Towards Explainable and Accountable Automatic Educational Text Scoring Systems

This thesis adopts a human-centered approach to explore how ATS in educational settings can be enhanced to better serve the humans involved (e.g., students and educators). Specifically, guided by this principle, the thesis not only investigates accuracy but also examines ways to improve three additional aspects: labeling costs, explainability, and the detection of AI-generated content.