Possibilities of Application of Adaptive Knowledge Testing Using Artificial Neural Networks in Training Economics Students

In line with the advancement of information technology, we are witnessing the development of adaptive knowledge testing, which presents a computerized system for evidence-based testing and assessment of learning outcomes. This system is distinguished by high efficiency owing to the optimization of generation procedures and the presentation and assessment of the results of adaptive tests. The study aims to evaluate the application of adaptive knowledge testing through artificial neural networks on the improvement of the level of training in economics students. A pedagogical experiment was conducted during the second semester of the 2022-2023 academic year at three universities on 288 3rd-year students. The authors developed assessment materials for adaptive knowledge testing with the use of artificial neural networks and developed and carried out the procedure of adaptive knowledge testing. Based on the dynamics of students' success indicators, conclusions were drawn about the efficiency of adaptive testing using artificial neural networks. The results of the pedagogical experiment support the hypothesis that the quality of economics students' training is significantly improved as a result of implementing adaptive knowledge testing using artificial neural networks.