Papers by Joseph Tey

1 papers
Interpretability from the Ground Up: Stakeholder-Centric Design of Automated Scoring in Educational Assessments (2026.findings-acl)

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Challenge: Despite increasing demand for transparency and interpretability, the field has yet to develop a widely accepted solution for interpretable automated scoring to be used in large-scale real-world assessments.
Approach: They propose to develop four principles of interpretability targeted at assessment stakeholder groups to address the need for transparency and interpretability in automated scoring.
Outcome: The proposed framework outperforms many uninterpretable scoring methods in terms of scoring accuracy and is, on average, within 0.06 QWK of the uninterprétable SOTA.

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