USING CLASSTIME'S AI-BASED TESTING IN LEARNING OUTCOMES ASSESSMENT

Introduction. Artificial intelligence technologies are also widely used by educational platforms to improve learning efficiency and provide users with the most personalized experience. An example of a platform that uses the capabilities of artificial intelligence to organize the evaluation of students' knowledge and skills during online/offline studies is Classtime. The Ukrainian-language interface contributes to the platform's clarity and usability, and enables it to be quickly and productively integrated into the educational process, which is confirmed by a number of studies. Purpose. The purpose of this study is to identify the practical experience of using the Classtime platform artificial intelligence capabilities to evaluate the students' learning outcomes in informatics and engineering. Methods. The research used general scientific methods of scientific research – analysis, synthesis, comparison, specification, and generalization of scientific literature, systematization and generalization of the received information.Results. Special attention is paid to educational achievement assessment platforms that are integrated with artificial intelligence tools. The main reasons for this focus on AI tools are: the ability to automate many aspects of evaluation, including making tests, scoring responses, analyzing results and reporting on learner progress; the ability to analyze large data volumes of the students responses, to recognize trends and identify weak points in education; opportunities to create individualized tasks, taking into account a student level of knowledge, skills and needs. The students' responses to tests with open answers in the form of problems were analyzed to check the students' level of educational achievements in engineering disciplines. Classtime platform correctly identifies the correct students' answers, despite differences in their writing and use of synonymous concepts. Originality. Our practical experience of using the Classtimet artificial intelligence capabilities to assess the students' learning outcomes in informatics and engineering has confirmed the hope for solving the problems of checking open-ended tasks from a wide range of disciplines. Conclusions. The problem of evaluating students' educational achievements by digital means has been investigated. The artificial intelligence capabilities of the Classtime platform have been tested for evaluating the students' learning outcomes in informatics and engineering. The key functional components that provide the means of artificial intelligence in educational achievement evaluation platforms are highlighted: automation of evaluation, analysis of answers, individualization of tasks.