Abstract:

Currently, the need for trained engineering personnel is growing rapidly, but is not sufficiently supported by technical universities. One of the main reasons is the limited scalability of the efforts of qualified faculty when using traditional forms of education. The solution to this problem is the use of new educational technologies and the digitalization of the educational process. The most of educational digital platforms uses traditional methods to assess quality of transfer the teacher’s knowledge to the student’s competence. These methods are based on automatic verification that checks only the answer.

In modern conditions, there is a tendency to use a mobile device (smartphone, tablet, etc.) as the main agent for all information transactions. The training process is no exception: almost all types of training sessions can be conducted through a mobile device, and at a convenient time for the participants. We suggest new educational digital system that can be used on mobile devices. Our tools allow you to check not only the answer, but also the solution step-by-step, indicating to the student, where he made a mistake, if the decision is not correct. A mobile device allows you to record all the actions performed in the educational process: lectures, questions and answers, problem solving process, etc. In this way, comprehensive big data can be collected while maintaining the confidentiality required by law. Processing the collected big data using machine learning methods allows you to objectively assess the real performance, which ensures the transition from the educational process based on attendance to the educational process based on performance.

As a result, our project allows you to assess the competence of students on the basis of a comprehensive automatic verification of solutions step-by-step. This leads to an increase in the productivity of teachers and an increase in the number of trained engineering personnel.

Keywords:

Education, artificial intelligence, big data, automatic verification, knowledge representation, ontologies.