Research and Development of Machine Learning Methods and Neural Network Architectures for Usage in the Field of Verification
Global trends in the digitalization of education require the transfer of a significant share of the educational process to digital educational environments with automatic verification of the tasks completed by students. The downside of automatic verification is that students use other people's solutions in their answers, passing them off as their own. This article discusses the problem of automatic and semi-automatic detection of borrowings on the example of passing solutions in programming workshops. As an approach to the study, the path of constructing predictive models of the probability of borrowing was chosen. We studied the applicability of deep machine learning methods to solving the problem of detecting borrowing, and also considered a number of heuristic techniques designed to improve the accuracy and expand the scope of using the constructed deep models.