DIDACTIC POSSIBILITIES OF ORGANIZING MEDICAL CHEMISTRY LABORATORY CLASSES AS A CONTINUOUS LEARNING CYCLE USING ARTIFICIAL INTELLIGENCE TOOLS

The thesis analyzes the current state of medical chemistry laboratory classes in medical higher education institutions and reveals the didactic possibilities of consistently supporting the class with artificial intelligence tools across the stages of "pre-laboratory preparation – laboratory performance – post-laboratory reflection – adaptive assessment". These possibilities are illustrated by a clinical case developed for the laboratory work "Buffer Solutions and Buffer Capacity".