Overview of AI Grading of Physics Olympiad Exams
This work addresses the problem of efficient and ethical grading for high school physics education, but it appears incremental as it builds on existing techniques without reporting specific performance gains.
The paper tackles the challenge of automatically grading diverse high school physics problems by proposing a multi-modal AI grading framework, based on a systematic literature review of potential techniques and examined in light of Australia's AI Ethical Principles.
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.