自動化の多層モデル:自動行動制御の出現を駆動するコアプロセス
Hermann Müller1, Rouwen Cañal-Bruland2, Stefan Künzell3
1Department of Sport Science, Justus Liebig University Giessen, Germany.
Acta psychologica
|December 12, 2025
まとめ
自動化は、自動化の多層モデル(MMA)を通じて練習によって現れる。このモデルは、認知制御レベルがどのように学習し適応し、スキルを段階的にし、認知リソースを解放するかを示す。
科学分野:
- 認知心理学
- 神経科学
- 学習科学
背景:
- 学習における自動化は複雑で、その定義とメカニズムに関する理論は様々である。
- 非自動処理から自動処理への移行には、統一された説明モデルが欠けている。
研究 の 目的:
- 練習を通じて自動化が出現する仕組みを説明する自動化の新しい多層モデル(MMA)を提案する。
- 自動化を段階的な特性として、二値的なものではなく概念化する。
主な方法:
- MMAは、適応制御ユニットを持つ階層的に組織化された処理レベルを想定している。
- これらのユニットは、規則性を学習し、タスクを予測し、目標指向の出力を生成する。
- 自動化は、レベル間の制御信号交換の減少としてモデル化される。
主要な成果:
- MMAは自動化の前提条件とメカニズムを指定する。
- 処理レベルが独立性を獲得し、高レベルの能力を解放する方法を示す。
- 自動化の程度は、制御信号交換によって定量化できる。
結論:
- MMAは、人間の自動化を段階的なプロセスとして理解するためのフレームワークを提供する。
- 自動化された行動の予測を提供し、将来の研究分野を特定する。
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