Stochastic Learning Paths in Knowledge Spaces

知识空间中的随机学习路径

• 批准号: 9307423
• 负责人: Jean-Claude Falmagne
• 金额: $ 19.25万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-07-15 至 1998-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9307423&HistoricalAwards=false
• 关键词: Stochastic; Learning; Paths; Knowledge; Spaces

This project will continue the development of a new theory of learning in which the progress of students learning over time is modeled probabilistically as a Markov stochastic process. This theory is designed to provide responses to key questions about learning processes such as : What is the distribution of the knowledge states at the beginning of a particular grade in school, such as grade 4? What are the most frequently traveled learning paths? What are the easiest items for a student to learn given a particular knowledge state? How long does it take, on the average, for a student with a particular learning rate to go from one knowledge state to another? Do the students in school district A tend to follow different paths from those in school district B? This theory is a potentially powerful tool for the precise monitoring of students' learning. However, crucial work remains to be done for this theory to be easily applied by practitioners. So far it has been applied only to the special case of a single test given at a particular time. The cases of two or more tests (on the same sample of students) raise a number of technical issues (some of which are related to parameter estimations) which will be addressed in the research. The PI will also conduct an application of the theory.

该项目将继续发展一种新的学习理论，其中学生随时间的学习进度被概率地建模为马尔可夫随机过程。 该理论旨在回答有关学习过程的关键问题，例如：学校特定年级（例如四年级）开始时的知识状态分布如何？ 最常走的学习路径是什么？ 在特定的知识状态下，学生最容易学习的项目是什么？ 具有特定学习率的学生从一种知识状态转变到另一种知识状态平均需要多长时间？ A学区的学生是否倾向于走与B学区不同的道路？ 该理论是精确监控学生学习的潜在强大工具。 然而，要使该理论易于被实践者应用，还有重要的工作要做。 到目前为止，它仅适用于在特定时间给出的单个测试的特殊情况。 两个或多个测试的案例（针对同一学生样本）提出了许多技术问题（其中一些与参数估计有关），这些问题将在研究中得到解决。 PI 还将对该理论进行应用。