或日常互联网使用情况,GenAI的接受程度并没有显著差异,但根据部门,年级,使用的AI工具和自我认知的熟练程度而有所不同.
- 人工智能素养 (AIL) 显示出基于性别,部门,年级,工具使用和熟练程度的显著差异,接受人工智能培训的人得分更高.
- 影响GenAI接受的关键因素包括日常使用,问题解决,学习应用程序和任务效率,而AIL受到了理解AI的重要性,伦理和特定AI概念 (如机器学习) 的影响.
结论:
- 未来教师的GenAI接受和AIL受到个人,学术和技术因素的结合的影响.
- 有针对性的培训和课程开发对于提高未来教育工作者对GenAI的接受度和AIL的接受度至关重要.
- 了解这些影响因素对于开发有效的战略来将AI整合到教师教育计划和K-12课堂中至关重要.
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