Self-education as a leading trajectory for training finalists of the second All-Russian Olympiad in Artificial Intelligence for schoolchildren

I. Trubina
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Abstract

The article presents the analysis of survey of finalists of the second All-Russian Olympiad in Artificial Intelligence for schoolchildren, held in the fall of 2022. The hypothesis of the study was the assumption of the leading role of self-education of schoolchildren in the field of studying intellectual technologies at the present stage.Analyzing the answers of the finalists, we determined that basic knowledge in four subjects of the general education cycle (mathematics, computer science, physics, and English) forms the basis for self-education in the process of preparation for the Olympiad. When solving new tasks for oneself, along with the assimilation of concepts and generalized methods of action, the student changes, transforming into a subject of educational activity.We have formed a rating of factors that helped the finalists in preparing for the finals of the Olympiad. The finalist’s awareness of their educational preferences allows them to build cognitive strategy, which is understood as the fulfillment of a specific set of tasks and a sequence of aimed at achieving an educational goal. The success of the self-educational trajectory is ensured by the observance of three principles of its implementation: obtaining high-quality subject knowledge, transforming the Olympiad finalist into a subject of educational activity, and building an individual strategy of self-determination.
自学是培养第二届全俄中小学生人工智能奥林匹克竞赛决赛选手的主要途径
文章介绍了对2022年秋季举行的第二届全俄中小学生人工智能奥林匹克竞赛决赛选手的调查分析。通过分析决赛选手的回答,我们确定普通教育周期四个科目(数学、计算机科学、物理和英语)的基础知识构成了奥林匹克竞赛准备过程中自我教育的基础。在为自己解决新任务时,随着概念和通用行动方法的吸收,学生会发生变化,转变为教育活动的主体。决赛选手对自己教育偏好的认识使他们能够建立认知策略,这种策略被理解为完成一系列特定的任务和旨在实现教育目标的序列。自我教育轨迹的成功需要遵守三个实施原则:获得高质量的学科知识,将奥林匹克决赛选手转变为教育活动的主体,以及建立个人自决战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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