Application of machine learning algorithm for career guidance of university applicants

Author:

Zabokritskaya Lyubov D., ,Oreshkina Tatyana A.,Obabkov Ilya N.,Chepurov Evgeny G., , ,

Abstract

The aim of the article is to describe the experience of implementing our own software product (Wizard UrFU) for career guidance and navigation of university entrants. The importance of introducing digital technologies for career guidance and navigation of university entrants is substantiated. The article addresses both sociological and IT tasks. On the part of information technology, a description is given of the main methods on which the work of a software product for vocational guidance and navigation of applicants can be built. In particular, we have proved that the most promising is the complex method, which is based on a combination of several methods and algorithms for the operation of neural networks for vocational guidance and navigation of applicants. The article describes the algorithm of the software product developed by our team. We show that this algorithm is based on the analysis of digital traces of applicants in the social network VKontakte. The algorithm uses the machine learning method. We also show that the career guidance system in the Wizard web application is based on a comparison of profile data in the VKontakte social network and generalized data of university students successfully enrolled in one of the educational programs. We analyzed the statistics of recommendations of educational programs to UrFU applicants using the UrFU Wizard web application using the Yandex. Metrics. The socio-demographic portrait of the UrFU Wizard software product user is a young man (or woman) aged 18 to 24 from Yekaterinburg or Sverdlovsk Oblast. This description fully coincides with the main target audience of the Ural Federal University. As a result, 12,780 potential applicants of Ural Federal University started submitting documents through the web application. In addition, 32% or 15,293 applicants made a transition to the institutions’ social networks and educational programs for a more detailed acquaintance. The analysis of the admission campaign results showed that all educational programs that were in the TOP of recommended areas had a significant increase in applicants compared to previous years. In general, Ural Federal University in 2021 held the most massive admission campaign among higher educational institutions in the Russian Federation. In our opinion, the use of services based on the work of artificial intelligence for career guidance and navigation of applicants of a higher educational institution allows a successful solution of the following tasks: to expand the geography of admission without holding face-to-face meetings with applicants; to increase the reach of the advertising campaign and personalize advertising offers; to attract creative and motivated youth; to help the applicant to make the right choice of the direction of training and thereby increase the motivation to study.

Publisher

Tomsk State University

Subject

General Medicine

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