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在答案表上无监督的光学标记识别,用于大规模打印的多选项测试
Yahir Hernández-Mier1, Marco Aurelio Nuño-Maganda1, Said Polanco-Martagón1
1Intelligent Systems Department, Polytechnic University of Victoria, Ciudad Victoria 87138, Mexico.
本研究介绍了一款用于自动光学标记识别 (OMR) 的桌面应用程序,以得分多选项测试. 该系统显著减少了分级时间,并提高了准确性,而不是手动评分.
科学领域:
- 计算机科学 计算机科学
- 图像处理 图像处理
- 教育技术的教育技术
背景情况:
- 手动评分多选项测试是耗时的,容易出现错误.
- 现有的光学标记识别 (OMR) 算法在扫描答案表中的现实世界的变化中扎.
- 对大规模评估的评分过程的自动化对于效率至关重要.
研究的目的:
- 开发和评估一个桌面应用程序,用于多选择题 (MCQ) 答案表的光学标记识别 (OMR).
- 提高评分标准化测试的速度和准确性.
- 为运营商提供一个用户友好的界面来管理和分析考试结果.
主要方法:
- 编制了来自墨西哥塔马乌利帕斯州考试的6029张扫描答案表 (564,040个四选项答案) 的数据集.
- 开发了一种图像处理模块,用于从数字化答案表中提取答案.
- 创建了一个操作员界面来选择文件和结果表格.
主要成果:
- OMR系统在评分整个考试时实现了96.15%的准确性,没有错误.
- 该系统正确分类了99.95%的个别四选项答案.
- 自动评分平均每张答案表1.04秒,而手动评分2分钟.
结论:
- 开发的OMR桌面应用程序提供了一个高度准确和高效的解决方案,用于评分多项选择测试.
- 该系统在速度和精度方面明显优于手动分级.
- 这项技术有可能简化大规模的教育评估.
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