Automated ai-based proctoring for online testing in e-learning system

Oleh Shkodzinsky, Mykhailo Lutskiv
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Abstract

Based on the analysis of existing on the market algorithmic solutions for identity verification during knowledge control in electronic learning systems, the requirements for the target system were formed. The main algorithms and approaches to the detection and recognition of faces were considered, as a result of which an effective combination of algorithms was chosen. The system of photo fixation and identity verification during knowledge control in LMS ATutor was designed and implemented. Its effectiveness was verified on the basis of a sample of test passes during its work in the real conditions of the educational process. Conclusions were made regarding the feasibility of implementation.
基于人工智能的在线考试自动监考
在分析电子学习系统知识控制过程中现有的身份验证算法解决方案的基础上,提出了目标系统的需求。分析了人脸检测与识别的主要算法和方法,选择了一种有效的算法组合。设计并实现了LMS ATutor知识控制过程中的照片固定与身份验证系统。在教育过程的实际条件下,通过一个测试样本来验证其有效性。对实施的可行性作出了结论。
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