A machine learning assistant for detecting fraudulent activities in synchronous online programming exams.

ABSTRACT: The rapid expansion of online learning has made education more accessible but has also introduced significant challenges in maintaining academic integrity, particularly during online exams. For certain types of exams, students are prohibited from connecting to the Internet to prevent them from accessing unauthorized resources, utilizing generative artificial intelligence tools, or engaging in other forms of cheating. However, in online exams, students must remain connected to the Internet. Most existing online proctoring systems rely on various devices to monitor students' actions and environments during the exam, focusing on tracking physical behavior, such as facial expressions, eye movements, and the presence of unauthorized materials, rather than analyzing the students' work within the

SUBMITTER: Ortin F 

PROVIDER: S-EPMC12453727 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature