During the learning process in any field, testing and monitoring the knowledge of students or other learners is an essential part. The purpose of this research was to develop an information system (web platform) that simplifies the offline test grading process using optical character recognition technologies powered by machine learning algorithms. The object of this research is the processes and functionality involved in creating an information system for the automated grading and evaluation of offline tests. The developed system can recognize handwritten text from photos, create an array of responses, and compare them to the answers provided by the teacher. This approach significantly reduces the time teachers spend on grading tests. For user convenience, a minimalist interface was created, granting access to all main system functions with intuitive controls. A detailed description of the developed algorithms and machine learning models is provided.
