TY - JOUR TI -

The development of a model for the personalized learning path using machine learning methods

T2 - IS - KW - training and development KW - supra-professional competencies KW - adaptability KW - recommendation system KW - machine learning KW - matrix factorization KW - neural network AB -       Today, the economy is undergoing a digital transformation. Its key barriers are a lack of qualified personnel, competencies and knowledge, as well as internal resistance in organizations. It can be overcome through quality staff development and training. An urgent problem is to build a personalized learning path. Modern research is aimed at the implementation of recommendation systems in order to select relevant material. However, these recommendations are based on digital traces; the student’s full personal profile, as well as organizational values are not considered. This study aims is to create an intelligent guide that would accompany an employee throughout his life in the organization, involving him in the learning process according to a personalized path based on a complex personal profile and reactions to educational material, training soft and hard skills in accordance with the values of the organization and the employee. Methods of system analysis, system engineering, psychodiagnostic research (the DISC model, Rowe’s "Decision-making Style" methodology, Honey and Mumford’s method of determining activity styles, psychotype test), software design and artificial intelligence (matrix factorization and neural networks) were used in this study. The study was conducted on a unique database collected as part of its implementation and consisting of educational tasks for soft skills development, plus data on their implementation by users with different soft skills profiles. An intelligent guide model has been developed and implemented as a software component for an enterprise management system. The basis consists of psychodiagnostic modules, organizational management, training and recommendations. The intelligence of the system we developed allows you to qualitatively form a personalized learning path that will involve an employee not only in the learning and development process, but also in achieving organizational goals. The organization receives T-shaped specialists who have a proactive position and are capable of self-organization by investing in the development of employees. The results of this study can be used by enterprises not only at the organizational level, but also through broadcasting in the education system to form an education ecosystem in accordance with the requirements of innovative development of a given region’s economy. AU - Ekaterina Morozevich AU - Vladimir Korotkikh AU - Yevgeniya Kuznetsova UR - https://bijournal.hse.ru/en/2022--2 Vol 16/670746381.html PY - 2022 SP - 21-35 VL -