中国の大学でEFL学習者のAI技術への受け入れが,コンピュータの自己効率性によって推進されていることを調査する.
1Basic Teaching Department(English Branch), Jianghai Polytechnic College, Yangzhou, Jiangsu, China.
Acta psychologica
|February 17, 2026
まとめ
コンピュータの自己効率性は,中国の大学で外国語 (EFL) としての英語を学ぶ人の間でAIの採用を大幅に高めています. この要因は,使いやすさと有用性との認識とともに,AI技術を使用する彼らの意図を駆動しています.
科学分野:
- 教育技術教育技術について
- 教育における人工知能
- 人とコンピュータの相互作用です.
背景:
- AIの使用におけるコンピュータの自己効率性に関する定量的な研究は限られている.
- EFL学習者の間でAIの受け入れに影響を与える要因を理解することは,効果的な技術統合に不可欠です.
- テクノロジー受け入れモデル (TAM) は,技術採用を研究するための枠組みを提供します.
研究 の 目的:
- 中国大学のEFL学習者のAI技術の受け入れに対するコンピュータの自己効率性の影響を調査する.
- この関係における,知覚された使いやすさ,知覚された有用性,および態度の仲介的な役割を調べる.
- EFL教育におけるAI技術の応用を強化するための経験的証拠を提供すること.
主な方法:
- 拡張技術受け入れモデル (TAM) が採用されました.
- オンラインアンケートを通じて,中国の大学でEFLを学ぶ776人の生徒から収集されたデータです.
- データ分析に使用される構造方程式モデリング (SEM).
主要な成果:
- コンピュータの自己効率性は,AIを使用する行動的意図に肯定的に影響します.
- 認識された使いやすさ,認識された有用性,および態度は,コンピュータの自己効率性とAIの使用意図の間のリンクを媒介する.
- 提案されたTAMモデルは,変数間の有意な関係を実証した.
結論:
- コンピュータの自己効率性は,中国語のEFL学習者のAI受け入れの重要な決定因子です.
- 認識された使いやすさ,有用性,そしてポジティブな態度を高めることを目的とした介入は,AIの採用を促進することができます.
- 結果は,EFLの文脈でAIを推進する教育者や政策立案者にとって実用的な洞察を提供します.
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