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Enhancing School Education Through Variative Learning in Artificial Intelligence

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The dissertation explores the methodology of variable education in artificial intelligence within the Informatics curriculum for basic education. It discusses the necessity of integrating AI education in schools, proposes various educational trajectories, and examines the effectiveness of such training on students' functional literacy and understanding of AI technologies.
  • main points
  • unique insights
  • practical applications
  • key topics
  • key insights
  • learning outcomes

  • • main points

    • 1
      Comprehensive analysis of AI education integration in the school curriculum
    • 2
      Proposed innovative methodologies for variable education in AI
    • 3
      Empirical validation of the educational model's effectiveness

  • • unique insights

    • 1
      The need for AI literacy among students to interact with intelligent systems
    • 2
      The development of a structured approach to teaching AI at different educational levels

  • • practical applications

    • The article provides a framework for implementing AI education in schools, enhancing students' understanding and skills in a critical area for future careers.

  • • key topics

    • 1
      Integration of AI in school education
    • 2
      Methodology of teaching AI
    • 3
      Variable education approaches in Informatics

  • • key insights

    • 1
      Innovative educational trajectories for AI learning
    • 2
      Empirical research supporting the proposed methodologies
    • 3
      Focus on both basic and advanced AI concepts

  • • learning outcomes

    • 1
      Understanding the importance of AI education in schools
    • 2
      Ability to implement variable education methodologies in the curriculum
    • 3
      Enhanced skills in developing educational content related to AI
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“ Introduction

In today's rapidly evolving technological landscape, the significance of artificial intelligence (AI) in education cannot be overstated. This article discusses the necessity of incorporating AI into the school curriculum, particularly within the Informatics subject, to equip students with essential skills for the future.

“ Theoretical Aspects of AI Education

The theoretical framework for teaching AI in schools highlights its relevance in modern education. Various countries, including Russia, have recognized the need to integrate AI concepts into their educational systems, emphasizing the importance of foundational knowledge in programming and machine learning.

“ Methodology of Variative Learning

Variative learning methodologies allow for tailored educational experiences that cater to diverse student needs. This section outlines the principles of variative learning and its application in teaching AI, ensuring that students can engage with the material at both basic and advanced levels.

“ Implementation of AI in School Curriculum

Implementing AI education within the Informatics curriculum involves developing appropriate content and teaching strategies. This section discusses how to effectively structure lessons and resources to facilitate student understanding of AI concepts.

“ Experimental Validation of Learning Methods

To assess the effectiveness of the proposed variative learning methods, experimental studies were conducted. This section presents the findings, demonstrating the positive impact of structured AI education on student performance and engagement.

“ Conclusion

In conclusion, the integration of artificial intelligence into the school curriculum is crucial for preparing students for future challenges. By adopting variative learning methodologies, educators can enhance the learning experience and foster a deeper understanding of AI among students.

 Original link: https://www.mgpu.ru/wp-content/uploads/2023/10/dissertatsiya-Merenkovoj-Poliny-Alekseevny.pdf

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