DEVELOPMENT OF INTELLIGENT SYSTEMS FOR AUTOMATIC ASSESSMENT OF STUDENTS' ACADEMIC ACHIEVEMENTS

Aims: to analyse the development of artificial intelligence systems for automatic assessment of students' learning achievements. Methodology: to achieve this goal, the scientific methods of analysis and synthesis, content analysis, SWOT analysis, comparison, and typology were used. Results: it has been established that among the key advantages is a significant increase in the objectivity of the assessment of students' knowledge and skills. It is important to consider the acceleration of the process of checking the results, which saves time and effort for teachers. Another important advantage is the provision of real-time feedback during assessment. Scientific novelty: It has been established that one of the major problems is the possibility of bias and inequality in the educational system. Given that intelligent systems are based on certain algorithms, any bias or false information in the initial data can lead to biased results. Additional challenges include the excessive mechanisation of the assessment process, which does not always allow for the individual characteristics of each student, as well as ensuring appropriate protection of personal data. Conclusions: Intelligent student assessment systems are a powerful tool in countering corruption schemes in the educational system, especially in developing countries.