Dataset adaption and evaluation on NLP models for automated grading system
With the development of artificial intelligence in recent years, NLP (Natural Language Processing) has become increasingly mature, and one of its applica tions includes AGS (Automated Grading System). AGS plays a very important role in today’s educational learning by assigning a specific score to...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/169103 |
| _version_ | 1826127887163457536 |
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| author | Jiang, Yuxun |
| author2 | Lihui Chen |
| author_facet | Lihui Chen Jiang, Yuxun |
| author_sort | Jiang, Yuxun |
| collection | NTU |
| description | With the development of artificial intelligence in recent years, NLP (Natural
Language Processing) has become increasingly mature, and one of its applica tions includes AGS (Automated Grading System). AGS plays a very important
role in today’s educational learning by assigning a specific score to a given
response to a specific question. And how to improve the accuracy of AGS be comes a crucial issue. One of them is how to process at the data level to make
the results better, and the other is how to choose a better language model to
achieve better results. In this dissertation, we compare the data and network
structure to illustrate how to train a better AGS system. |
| first_indexed | 2024-10-01T07:15:52Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/169103 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:15:52Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1691032023-07-04T15:36:44Z Dataset adaption and evaluation on NLP models for automated grading system Jiang, Yuxun Lihui Chen School of Electrical and Electronic Engineering ELHCHEN@ntu.edu.sg Engineering::Electrical and electronic engineering With the development of artificial intelligence in recent years, NLP (Natural Language Processing) has become increasingly mature, and one of its applica tions includes AGS (Automated Grading System). AGS plays a very important role in today’s educational learning by assigning a specific score to a given response to a specific question. And how to improve the accuracy of AGS be comes a crucial issue. One of them is how to process at the data level to make the results better, and the other is how to choose a better language model to achieve better results. In this dissertation, we compare the data and network structure to illustrate how to train a better AGS system. Master of Science (Computer Control and Automation) 2023-06-30T04:15:36Z 2023-06-30T04:15:36Z 2023 Thesis-Master by Coursework Jiang, Y. (2023). Dataset adaption and evaluation on NLP models for automated grading system. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/169103 https://hdl.handle.net/10356/169103 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Jiang, Yuxun Dataset adaption and evaluation on NLP models for automated grading system |
| title | Dataset adaption and evaluation on NLP models for automated grading system |
| title_full | Dataset adaption and evaluation on NLP models for automated grading system |
| title_fullStr | Dataset adaption and evaluation on NLP models for automated grading system |
| title_full_unstemmed | Dataset adaption and evaluation on NLP models for automated grading system |
| title_short | Dataset adaption and evaluation on NLP models for automated grading system |
| title_sort | dataset adaption and evaluation on nlp models for automated grading system |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/169103 |
| work_keys_str_mv | AT jiangyuxun datasetadaptionandevaluationonnlpmodelsforautomatedgradingsystem |