Development of a model of predictive analytics of financial income from educational activities based on the digital footprint of students
Abstract. The article examines the role of the use of digital technologies in educational organizations. A model for assessing professional skills and competencies as an automated point-rating system is being developed. A variant of the point-rating system (PRS) functioning is proposed, factor variables determining the student`s summary rating are determined, and a graphical model of a neural network is presented that allows predicting financial results from the implementation of educational activities at the university.
Keywords: individual educational trajectory, digital technologies, student`s digital twin, intelligent digital assistant, digital footprint
Highlights:
♦ predictive analytics is one of the tools for improving the educational performance due to the possibility of corrective influence on the student at the early stages of the educational period;
♦ artificial neural networks allow to build a flexible predictive analytics model that receives digital footprint data from automated tools accompanying the educational process to predict personalized learning outcomes;
♦ forecasting academic performance allows not only to increase the efficiency of the educational process, but also to estimate the planned financial income from educational activities for a period of up to one year.
Dmitry N. Frantasov, Anna V. Balanovskaya, Evgenia G. Repina, Elena V. Voronina - Samara State University of Economics, Samara, Russia