Educational data mining for structured mathematical questions

• Main Author: Kok, Mun Kiat
• Other Authors: Hui Siu Cheung
• Format: Final Year Project
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Computer science and engineering::Mathematics of computing::Numerical analysis
• Online Access: http://hdl.handle.net/10356/59265
• Institution: Nanyang Technological University

O-level elementary mathematics is a core subject in Singapore’s secondary school education. While the content is absolute, the questions are changing every year. A common question setting technique to test a student’s understanding of the subject is to obfuscate the question with confusing question texts. As such, solving O-level elementary math requires a different skill set of being able to identify concepts being tested before applying the mathematical skill to find the solution. The project aims to use latent semantic analysis and BM25F scoring algorithm in search engines to successfully identify patterns and key features of questions as well as classify a data base of O-level mathematic questions. The final product is a web application that allows users to view questions as well as use the front-end tools to help classify questions that they have.