Collaborative Research: Learning About Complex Systems in Middle School by Constructing Structure-Behavior-Function Models

协作研究：通过构建结构-行为-功能模型来学习中学复杂系统

• 批准号: 0632546
• 负责人: Rebecca Jordan
• 金额: --
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0632546&HistoricalAwards=false
• 关键词: Collaborative; Research; Learning; About; Complex

Background: Artificial Intelligence theories of model-based analogy in conceptual design have led to amethodology and a language for building functional and causal models of complex systems calledStructure-Behavior-Function (SBF) models. An SBF model of a system explicitly represents its structure[S] (i.e., its configuration of components and connections), its functions (F) (i.e., its output behaviors), andinternal causal behaviors [B] (i.e. its causal processes that compose the functions of the components intothe functions of the system). The SBF language provides a vocabulary for expressing and organizingknowledge in a hierarchy, which captures functionality and causality at multiple levels of aggregation andabstraction.Empirical research in the Learning Sciences using the SBF methodology have led to substantial evidencethat while experts model a complex system in terms of its structure, behaviors and functions, novicesexpress primarily the structure of the system, demonstrate minimal understanding of its functions, andlargely miss its behaviors.

背景：概念设计中基于模型的类比的人工智能理论导致了一种方法和语言，用于构建复杂系统的功能和因果模型，称为结构-行为-功能（SBF）模型。系统的SBF模型明确表示其结构[S]（即组件和连接的配置），功能(F)（即输出行为）和内部因果行为[B]（即将组件的功能组成系统功能的因果过程）。SBF语言为在层次结构中表达和组织知识提供了一个词汇表，它在聚合和抽象的多个层次上捕获功能和因果关系。学习科学中使用SBF方法的实证研究已经得出了大量证据，表明当专家根据其结构、行为和功能对复杂系统进行建模时，新手主要表达系统的结构，对其功能的理解很少，并且在很大程度上忽略了它的行为。