Methods and Intelligent Models for Automated Knowledge Assessment and Academic Integrity Analysis in Digital Learning Platforms
This paper investigates intelligent models and methods for automated knowledge assessment and academic integrity analysis in digital educational platforms. The rapid spread of generative artificial intelligence tools has created new challenges for existing e-learning systems, which are primarily oriented toward result-based evaluation rather than process analysis. An integrated approach combining behavioral, textual, and statistical features of student learning activity has been proposed.