混合言語学習における自己規制エンジンとしての形成的評価: トップレベルのエンジニアリングの才能を持つケーススタディ
Honghao Ren1, Wenli Zhang1, Hongquan Cao1
1School of Foreign Studies, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.
Acta psychologica
|February 21, 2026
まとめ
形成的評価は,ブレンドラーニングにおける自己規制 (SRL) エンジンとして作用し,学生のモチベーションと学習の質を高めます. この周期的なプロセスは,エンジニアリング教育にとって不可欠な自律的な学習をサポートします.
科学分野:
- 教育技術教育技術について
- 言語学習 言語学習 言語学習
- 自律学習による学習です.
背景:
- 結果指向の評価とプロセス指向の学習のギャップを埋める.
- 自己規制 (SRL) エンジンとしての形成的評価を調査する.
- エンジニアリングの学生のための日本語のブレンドコースに焦点を当てています.
研究 の 目的:
- エンジニアリング学生の自己規制 (SRL) の促進における形成的評価の役割を検討する.
- 学習に対する対話的フィードバックエコロジーの影響を分析する.
- 外国語教育におけるカリキュラム改革のための実践的な指導を提供すること.
主な方法:
- 40人の1年生エンジニアリングの学生を対象とした混合手法設計.
- 定量データ:アンケートとパフォーマンスメトリック (N=40)
- 定性データ:反省型学習ジャーナル (n=87件) と半構造面接 (n=4)
- 組み込みの形成メカニズム:SPOC分析,チェックポイント,ジャーナル,ピアインタラクション.
主要な成果:
- 継続的な,マルチエージェントのフィードバックは,動機付け,戦略の使用,そして反射的な規制を強化します.
- 学習者の不安が軽減され,学習目標の内在化が改善されます.
- 評価は周期的なSRLプロセスに変換され,エンゲージメントと言語学習の質を高めます.
結論:
- 形成的評価は,ブレンドラーニング環境における持続可能なSRLエンジンとして機能します.
- この研究は,エンジニアリングの文脈で自律的な生涯学習を促進するための移行可能なモデルを提供します.
- 外国語教育におけるカリキュラム開発に関する実用的な意味合いも強調されています.
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