韓国の伝統医学教育における生成性人工知能の利用と認識:韓国の大学生を横断的に調査
PubMedで要約を見る
まとめ
この要約は機械生成です。韓国の伝統医学 (TKM) の学生の間でジェネラティブAI (GenAI) の認識は高いが,TKM教育におけるその使用は限られている. GenAIをTKMのカリキュラムに統合することは,デジタル準備と学習成果の向上に不可欠です.
科学分野
- 医学教育
- 教育における人工知能
- デジタル・ヘルス
背景
- 韓国の伝統的な韓国医学 (TKM) の大学生におけるジェネラティブAI (GenAI) の使用,意識,および満足度を調査した.
- TKMの学術的な文脈におけるGenAIの採用と満足度に影響を与える重要な要因を特定しました.
研究 の 目的
- TKM教育におけるGenAI利用の現状と学生の認識を評価する.
- TKMの学生のGenAI使用と満足度に関連する人口統計学的および学術的要因を特定する.
主な方法
- 56項目のアンケートで6学年の234人のTKM学生を調査した.
- データ分析には,記述的統計,単変数,多変数ロジスティック回帰,および相関分析が含まれていた.
主要な成果
- 高いGenAI認識 (88.5%) と一般的な使用 (79.9%) が,TKM特有の学習使用は低い (16.2%).
- 一般的なGenAI使用に対する学生の満足度 (70.4%) は,TKM教育に対する満足度が低い (45.8%) と対照的です.
- TKMのカリキュラム登録,年齢,以前の専攻,奨学金,自己学習などの要因は,GenAIの使用/満足度と相関しています.
結論
- GenAIに対する学生の関心と,TKMのカリキュラムへの統合の間に大きなギャップがある.
- TKM教育におけるデジタル準備と学習成果を改善するために,GenAIの体系的な組み込み,教員研修,および制度的サポートが推奨されています.
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