An Intelligent System to Automate the Detection of Online Cheating Activities using AI and Context Aware Techniques

Qinyuhan Zhao1, Mingze Gao2 and Yu Sun3, 1Pacific Academy Irvine, USA, 2University of California, USA, 3California State Polytechnic University, USA; Qinyuhan Zhao1, Mingze Gao2 and Yu Sun3, 1Pacific Academy Irvine, USA, 2University of California, USA, 3California State Polytechnic University, USA

An Intelligent System to Automate the Detection of Online Cheating Activities using AI and Context Aware Techniques

Authors

Qinyuhan Zhao¹, Mingze Gao² and Yu Sun³, ¹Pacific Academy Irvine, USA, ²University of California, USA, ³California State Polytechnic University, USA

Abstract

In the environment of online courses and online exams, cheating in online courses is prevalent [1]. To better ensure fairness in exams, schools and educational institutions need to use technology to detect and deter cheating [2]. Starting from practical application, this paper discusses 3 different methods to detect cheating behavior, and proposes a new way. for online exam supervision.

Keywords

Machine Learning, Audio Detection, Context-Aware.

CS&IT Conference Proceedings

An Intelligent System to Automate the Detection of Online Cheating Activities using AI and Context Aware Techniques