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|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.||URI:||http://hdl.handle.net/10356/51881||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Student Reports (FYP/IA/PA/PI)|
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