特征向量
模式(遗传算法)
构造(python库)
对象(语法)
数学
计算机科学
数学教育
域代数上的
人工智能
纯数学
机器学习
程序设计语言
量子力学
物理
作者
Hilda Salgado,María Trigueros
标识
DOI:10.1016/j.jmathb.2015.06.005
摘要
In this article we share the results of an investigation of a classroom experience in which eigenvalues, eigenvectors, and eigenspaces were taught using a modeling problem and activities based on APOS (Action, Process, Object, Schema) Theory. We show how a sample of 3 students were able to construct an object conception of these difficult concepts in one semester course—something that existing literature had proven to be almost impossible to achieve. Using one team as a case study we describe the work done by a group of 30 students to show how eigenvectors and eigenvalues emerged in a group discussion. Furthermore, we present evidence on how, at least three students, were able to construct an object conception, demonstrating a deep understanding of these concepts. Finally, we validate the designed genetic decomposition. In summary, the results demonstrate the approach to be promising in the learning of eigenvalues and eigenvectors.
科研通智能强力驱动
Strongly Powered by AbleSci AI