Using Latent Semantic Analysis for Automated Grading Programming Assignments
Traditionally, computer programming assignments are graded manually by educators. As this task is tedious, timeconsuming and prone to bias, the need for automated grading tool is necessary to reduce the educators' burden and avoid inconsistency and favoritism. Recent researches have claimed...
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2011
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/16627/ http://ir.unimas.my/id/eprint/16627/1/Using%20Latent%20Semantic%20Analysis%20for%20Automated%20Grading%20%28abstract%29.pdf |
| _version_ | 1848838102077931520 |
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| author | Kartinah, Zen D.N.F, Awang Iskandar Ongkir, Linang |
| author_facet | Kartinah, Zen D.N.F, Awang Iskandar Ongkir, Linang |
| author_sort | Kartinah, Zen |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Traditionally, computer programming assignments are
graded manually by educators. As this task is tedious, timeconsuming
and prone to bias, the need for automated grading tool
is necessary to reduce the educators' burden and avoid
inconsistency and favoritism. Recent researches have claimed that
Latent Semantic Analysis (LSA) has the ability to represent
human cognitive knowledge to assess essays, retrieving
information, classification of documents and indexing. In this
paper, we adapt LSA technique to grade computer programming
assignments and observe how far it can be applied as an
alternative approach to traditional grading methods by human.
The grades of the assignments are generated from the cosine
similarity that shows how close students' assignments to the model
answers in the latent semantic vector space. The results show that
LSA is not able to detect orders of computer programming and
symbols; however, LSA is able to grade assignments faster and
consistently, which avoid bias and reduces the time spent by
human. |
| first_indexed | 2025-11-15T06:50:13Z |
| format | Article |
| id | unimas-16627 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:50:13Z |
| publishDate | 2011 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-166272017-06-13T07:42:19Z http://ir.unimas.my/id/eprint/16627/ Using Latent Semantic Analysis for Automated Grading Programming Assignments Kartinah, Zen D.N.F, Awang Iskandar Ongkir, Linang T Technology (General) Traditionally, computer programming assignments are graded manually by educators. As this task is tedious, timeconsuming and prone to bias, the need for automated grading tool is necessary to reduce the educators' burden and avoid inconsistency and favoritism. Recent researches have claimed that Latent Semantic Analysis (LSA) has the ability to represent human cognitive knowledge to assess essays, retrieving information, classification of documents and indexing. In this paper, we adapt LSA technique to grade computer programming assignments and observe how far it can be applied as an alternative approach to traditional grading methods by human. The grades of the assignments are generated from the cosine similarity that shows how close students' assignments to the model answers in the latent semantic vector space. The results show that LSA is not able to detect orders of computer programming and symbols; however, LSA is able to grade assignments faster and consistently, which avoid bias and reduces the time spent by human. IEEE 2011 Article PeerReviewed text en http://ir.unimas.my/id/eprint/16627/1/Using%20Latent%20Semantic%20Analysis%20for%20Automated%20Grading%20%28abstract%29.pdf Kartinah, Zen and D.N.F, Awang Iskandar and Ongkir, Linang (2011) Using Latent Semantic Analysis for Automated Grading Programming Assignments. International Conference on Semantic Technology and Information Retrieval (STAIR), 2011. ISSN ISBN: 978-1-61284-353-7 http://ieeexplore.ieee.org/document/5995769/ DOI: 10.1109/STAIR.2011.5995769 |
| spellingShingle | T Technology (General) Kartinah, Zen D.N.F, Awang Iskandar Ongkir, Linang Using Latent Semantic Analysis for Automated Grading Programming Assignments |
| title | Using Latent Semantic Analysis for Automated Grading Programming Assignments |
| title_full | Using Latent Semantic Analysis for Automated Grading Programming Assignments |
| title_fullStr | Using Latent Semantic Analysis for Automated Grading Programming Assignments |
| title_full_unstemmed | Using Latent Semantic Analysis for Automated Grading Programming Assignments |
| title_short | Using Latent Semantic Analysis for Automated Grading Programming Assignments |
| title_sort | using latent semantic analysis for automated grading programming assignments |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/16627/ http://ir.unimas.my/id/eprint/16627/ http://ir.unimas.my/id/eprint/16627/ http://ir.unimas.my/id/eprint/16627/1/Using%20Latent%20Semantic%20Analysis%20for%20Automated%20Grading%20%28abstract%29.pdf |