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Updated: Jan 28, 2026

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医療教育者向け人工知能（AI）リテラシーに関する専門家コンセンサス（2025年版）

Hui Pan1, Meng-Chun Gong2, Jing-Hui Lu2

  • 1Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
|January 27, 2026
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まとめ

このコンセンサスは、教育における生成AI（AI）をナビゲートするための、医療教育者向けAIリテラシーフレームワークを提案します。効果的なAI統合と専門能力開発のためのコアコンピテンシーを概説します。

キーワード:
人工知能リテラシーコンピテンシーフレームワーク教育者開発専門家コンセンサス医学教育

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科学分野:

  • 医学教育;人工知能;デジタルヘルス

背景:

  • 生成AI（AI）は、医学教育において重大な課題と機会をもたらします。;医療教育者がAIリテラシーを開発するための指針となる構造化されたフレームワークが必要です。

研究 の 目的:

  • 医療教育者向け包括的AIリテラシーフレームワーク（CAIP-ME）を提案すること。;医療教育者のAIリテラシーに関するコアコンピテンシー項目と評価基準を確立すること。

主な方法:

  • 体系的な文献レビュー。;予備的なフレームワーク構築。;専門家による複数回の予備研究。;60人の学際的な専門家による構造化デルファイ法。

主要な成果:

  • 5つのコア次元と25の具体的なコンピテンシー項目からなるフレームワークが開発されました。;コンピテンシーは、11の基礎項目と14の開発項目に分類されます。;各項目には、定義、行動的現れ、評価指標が含まれます。

結論:

  • CAIP-MEフレームワークは、医療教育者の専門能力開発のための科学的根拠を提供します。;ファカルティビルディングをサポートし、医学教育におけるデジタルトランスフォーメーションの参考となります。;このフレームワークは、教育と学習の改善のために、医療教育者のAIコンピテンシーを高めることを目的としています。