模拟教学设置的特点

Wouter R. van Joolingen, Ton de Jong
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引用次数: 39

摘要

本文讨论了仿真的内部特性。它的主要部分是关于模型及其与领域的关系。定义了一些关于建模和仿真的核心概念。这些概念包括:•模型的结构和特征;•与正在建模的系统的关系;•学习者或其他代理与模型的相互作用。提出了模型类型的分类,并提出了几种模型类型表示的第一个想法。分类包括定性和定量模型之间的区别。根据模型的时间依赖性,可以进一步将模型分为动态模型和静态模型。任何仿真模型的基本元素都是模型的状态,描述被建模系统的属性,以及一组确定模型状态可能发展的规则。状态空间是所有可能状态的集合。在定量模型中,状态的基本元素是变量,这些变量可以是相关的,也可以是独立的。因变量是指其值由自变量决定的变量。模型规则是方程,决定变量值的发展。根据状态空间的结构,定量模型分为离散模型和连续模型。定性模型有一个由被建模系统的命题组成的状态空间。在这种情况下,模型规则具有更具描述性的特征。简要讨论了模型与对应的实际系统之间的关系。现实系统有三种类型:物理系统、人工系统和抽象系统。区分这些类型的系统的主要标准是构建一个完整描述系统的模型(基本模型)的可能性。通过引入交互和场景的概念来描述学习者与模型和仿真的交互。交互描述了在模型上执行的操作序列,场景包括交互和参与交互的代理。讨论了教学模拟环境的分类(通常简称:教学(或教育)模拟)。研究了这些分类的有用性和特点。许多现有的分类不能很好地区分模拟学习环境的相关方面。三个部分描述了模拟的内部特征和de Jong(本卷)中介绍的四个主题之间的关系:领域模型,学习目标,学习过程和学习者活动。由于仿真模型在本文的第一部分中进行了广泛的讨论,因此关于领域和仿真模型的部分概述了模型中未明确提及的领域方面。在这里,将介绍一个额外的知识库,称为认知模型。对于每种类型的学习目标,阐述了与领域模型或场景的关系。通过将学习者活动的可能类型与模型和场景元素联系起来,从而导致对模型或场景结构的需求,讨论了学习过程与学习者活动和领域模型之间的关系。
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Characteristics of simulations for instructional settings

This paper discusses the internal characteristics of simulations. The major part of it is concerned with models and their relation with the domain. Some central concepts regarding modelling and simulation are defined. These include concepts regarding:

  • the structure and characteristics of the model;

  • the relationship to the system that is being modelled;

  • the interaction of the learner or other agents with the model. A classification of model types is presented, accompanied by a first idea on the representation of the several types of models. The classification includes the distinction between qualitative and quantitative models. Models can further be classified into dynamic and static models, determined by the time dependency of the model. The basic elements of any simulation model are the state of the model, describing the properties of the system that is modelled, and a set of rules determining the possible development of the model state. State space is the collection of all possible states.

In quantitative models the basic elements of the state are variables, which can be dependent or independent. Dependent variables are variables of which the value is determined by the independent variables. The model rules are equations, determining the development of the values of the variables. Quantitative models are classified into discrete and continuous models, depending on the structure of the state space. Qualitative models have a state space consisting of propositions about the modelled system. In this case, the model rules have a more descriptive character.

A brief discussion of the relationship between the model and the corresponding real system is given. Three types of real systems are distinguished: physical, artificial and abstract. The main criterion for a distinction between these types of systems is the possibility of constructing a model that describes the system completely (a base model).

The interaction of the learner with models and simulations is described by introducing the concepts of interaction and scenario. The interaction describes the sequence of operations that are performed upon the model, the scenario includes the interaction and the agents who take part in the interaction.

Classifications of instructional simulation environments (often just called: instructional (or educational) simulations) are discussed. The usefulness and features of these classifications are investigated. Many of the existing classifications do not distinguish very well between relevant aspects of simulation learning environment.

Three sections describe the relationship between the internal characteristics of simulations and the four themes introduced in de Jong (this volume): domain models, learning goals, learning processes and learner activity. Because simulation models are discussed extensively in the first section of this paper, the section on domain and simulation models gives an overview of domain aspects that are not explicitly referred to in the model. Here, an additional knowledge base, called the cognitive model will be introduced. For each type of learning goal the relation with the domain model or scenario is elaborated. The relationship between learning processes and learner activity and domain models is discussed by relating the possible types of learner activity with the model and scenario elements, resulting in demands for the structure of the model or scenario.

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