ACADEMIC ASSESSMENT PARAMETERS AND CRITERIA IN THE AGE OF ARTIFICIAL INTELLIGENCE

Abstract

This article examines the impact of artificial intelligence technologies on the process of assessing student knowledge in higher education and addresses the issue of developing new criteria. The study analyses the shortcomings of traditional assessment methods, evaluates the effectiveness and limitations of AI detection instruments, and proposes new process-oriented parameters grounded in current pedagogical scholarship. The developed criteria serve to ensure academic justice and to objectively measure students' critical thinking, analytical reasoning, and prompt engineering skills. The findings suggest that a hybrid assessment model — one that values the process of knowledge construction rather than the final textual product alone — represents the most educationally defensible response to the challenges posed by generative artificial intelligence in higher education