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Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques

The identification of students’ learning style in learning mathematics is important for educators in choosing an effective teaching approach/methodology. Students from different field of studies to complete were asked the Index Learning Styles questionnaire to identify the student’s learning style o...

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Main Author: Mat Esa, Asmarizan
Format: Thesis
Language:English
English
Published: 2015
Subjects:
QA Mathematics
QA76 Computer software
Online Access:http://eprints.utem.edu.my/id/eprint/15877/1/DISCOVERING%20STUDENT%20LEARNING%20STYLES%20IN%20ENGINEERING%20MATHEMATICS%20AT%20POLITEKNIK%20MERLIMAU%20USING%20NEURAL%20NETWORK%20TECHNIQUES%20%2824%20pgs%29.pdf
http://eprints.utem.edu.my/id/eprint/15877/2/Discovering%20student%20learning%20styles%20in%20engineering%20mathematic%20at%20Politeknik%20Merlimau%20using%20neural%20network%20techniques.pdf
http://eprints.utem.edu.my/id/eprint/15877/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96223
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spelling my.utem.eprints.158772022-10-06T09:23:13Z http://eprints.utem.edu.my/id/eprint/15877/ Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques Mat Esa, Asmarizan QA Mathematics QA76 Computer software The identification of students’ learning style in learning mathematics is important for educators in choosing an effective teaching approach/methodology. Students from different field of studies to complete were asked the Index Learning Styles questionnaire to identify the student’s learning style of learning DBM1013 - Engineering Mathematics. This technique is used to consider their learning styles and how to improve students’ performance in learning DBM1013 – Engineering, Mathematics, the questionnaires were evaluated to identify the best learning styles used by students in learning Engineering Mathematics. However, the problem with this method is the time spent by students in answering questions and the accuracy of the results obtained. If questionnaires are too long, students tend to choose both answers arbitrarily instead of thinking about the result of the student’s learning style observed through analysis. This research identified the classification of students learning styles based on the Felder Silverman Learning dimension. Four learning dimension has been classified by using backpropagation neural networks. The algorithm has been run on training, validation and testing, training process data and 20 neurons. The result shows that the neural network is able to identify the students' learning styles according to the dimension with satisfying result. 2015 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/15877/1/DISCOVERING%20STUDENT%20LEARNING%20STYLES%20IN%20ENGINEERING%20MATHEMATICS%20AT%20POLITEKNIK%20MERLIMAU%20USING%20NEURAL%20NETWORK%20TECHNIQUES%20%2824%20pgs%29.pdf text en http://eprints.utem.edu.my/id/eprint/15877/2/Discovering%20student%20learning%20styles%20in%20engineering%20mathematic%20at%20Politeknik%20Merlimau%20using%20neural%20network%20techniques.pdf Mat Esa, Asmarizan (2015) Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques. Masters thesis, Universiti Teknikal Malaysia Melaka. https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96223
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
English
topic QA Mathematics
QA76 Computer software
spellingShingle QA Mathematics
QA76 Computer software
Mat Esa, Asmarizan
Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
description The identification of students’ learning style in learning mathematics is important for educators in choosing an effective teaching approach/methodology. Students from different field of studies to complete were asked the Index Learning Styles questionnaire to identify the student’s learning style of learning DBM1013 - Engineering Mathematics. This technique is used to consider their learning styles and how to improve students’ performance in learning DBM1013 – Engineering, Mathematics, the questionnaires were evaluated to identify the best learning styles used by students in learning Engineering Mathematics. However, the problem with this method is the time spent by students in answering questions and the accuracy of the results obtained. If questionnaires are too long, students tend to choose both answers arbitrarily instead of thinking about the result of the student’s learning style observed through analysis. This research identified the classification of students learning styles based on the Felder Silverman Learning dimension. Four learning dimension has been classified by using backpropagation neural networks. The algorithm has been run on training, validation and testing, training process data and 20 neurons. The result shows that the neural network is able to identify the students' learning styles according to the dimension with satisfying result.
format Thesis
author Mat Esa, Asmarizan
author_facet Mat Esa, Asmarizan
author_sort Mat Esa, Asmarizan
title Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
title_short Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
title_full Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
title_fullStr Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
title_full_unstemmed Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
title_sort discovering student learning styles in engineering mathematic at politeknik merlimau using neural network techniques
publishDate 2015
url http://eprints.utem.edu.my/id/eprint/15877/1/DISCOVERING%20STUDENT%20LEARNING%20STYLES%20IN%20ENGINEERING%20MATHEMATICS%20AT%20POLITEKNIK%20MERLIMAU%20USING%20NEURAL%20NETWORK%20TECHNIQUES%20%2824%20pgs%29.pdf
http://eprints.utem.edu.my/id/eprint/15877/2/Discovering%20student%20learning%20styles%20in%20engineering%20mathematic%20at%20Politeknik%20Merlimau%20using%20neural%20network%20techniques.pdf
http://eprints.utem.edu.my/id/eprint/15877/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96223
_version_ 1746213409623375872
score 13.211869

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