验证ChatGPT使用量表:在研究生中验证心理特征和因素结构
Mohamed Nemt-Allah1, Waleed Khalifa2, Mahmoud Badawy2
1Faculty of Education, Al-Azhar University, Dakahlia, Egypt. mohamednamatallah.2026@azhar.edu.eg.
BMC psychology
|September 24, 2024
概括
一个新的尺度衡量了研究生如何使用ChatGPT进行学术写作,任务支持和依赖. 这种经过验证的工具有助于理解AI.
科学领域:
- 教育技术的教育技术
- 高等教育研究 高等教育研究
- 教育中的人工智能
背景情况:
- 学术界越来越多地使用ChatGPT,这引发了人们对学习和诚信的担忧.
- 需要一个心理测量健全的仪器来评估在研究生中使用ChatGPT.
研究的目的:
- 为研究生开发和验证一个全面的ChatGPT使用量表.
- 评估ChatGPT在高等教育中的多维性质.
主要方法:
- 与443名研究生进行的横截面调查.
- 探索性因素分析 (EFA) 和确认性因素分析 (CFA) 在39项尺度上.
- 使用克伦巴赫的alpha和麦当劳的omega评估了内部一致性.
主要成果:
- EFA确定了一个三要素结构:学术写作辅助,学术任务支持和依赖和信任.
- CFA证实了15项尺度的结构与可接受的适应指数.
- 该尺度表现出良好的内部一致性和趋同有效性.
结论:
- 经过验证的ChatGPT使用量表是评估研究生对人工智能工具的参与度的可靠和有效工具.
- 提供了对人工智能辅助学术实践及其对研究生教育的影响的见解.
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