Scholarlink

This chapter explores the transformative impact of generative Artificial Intelligence (AI) on geography education through the lenses of the SAMR model, Bloom’s Taxonomy, and the AI-TPACK framework. It examines how AI is reshaping teaching methods, learning experiences, and teacher competencies in geography education. The SAMR model demonstrates AI’s potential to redefine geographical learning experiences, moving beyond mere substitution to enable novel educational approaches. Bloom’s Taxonomy analysis reveals how AI alters students’ cognitive experiences, enhancing higher order thinking skills while potentially risking over-reliance on AI-generated content. The AI-TPACK framework highlights the evolving competencies required for geography teachers in the AI era, emphasizing the need for integrated technical, pedagogical, and content knowledge.

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

Generative AI and Geography Education

  • 章节

  • 发表日期：

    2025年

查看全文
  • Jongwon Lee

摘要

This chapter explores the transformative impact of generative Artificial Intelligence (AI) on geography education through the lenses of the SAMR model, Bloom’s Taxonomy, and the AI-TPACK framework. It examines how AI is reshaping teaching methods, learning experiences, and teacher competencies in geography education. The SAMR model demonstrates AI’s potential to redefine geographical learning experiences, moving beyond mere substitution to enable novel educational approaches. Bloom’s Taxonomy analysis reveals how AI alters students’ cognitive experiences, enhancing higher order thinking skills while potentially risking over-reliance on AI-generated content. The AI-TPACK framework highlights the evolving competencies required for geography teachers in the AI era, emphasizing the need for integrated technical, pedagogical, and content knowledge.