Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence

This paper is concerned with the problem of improving undergraduate mathematical modelling competence in the current big data world. Firstly, we review the renowned teacher's seven-step, student's four-step and a six-step modelling cycles to explain mathematical modelling competence. The s...

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Main Authors: Xiao, X., Xu, Honglei, Xu, S.
Format: Journal Article
Published: John Wiley & Sons, Inc. 2015
Subjects:
Online Access:http://onlinelibrary.wiley.com/doi/10.1002/cae.21632/epdf
http://hdl.handle.net/20.500.11937/63342
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author Xiao, X.
Xu, Honglei
Xu, S.
author_facet Xiao, X.
Xu, Honglei
Xu, S.
author_sort Xiao, X.
building Curtin Institutional Repository
collection Online Access
description This paper is concerned with the problem of improving undergraduate mathematical modelling competence in the current big data world. Firstly, we review the renowned teacher's seven-step, student's four-step and a six-step modelling cycles to explain mathematical modelling competence. The six-step modelling cycle is also used in Common Core State Standards for Mathematics (CCSSM) in the United States. Based on these previous modelling cycles, we propose a new five-phase modelling cycle by use of the tool named IBM SPSS Modeler in accordance with Cross Industry Standard Process for Data Mining (CRISP-DM). A teaching case will be presented to apply these methodologies to undergraduates' mathematical modelling lessons. It is shown that teachers can use IBM SPSS Modeler to improve student's mathematical modelling competence by understanding and practicing the process of five-phase modelling.
first_indexed 2025-11-14T10:25:42Z
format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:25:42Z
publishDate 2015
publisher John Wiley & Sons, Inc.
recordtype eprints
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spelling curtin-20.500.11937-633422019-02-19T04:28:16Z Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence Xiao, X. Xu, Honglei Xu, S. IBM SPSS Modeler mathematical modelling competence visualize modelling This paper is concerned with the problem of improving undergraduate mathematical modelling competence in the current big data world. Firstly, we review the renowned teacher's seven-step, student's four-step and a six-step modelling cycles to explain mathematical modelling competence. The six-step modelling cycle is also used in Common Core State Standards for Mathematics (CCSSM) in the United States. Based on these previous modelling cycles, we propose a new five-phase modelling cycle by use of the tool named IBM SPSS Modeler in accordance with Cross Industry Standard Process for Data Mining (CRISP-DM). A teaching case will be presented to apply these methodologies to undergraduates' mathematical modelling lessons. It is shown that teachers can use IBM SPSS Modeler to improve student's mathematical modelling competence by understanding and practicing the process of five-phase modelling. 2015 Journal Article http://hdl.handle.net/20.500.11937/63342 http://onlinelibrary.wiley.com/doi/10.1002/cae.21632/epdf John Wiley & Sons, Inc. restricted
spellingShingle IBM SPSS Modeler
mathematical modelling competence
visualize modelling
Xiao, X.
Xu, Honglei
Xu, S.
Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence
title Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence
title_full Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence
title_fullStr Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence
title_full_unstemmed Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence
title_short Using IBM SPSS Modeler to Improve Undergraduate Mathematical Modelling Competence
title_sort using ibm spss modeler to improve undergraduate mathematical modelling competence
topic IBM SPSS Modeler
mathematical modelling competence
visualize modelling
url http://onlinelibrary.wiley.com/doi/10.1002/cae.21632/epdf
http://hdl.handle.net/20.500.11937/63342