AI辅助识别考生是否看屏幕外，提升在线监考效率。
AI-assisted Gaze Detection for Proctoring Online Exams
- 用AI分析视频帧，自动定位考生视线相似的片段。
- 用户研究显示系统显著降低监考疲劳度。
- 适合需要人工复核的远程考试监考场景。
对于高风险的在线考试，检测潜在违规行为对保障考试安全至关重要。本研究探讨检测考生是否视线离开屏幕的任务，因为这种行为可能暗示其在查阅外部资源。在异步监考中，考试视频会被记录并由监考人员审查。然而，当考试时长较长时，监考人员逐帧观看视频以确定考生视线偏离的具体时刻会非常繁琐。本文提出一种AI辅助的注视检测系统，允许监考人员在不同视频帧间快速导航，并发现考生视线方向相近的帧。该系统使监考人员更高效地识别可疑时刻。我们还设计了一个评估框架，用于对比人工监考与纯机器学习监考的效果，并开展用户研究以收集监考人员反馈，旨在证明系统的有效性。
原文摘要 · Abstract (English)
For high-stakes online exams, it is important to detect potential rule violations to ensure the security of the test. In this study, we investigate the task of detecting whether test takers are looking away from the screen, as such behavior could be an indication that the test taker is consulting external resources. For asynchronous proctoring, the exam videos are recorded and reviewed by the proctors. However, when the length of the exam is long, it could be tedious for proctors to watch entire exam videos to determine the exact moments when test takers look away. We present an AI-assisted gaze detection system, which allows proctors to navigate between different video frames and discover video frames where the test taker is looking in similar directions. The system enables proctors to work more effectively to identify suspicious moments in videos. An evaluation framework is proposed to evaluate the system against human-only and ML-only proctoring, and a user study is conducted to gather feedback from proctors, aiming to demonstrate the effectiveness of the system.
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