Please use this identifier to cite or link to this item:
Title: Educational data mining
Authors: Toh, Jun Hao.
Keywords: DRNTU::Engineering
Issue Date: 2013
Abstract: 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.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
4.48 MBAdobe PDFView/Open

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.