THEORETICAL AND METHODOLOGICAL FOUNDATIONS OF ASSESSING SCHOOL STUDENTS’ ACADEMIC ACHIEVEMENTS BASED ON ARTIFICIAL INTELLIGENCE
Abstract
This study analyzes the theoretical and methodological foundations of assessing school students' academic achievements based on artificial intelligence. In the context of the modern digital educational environment, improving the assessment process and enhancing its accuracy, transparency, and efficiency is considered a pressing issue. From this perspective, the study explores the potential of artificial intelligence technologies in the educational process and the ways of integrating them into the assessment system. The work scientifically substantiates approaches aimed at the comprehensive assessment of students' individual characteristics, cognitive activity, and learning outcomes. Furthermore, the principles, criteria, and indicators for developing assessment models based on artificial intelligence are defined. Within the framework of the study, mechanisms of adaptive assessment, automated testing, forecasting, and personalized learning support are analyzed. As a result, an innovative model for assessing students’ academic achievements in school education is proposed, and its theoretical and practical significance is justified. This approach serves to improve the quality of education, optimize the learning process, and shape the individual development trajectory of students.
Keywords
artificial intelligence, digital education, assessment of academic achievements, automated testing, individualized education, assessment criteria, quality improvement in education, forecasting, digital learning environment, innovative pedagogical technologies..How to Cite
References
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