The applicant’s virtual consultant to provide career guidance and specialty selection during the admissions campaign
Students Name: Ustyianovych Taras Ostapovych
Qualification Level: magister
Speciality: Information, Library and Archival Studies
Institute: Institute of the Humanities and Social Sciences
Mode of Study: full
Academic Year: 2022-2023 н.р.
Language of Defence: англійська
Abstract: In the Ukraine educational system, the problem of a professional orientation is quite acute, especially for entrants to higher education institutions when choosing a specialty for obtaining an academic degree. From the applicant’s point of view, difficulties are revealed in career and personal development, choosing a specialty that brings satisfaction and benefit. In the case of higher education institutions, it is crucial to ensure quality management due to the imbalance of applications and entrants per specialty. Currently, there are several related theoretical studies on this topic: sustainable development, recommendation engines, and automated systems in higher education [1- 3]. However, this is only one piece of the puzzle that still needs to be completed. Domestic researchers focus exclusively on specific aspects of this problem but need to describe it globally as a complete picture. So, there still needs to be an end-to-end solution in Ukrainian higher education. Essential are the pieces of research by Fedushko S.S., Ustyianovych T.O., and Syerov Y.O. on the innovative selection of specialties for higher education institution applicants in Ukraine. A decision-making algorithm for choosing an educational specialty and a database with the characteristics of each specialty is proposed [4-5]. 117 The researchers described the target audience of entrants and the expected input data set for making recommendations. Studies published in the two most authoritative scientific databases, Scopus and Web of Science, were analyzed using the PRISMA method to examine available papers thoroughly. [6, 7, 8, 9, 10]. The international experience of solving similar problems and relevant Internet resources were analyzed, particularly Pearson Pathways and the analytical center CEDOS, which contains a set of investigations on the same topic. The Python programming language was chosen to implement the solution since it supports a wide range of integration functionality with cloud computing environments, software libraries for creating recommendation algorithms, and web development. Study object - the process of information and recommendation support of entrants. Scope of research - development of a virtual consultant to provide specialty recommendations to entrants of Ukrainian higher education institutions. Goal of research - development of a virtual consultant to provide specialty recommendations for entrants. As a result of completing the master’s thesis, it was possible to create a virtual consultant for the applicant, in particular, to obtain the following resources: a specialties database; a recommendation algorithm that works based on neural networks and is developed using the TensorFlow software library; analysis admission campaign 2021; a set of associative rules for choosing specialties. Ways to overcome such risks as service unavailability, user complaints, and consequences of the war in Ukraine are considered and described. It is proposed to optimize the current solution and improve it based on user feedback. Keywords: virtual consultant; educational technologies; recommendation system; admission campaign; higher education institution.