Principled Design of Interpretable Automated Scoring for Large-Scale Educational Assessments
Published:Nov 21, 2025 09:19
•1 min read
•ArXiv
Analysis
This article likely discusses the design principles for creating AI systems that can automatically score educational assessments. The focus is on interpretability, meaning the system's reasoning should be understandable, which is crucial for trust and feedback. The scale of the assessments suggests a focus on efficiency and potentially personalized learning. The use of 'principled design' implies a focus on ethical considerations and fairness in the scoring process.
Key Takeaways
- •Focus on interpretable AI for educational assessment.
- •Addresses the need for fairness and ethical considerations in automated scoring.
- •Likely explores methods for large-scale assessment.
- •Aims to improve trust and provide feedback through understandable AI reasoning.
Reference
“”