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Assistant teaching of linear algebra based on geometric interpretation and practical application

Published: 21 January 2020 Publication History

Abstract

Linear algebra is not only a powerful tool in dealing with the problem of multi-variables, but also strongly logical. Students always feel that linear algebra is abstract, boring, and difficult to understand. For the teaching of linear algebra, the instructional design of linear algebra that combining the geometry intuition and practical application is proposed to help students understand the abstract knowledge. As an example in our teaching process, the geometric interpretation of matrix, similar matrices, eigenvalues and eigenvectors are given in turn. This teaching method aims to help students shift perception from visual to abstract and thus improve the teaching efficiency of linear algebra. The practical application of eigenvalue in image compression, i.e. Karhunen-Loeve transform, is presented. It is advantages to promote students' motivation in learning and cultivate their abilities in using mathematics to solve practical problems.

References

[1]
STEWART S, THOMAS M O J. 2007. Embodied, symbolic and formal thinking in linear algebra. Math Educ Sci Tech. 38, 7 (Oct.2007): 927--937.
[2]
WU Ming-yue, LI Wan-dong, WANG Bo, CAO Fu-jun.2018. Teaching exploration of geometrical meaning of matrix and linear transformation. Journal of Science of Teachers' College and University. 38, 7 (Jul.2018), 61--64.
[3]
Wang Fei, Liao Xiaofeng, Guo Songtao, Zhan Ming. 2016. On heuristic teaching of vector space based on geometric intuition and engineering application. Journal of Southwest Normal University (Natural Science Edition).41, 3 (Mar.2016): 196--201.
[4]
GUEUDET G. 2004. Should we teach linear algebra through geometry. Linear Algebra and its Applications. 379 (Jan.2004):491--501.
[5]
Yan Y, Liu B, Xu X, et al.2011. The Fusion of Mathematics Experiment and Linear Algebra Practice Teaching. Information Computing and Applications. Springer Berlin Heidelberg.
[6]
Guo Yan, Zhao Yuying. 1995.Certain application of linear algebra.Journal of Luoyang University.10, 2 (Jun.1995): 79--82.
[7]
Caglayan, Günhan.2018. Linear algebra students' understanding of similar matrices and matrix representations of linear transformations in a MATLAB-assisted learning environment. Computers in the Schools. 35, 3 (Oct.2018): 204--225.
[8]
Li Ji-chen, Zhao xiaoyan. 2018.The practice and design of teaching contents about cultivating students' creative thinking. College Mathematics. 34, 2 (Apr.2018):63--66.
[9]
Zhou Hailin.2018. Analogy method for linear dependence of vectors in linear algebra. Studies in College Mathematics. 21, 1, (Apr.2018): 68--70.
[10]
Shen Yan, Wang Feng, Fan Zhoutian. 2018.From linear operation to the definition of determinant.College mathematics.34, 5 (Oct.2018):67--71.
[11]
Min Chao.2019. Studies on the properties of eigenvalues of matrices-thoughts of the linear algebra teaching. Education Teaching Forum.24(Jun.2019):190--191.
[12]
Yang Wei, Gao Shuping, Chen Huaichen.2019. Integration of Matlab and linear algebra teaching in MOOC. Studies in College Mathematics. 22, 3(May.2019):60--62.
[13]
Lesh, Richard, and Lyn D. English.2005.Trends in the evolution of models & modeling perspectives on mathematical learning and problem solving." Zentralblatt Fur Didaktik Der Mathematik. 37, 6 (Jan.2005): 487--489.
[14]
Possani, E., et al. 2010.Use of models in the teaching of linear algebra. Linear Algebra and its Applications. 432, 8 (Jan.2010): 2125--2140.
[15]
Ji Qiang, Shi Wenxuan, Tian Mao, Chang Shuai. 2016. Multispectral image compression based on uniting KL transform and wavelet transform. Infrared and laser engineering. 45, 2 (Feb.2016):0228004.

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    ICETC '19: Proceedings of the 11th International Conference on Education Technology and Computers
    October 2019
    326 pages
    ISBN:9781450372541
    DOI:10.1145/3369255
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • University of Twente: University of Twente

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    New York, NY, United States

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    Published: 21 January 2020

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    Author Tags

    1. K-L transform
    2. Matrix
    3. eigenvalue
    4. image compression
    5. similar matrices

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