Educational data mining

Mathematics is one of the core subjects which all Secondary School students have to take in order to further on with their tertiary education or qualify for the workforce. With multiple subjects to focus before the examinations, educators and parents are finding the quickest and fastest method to be...

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Main Author: Toh, Jun Hao.
Other Authors: Hui Siu Cheung
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/51881
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-518812023-03-03T20:44:28Z Educational data mining Toh, Jun Hao. Hui Siu Cheung School of Computer Engineering DRNTU::Engineering Mathematics is one of the core subjects which all Secondary School students have to take in order to further on with their tertiary education or qualify for the workforce. With multiple subjects to focus before the examinations, educators and parents are finding the quickest and fastest method to best equip the students to face the examination challenge. Because of the demand for intelligent way of examination revision, the Education industry has already taken steps into investing on software systems that make revision more efficient. However, most systems do not offer features such as Tag, Topic Distribution Analysis, Topic Trend Analysis, and Question Clustering based on Tag Similarities. These features are found to be very useful in allowing students to identify the major topics through topic trend and distribution analysis, identifying the knowledge needed to attempt questions through useful knowledge tags, and finding similar questions through Tag searches or Question Clustering tools. The project aims to develop a web-based application that uses the “GCE Ordinary Level Additional Mathematics” subject as the platform for performing topic distribution and trend analysis, and also Tags and Clustering features. Dataset consists of questions and answers in text, images, and mathematical formula state. Visualization tools are also incorporated for better user readability. Bachelor of Engineering (Computer Science) 2013-04-15T04:11:43Z 2013-04-15T04:11:43Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/51881 en Nanyang Technological University 144 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Toh, Jun Hao.
Educational data mining
description Mathematics is one of the core subjects which all Secondary School students have to take in order to further on with their tertiary education or qualify for the workforce. With multiple subjects to focus before the examinations, educators and parents are finding the quickest and fastest method to best equip the students to face the examination challenge. Because of the demand for intelligent way of examination revision, the Education industry has already taken steps into investing on software systems that make revision more efficient. However, most systems do not offer features such as Tag, Topic Distribution Analysis, Topic Trend Analysis, and Question Clustering based on Tag Similarities. These features are found to be very useful in allowing students to identify the major topics through topic trend and distribution analysis, identifying the knowledge needed to attempt questions through useful knowledge tags, and finding similar questions through Tag searches or Question Clustering tools. The project aims to develop a web-based application that uses the “GCE Ordinary Level Additional Mathematics” subject as the platform for performing topic distribution and trend analysis, and also Tags and Clustering features. Dataset consists of questions and answers in text, images, and mathematical formula state. Visualization tools are also incorporated for better user readability.
author2 Hui Siu Cheung
author_facet Hui Siu Cheung
Toh, Jun Hao.
format Final Year Project
author Toh, Jun Hao.
author_sort Toh, Jun Hao.
title Educational data mining
title_short Educational data mining
title_full Educational data mining
title_fullStr Educational data mining
title_full_unstemmed Educational data mining
title_sort educational data mining
publishDate 2013
url http://hdl.handle.net/10356/51881
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