复杂系统控制内隐学习范式的特点研究

Characteristics of the Complex-system-control Model of Implicit Learning

在人工语法学习、序列学习以及复杂系统控制这三大内隐学习研究范式中,复杂系统控制范式尝试模拟出人们在实际问题解决过程中可能出现的内隐学习,具有更高的生态效度。对城市交通系统、英国经济学模型、糖生产任务以及人际交互任务等复杂系统控制任务进行研究后,我们得出复杂系统控制范式的特点:任务情境的自然性、学习过程的互动性、系统变化的连续性、系统规则的隐蔽性及内隐-外显学习的混合性等。

Of the three important models in the research of implicit learning, the artificial grammar model, the sequence learning model and the complex-system-control model, the complex-system-control model has the highest ecological validity for its attempt to simulate implicit learning in the real problem-solving situation. Through the study of a series of complex system control models we found five characteristics： natural task situation, interactive learning process, continuous change of the system, complex rule, and the close link of implicit-explicit learning.