Making Sense of Complex Phenomena through Building Object- based Parallel Models

小行星9632612 该项目的内容领域是学习“复杂性”。 复杂性是研究系统中的现象表现出复杂的行为，雪花晶体的生长，枫叶的周边模式，道琼斯指数或四年级教室的动态。这些都是可以被建模为由许多分布式但相互作用的部分组成的系统。它们都表现出非线性或突现性，超出了当前K-12数学课程的范围。 该项目的目标是通过使用基于对象的并行建模语言（OBPML），使复杂性的学生。学生从“零开始”建立复杂的数学和科学现象的模型，以及从“可扩展模型”库中提供的扩展模型。 通过这些活动，研究人员寻求： * 理解学习者在构建基于对象的并行模型时如何理解复杂现象 * 设计计算工具和活动，以促进学习者在a）构建复杂现象模型和B）构建复杂性直观概念 * 探讨参与数学建模的学习者如何改变他们对数学和科学事业的信念和态度 * 调查参与基于对象的并行建模的学习者开发的各种符号化模式。 OBPMLs提供了一种概率和统计建模方法。该项目的成果之一是加强和扩大了概率和统计在数学和科学课程中的作用，将其与蒙特卡罗模拟等计算技术相结合-从而开发了一个新的学科领域，也许更好地称为随机学。在这方面和其他方面，我们希望开发新的数学内容领域-内容领域生活在一个基于对象的并行介质。 ***

9632612 Wilensky The content area of the project is learning about "complexity". Complexity is the study of systems in which phenomena exhibit complex behavior , the growth of a snowflake crystal, theperimeter pattern of a maple leaf, the dynamics of the Dow Jones or of a fourth grade classroom. These are all systems which can be modeled as composed of many distributed but interacting parts. They all exhibit non-linear or emergent qualities which place them beyond the scope of current K-12 mathematics curricula. The project goal is to make complexity accessible to students through the use of object-based parallel modeling languages (OBPML). Students build models of complex mathematical and scientific phenomena from "scratch" as well as exending models they are given from a library of "extensible models". Through these activities, the researchers seek: * To understand how learners make sense of complex phenomena when engaged in building object-based parallel models * To design computational tools and activities that foster learner's in a) building models of complex phenomena and b) building intuitive conceptions of complexity * To investigate the ways in which learners engaged in this kind of modeling change their beliefs about and attitudes towards the mathematical and scientific enterprises * To investigate patterns in the kinds of symbolization developed by learners engaged in object-based parallel modeling. OBPMLs afford a probabilistic and statistical approach to modeling. One outcome of the project is a strengthened and broadened role for probability and statistics in the mathematics and science curricula, combining it with computational techniques such as Monte Carlo simulations - thus developing a new subject area perhaps better called stochastics. In this respect and others, we expect to develop new mathematical content areas - content areas which live in an object-based parallel medium. ***