Open AccessComputer-aided Linear Algebra Course on Jupyter-Python Notebook for Engineering Undergraduates
Author(s) -
Chang Tang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1815/1/012004
Subject(s) - python (programming language) , linear algebra , computer science , workflow , symbolic computation , algebra over a field , programming language , numerical linear algebra , software engineering , mathematics education , linear system , mathematics , pure mathematics , geometry , mathematical analysis , database
As an important basic course, linear algebra plays critical role for engineering undergraduates. However, traditional purely theoretical explanation makes students difficult to deeply understand the essence of linear algebra. In this paper, we introduce a new form of computer-aided linear algebra course with the application of a set of Python computer programs implemented on the Jupyter notebooks platform, and also aim to improve the development of innovative teaching methodologies for this course. In addition, in order to help students understand the intrinsic physical meanings of some concepts, we design some visual examples which demonstrate the practical applications of linear algebra. A serious of user-friendly Jupyter notebooks workflows developed in this work allow teachers–students to intuitively teach and learn theoretical concepts, description of practical problems, programming code, and simulation results with a visual output. The designed environment can help teachers/students to implement their simulations in Python language.