Overview of AI Grading of Physics Olympiad Exams
Fuente:
arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866913819859615744 |
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| author | McGinness, Lachlan |
| author_facet | McGinness, Lachlan |
| contents | Automatically grading the diverse range of question types in high school physics problem is a challenge that requires automated grading techniques from different fields. We report the findings of a Systematic Literature Review of potential physics grading techniques. We propose a multi-modal AI grading framework to address these challenges and examine our framework in light of Australia's AI Ethical Principles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_02121 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Overview of AI Grading of Physics Olympiad Exams McGinness, Lachlan Artificial Intelligence Automatically grading the diverse range of question types in high school physics problem is a challenge that requires automated grading techniques from different fields. We report the findings of a Systematic Literature Review of potential physics grading techniques. We propose a multi-modal AI grading framework to address these challenges and examine our framework in light of Australia's AI Ethical Principles. |
| title | Overview of AI Grading of Physics Olympiad Exams |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2505.02121 |