一个应用统计数据集用于人类与人工智能生成的答案分类
Md Shahidul Salim1, Sk Imran Hossain1
1Khulna University of Engineering & Technology, Khulna 9203, Bangladesh.
Data in brief
|July 4, 2024
概括
创建了一个由4231个问答对组成的新数据集,用于训练人工智能 (AI) 探测器进行应用统计学任务. 这有助于教师识别人工智能生成的文本,并确保学术完整性.
科学领域:
- 统计 统计 统计 统计
- 计算机科学 计算机科学
- 教育教育教育教育教育教育.
背景情况:
- 大型语言模型 (LLM) 越来越多地被学生用于作业.
- 检测人工智能生成的文本对教师来说是个挑战,特别是在专业领域.
- 现有的AI检测工具缺乏特定领域的准确性.
研究的目的:
- 开发一个数据集,用于训练应用统计学中的AI检测工具.
- 解决对特定领域AI文本真实性验证的需求.
- 创建一个框架来收集其他领域的类似数据集.
主要方法:
- 收集了来自领域专家的116个应用统计学问题.
- 设计了一个学生答案收集的框架.
- 收集了100个学生的回答和同样多的ChatGPT生成的答案.
- 创建了一个由4231个问答对组成的数据集.
主要成果:
- 成功创建了一个用于应用统计人工智能检测的新型数据集.
- 该数据集包含人类生成和人工智能生成的文本.
- 数据准备框架可适应其他领域.
结论:
- 该数据集将有助于开发和对应用统计的AI检测工具进行基准测试.
- 该研究提供了一个创建特定领域AI检测数据集的方法.
- 这项工作支持AI文本生成时代的学术诚信.
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