When AI Supports Assessment: Transparency and Educator Oversight

Introduction

Automated scoring and feedback can scale support for learners and instructors, but they introduce questions of transparency and control. Educators need to understand how systems work, when to trust or override them, and how to combine AI output with human judgment. This article outlines principles for transparent AI-assisted assessment.

How the System Works

Transparency starts with a clear, accessible description of what the system does: which inputs it uses, how scores or feedback are produced, and what the outputs represent. Technical documentation and plain-language summaries help instructors interpret results and explain them to learners and stakeholders. Black-box descriptions undermine trust and appropriate use.

When to Override or Supplement

AI output may be wrong, incomplete, or misaligned with local standards. Systems should support educator override and manual adjustment where policy allows. Clear workflows for flagging, reviewing, and correcting automated results ensure that human judgment remains in the loop for high-stakes or borderline decisions.

Interpretation and Action

Scores and feedback are only useful if they lead to appropriate action. Dashboards and reports should highlight what is actionable (e.g. areas of weakness, suggested next steps) without prescribing decisions that belong to the educator. Training and support help instructors integrate AI-assisted data into existing assessment and instructional practices.

Accountability and Governance

Organisations using AI-assisted assessment should define roles and responsibilities: who is accountable for score validity, who may override results, and how disputes are resolved. Governance should cover data use, model updates, and equity monitoring so that automation supports rather than undermines institutional standards.

Conclusion

AI can support assessment effectively when systems are transparent, override and supplementation are supported, and human judgment remains central to interpretation and action. Clear documentation, workflows, and governance help educators use automated tools appropriately and maintain accountability.

References

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3. American Educational Research Association et al. (2014). Standards for Educational and Psychological Testing. Washington, DC: AERA.