Performance tracking and analytics of education background and past performance to predict future academic performance
Date of Issue2016
School of Computer Engineering
Research on what makes a good student has been going on for many years, in various ways. While successful, the work done is not replicable as various schools take in different students from all sorts of backgrounds. This report aims to identify the relationship between key attributes in students coming from Polytechnics and the grades they obtain while in NTU. Over 600 tuples of student information were analyzed to reveal which input had the highest impact on the grades obtained. Techniques such as correlation and graph analysis using scatter plots and pie charts were utilized over the students’ Poly, Diploma, PolyGPA, EMaths and UScore. The results indicated strong relationships between certain input vectors and the students’ grades including the school and diploma that they originally came from. The analysis results may aid schools looking to take in candidates for programming courses in making a more informed decision on which candidate would be more likely to succeed in its courses. It can also aid schools in avoiding students who have do not have the aptitude for programming based courses.
DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
Final Year Project (FYP)
Nanyang Technological University