Pedagogical conditions enabling the finalists of the Artificial Intelligence Olympiad to achieve great results

Author:

Trubina I. I.1ORCID

Affiliation:

1. Institute for Strategy of Education Development of the Russian Academy of Education

Abstract

The article analyses the survey of the finalists in the first All-Russian Artificial Intelligence Olympiad for school students of the 8–11 grades of general education institutions. Artificial Intelligence is a strategically important area; it is designated as one of the end-to-end digital technologies in the national program “The Digital Economy of the Russian Federation”. Such technologies ensure accelerated development of priority sectors of the economy and the social sphere. In 2021 within the framework of achieving result 1.7 of the Federal Project “Artificial Intelligence” of the National Program “The Digital Economy of the Russian Federation’, the Ministry of Education of the Russian Federation organized and held an Artificial Intelligence Olympiad for school students of the 8–11 grades of general education institutions. The following objectives were pursued during the research: to obtain the Olympiad finalists’ “portrait” focusing on certain characteristic features; to examine the finalists’ attitude to the concept of “artificial intelligence”; to identify the pedagogical conditions enabling the finalists to succeed in the Olympiad; to provide an update on several modern trends in the development of general education. The systematization of the winners’ answers made it possible to develop an algorithm for achieving success that guaranteed the finalists the excellent results in the Artificial Intelligence Olympiad. This algorithm serves as a pedagogical condition for updating modern trends in general education. The implementation of correctly chosen pedagogical conditions can ensure the development and efficiency of the pedagogical system to achieve good results in the Artificial Intelligence Olympiad.

Publisher

Publishing House Education and Informatics

Subject

General Medicine

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