Scholarlink

This chapter explores the potential of using generative artificial intelligence (AI) to enhance teaching methods and monitoring, thereby improving the quality of education for students in primary and secondary schools. In a related way, this is a discussion that is indirectly related to the global shortage of teachers. We believe that these actions have direct implications with the United Nations (UN) 2030 sustainable development perspective, especially regarding education and the reduction of inequalities, since the improvement of the quality of education through AI can imply the expansion of school knowledge and, in the medium and long term, better education implies the collective improvement of social groups. Our method involves conducting a comprehensive theoretical discussion that addresses the global challenges in teacher training and work, utilizing data from sources such as United Nations Educational, Scientific and Cultural Organization (UNESCO), the UN, and the Organization for Economic Co-operation and Development (OECD). In addition to analyzing existing teaching data, we aim to explore the potential of developing AI systems tailored to the specific contexts of each country’s educational systems. We conducted broad research on the conditions of teaching work worldwide, to detect teacher gaps. We analyze from the perspective of the potential of generative AI, actions that can be produced to support AI to the teacher and the educational system with a view to improving school education in a sustainable way.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Artificial Intelligence in the Global Educational Context: Prospects for Pedagogical Practice and Application in the Context of Teacher Shortages

  • 章节

  • 发表日期：

    2025年

查看全文
  • Eucidio Pimenta Arruda,
  • Durcelina Pimenta Arruda

摘要

This chapter explores the potential of using generative artificial intelligence (AI) to enhance teaching methods and monitoring, thereby improving the quality of education for students in primary and secondary schools. In a related way, this is a discussion that is indirectly related to the global shortage of teachers. We believe that these actions have direct implications with the United Nations (UN) 2030 sustainable development perspective, especially regarding education and the reduction of inequalities, since the improvement of the quality of education through AI can imply the expansion of school knowledge and, in the medium and long term, better education implies the collective improvement of social groups. Our method involves conducting a comprehensive theoretical discussion that addresses the global challenges in teacher training and work, utilizing data from sources such as United Nations Educational, Scientific and Cultural Organization (UNESCO), the UN, and the Organization for Economic Co-operation and Development (OECD). In addition to analyzing existing teaching data, we aim to explore the potential of developing AI systems tailored to the specific contexts of each country’s educational systems. We conducted broad research on the conditions of teaching work worldwide, to detect teacher gaps. We analyze from the perspective of the potential of generative AI, actions that can be produced to support AI to the teacher and the educational system with a view to improving school education in a sustainable way.