Performance tracking and analytics of education background and past performance to predict future academic performance
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 com...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/10356/67059 |
| _version_ | 1811686030706737152 |
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| author | Ng, Benjamin |
| author2 | Chan Syin |
| author_facet | Chan Syin Ng, Benjamin |
| author_sort | Ng, Benjamin |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T04:53:56Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/67059 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:53:56Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/670592023-03-03T20:23:11Z Performance tracking and analytics of education background and past performance to predict future academic performance Ng, Benjamin Chan Syin School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval 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. Bachelor of Engineering (Computer Science) 2016-05-11T04:59:37Z 2016-05-11T04:59:37Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67059 en Nanyang Technological University 38 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Ng, Benjamin Performance tracking and analytics of education background and past performance to predict future academic performance |
| title | Performance tracking and analytics of education background and past performance to predict future academic performance |
| title_full | Performance tracking and analytics of education background and past performance to predict future academic performance |
| title_fullStr | Performance tracking and analytics of education background and past performance to predict future academic performance |
| title_full_unstemmed | Performance tracking and analytics of education background and past performance to predict future academic performance |
| title_short | Performance tracking and analytics of education background and past performance to predict future academic performance |
| title_sort | performance tracking and analytics of education background and past performance to predict future academic performance |
| topic | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval |
| url | http://hdl.handle.net/10356/67059 |
| work_keys_str_mv | AT ngbenjamin performancetrackingandanalyticsofeducationbackgroundandpastperformancetopredictfutureacademicperformance |