Survey and Analysis for the Challenges in Computer Science to the Automation of Grading Systems Article Swipe
Joan Lu
,
Bhavya Krishna Balasubramanian
,
Mike Joy
,
Qiang Xu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3748521
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3748521
Assessment is essential to educational system. Automatic grading reduces the time and effort taken by tutors to assess the answers written by the students. To understand recent computational methods used for automatic grading, a review has been conducted. 4,084 articles were initially identified using a keyword search. After filtering, the number was reduced to 57. It was found that statistical models are normally used in Automatic-Short-Answer-Grading (ASAG); vector-based similarity measures are the most popular among projects; pilot datasets are mostly used; standard datasets for evaluation are missing. Evidence shows that machine learning and deep learning are most popularly adopted methods and generative AI, e.g., LLMs and ChatGPT are also jump to the chance, which indicates that integrating AI in education is an inevitable trend. Also, most investigations prefer to adopt multiple approaches to improve computational quality, dataset analysis, and evaluation results. The identified research gaps will be a useful reference guide to users/researchers beneficial to formative/summative assessment. We concluded that the presented outcome, analysis and discussions are informative to academia and pedagogical practitioners who are interested in further developing/using ASAG systems. Although research into ASAG is still rudimentary, it is a promising area with impact on academic circles/commercially educational markets.
Related Topics
Concepts
Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.1145/3748521
- OA Status
- green
- References
- 110
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4412393299Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3748521Digital Object Identifier
- Title
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Survey and Analysis for the Challenges in Computer Science to the Automation of Grading SystemsWork title
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-14Full publication date if available
- Authors
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Joan Lu, Bhavya Krishna Balasubramanian, Mike Joy, Qiang XuList of authors in order
- Landing page
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https://doi.org/10.1145/3748521Publisher landing page
- Open access
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://pure.hud.ac.uk/en/publications/bc2b1310-a25f-4ae9-9c86-eb436de27398Direct OA link when available
- Concepts
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Computer science, Grading (engineering), Automation, Software engineering, Data science, Civil engineering, Mechanical engineering, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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110Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W6607408211, https://openalex.org/W4361026235, https://openalex.org/W2883991406, https://openalex.org/W2585620645, https://openalex.org/W2573047552, https://openalex.org/W2808827600, https://openalex.org/W2992137506, https://openalex.org/W3031374736, https://openalex.org/W2914823529, https://openalex.org/W3118615836, https://openalex.org/W2482062219, https://openalex.org/W117221489, https://openalex.org/W3093526511, https://openalex.org/W4319985906, https://openalex.org/W4400869639, https://openalex.org/W1967082761, https://openalex.org/W6739901393, https://openalex.org/W2963026768, https://openalex.org/W4402159845, https://openalex.org/W2705238372, https://openalex.org/W3106622878, https://openalex.org/W3005700362, https://openalex.org/W4388194978, https://openalex.org/W4400811617, https://openalex.org/W4393218999, https://openalex.org/W4391466322, https://openalex.org/W4399915777, https://openalex.org/W4400142690, https://openalex.org/W4391825111, https://openalex.org/W4401214065, https://openalex.org/W2901183774, https://openalex.org/W4205923277, https://openalex.org/W2933748549, https://openalex.org/W2972297345, https://openalex.org/W2992681517, https://openalex.org/W3125048963, https://openalex.org/W6730827622, https://openalex.org/W2900327614, https://openalex.org/W2594607895, https://openalex.org/W2896474819, https://openalex.org/W3209132994, https://openalex.org/W2739522917, https://openalex.org/W2223588359, https://openalex.org/W2171313960, https://openalex.org/W2966714320, https://openalex.org/W2997323475, https://openalex.org/W176211028, https://openalex.org/W2165403938, https://openalex.org/W2121184547, https://openalex.org/W2082815071, https://openalex.org/W2739692012, https://openalex.org/W3023321459, https://openalex.org/W2474948357, https://openalex.org/W3038915749, https://openalex.org/W2991492811, https://openalex.org/W3039412488, https://openalex.org/W4285223017, https://openalex.org/W4315750672, https://openalex.org/W2951400647, https://openalex.org/W4382562062, https://openalex.org/W4365801579, https://openalex.org/W2327620174, https://openalex.org/W2028776121, https://openalex.org/W2500036977, https://openalex.org/W2946428880, https://openalex.org/W2901451752, https://openalex.org/W2809666916, https://openalex.org/W4200387115, https://openalex.org/W2900237823, https://openalex.org/W3039640308, https://openalex.org/W3128469791, https://openalex.org/W2970812170, https://openalex.org/W3118846933, https://openalex.org/W2908596472, https://openalex.org/W2578287498, https://openalex.org/W2290116166, https://openalex.org/W4323520727, https://openalex.org/W2025719462, https://openalex.org/W4286282840, https://openalex.org/W4365807638, https://openalex.org/W2789863594, https://openalex.org/W4387724657, https://openalex.org/W3194212642, https://openalex.org/W2966193711, https://openalex.org/W4400350333, https://openalex.org/W4409347290, https://openalex.org/W4389500600, https://openalex.org/W6929576297, https://openalex.org/W6870089796, https://openalex.org/W4255554277, https://openalex.org/W2911666826, https://openalex.org/W2497133662, https://openalex.org/W2587103442, https://openalex.org/W4385570141, https://openalex.org/W4247603384, https://openalex.org/W3101613385, https://openalex.org/W4400810722, https://openalex.org/W3034730645, https://openalex.org/W4323347493, https://openalex.org/W3104125207, https://openalex.org/W4237392069, https://openalex.org/W3215154842, https://openalex.org/W4391559941, https://openalex.org/W2607403128, https://openalex.org/W4292970115, https://openalex.org/W2755087487, https://openalex.org/W2957937874, https://openalex.org/W2733628661, https://openalex.org/W4388351329, https://openalex.org/W2605961645 |
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| abstract_inverted_index.The | 141 |
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| abstract_inverted_index.tutors | 15 |
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| abstract_inverted_index.answers | 19 |
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