Modeling and Simulation in Inquiry Learning: Checking Solutions and Giving Intelligent Advice
Modeling and Simulation in Inquiry Learning: Checking Solutions and Giving Intelligent Advice
复制标题
探究式学习中的建模与仿真：检查解决方案并给出智能建议
DOI：
10.1177/0037549706074190
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
T. Jong
中科院分区：
文献类型：
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作者：
Crescencio Bravo;W. Joolingen;T. Jong
研究性学习是一种教学方法，学生通过理论构建和实验过程获得知识和技能。计算机建模和仿真可以在这种方法中发挥重要作用。学生使用建模构建物理系统的表示。使用模拟，他们执行这些表示来研究建模的现象或系统。然而，建模任务是复杂的，学生可能无法创建足够的模型，这阻碍了有效的学习。这就需要支持性措施来支撑建模过程。在本文中，我们解决的问题，设计这样的支持，通过开发智能咨询建模环境。建议是基于每个建模问题的参考解决方案的家庭的定义，对参考解决方案与学生的解决方案的比较，并使用建议知识库。这个建议指导学生构建更好的解决方案，帮助他们获得成功建模和纠正建模错误所需的知识。在合作会议中，有建议鼓励学生之间的讨论有关的建议和最好的方式进行。的建议方法的实证验证。
Inquiry learning is a didactic approach in which students acquire knowledge and skills through processes of theory building and experimentation. Computer modeling and simulation can play a prominent role within this approach. Students construct representations of physical systems using modeling. Using simulation, they execute these representations to study the phenomena or systems modeled. However, the modeling task is complex, and students can fail to create adequate models, which prevents effective learning. This necessitates supportive measures to scaffold the modeling processes. In this paper, we address the issue of designing such support through the development of intelligent advice to be incorporated in modeling environments. The advice is based on the definition of a family of reference solutions for each modeling problem, on the comparison of the reference solutions with the students' solutions, and on the use of an advice knowledge base. This advice guides the students to the construction of a better solution, helping them acquire the knowledge required for successful modeling and for the correction of modeling mistakes. In a collaborative session, having the advice encourages discussion between students about the advice and the best way of proceeding. Empirical validations of the advice approach are presented.