Thank you, Tracy, for raising such an important question!
Grading at scale while maintaining meaningful, personalised feedback is one of higher education's biggest challenges.
We've been exploring this through EduGrade AI (https://app.edugradeai.com/ ), an educator-controlled, AI-assisted assessment and feedback platform developed through research at Queen Mary University of London.
Our approach combines AI efficiency with human academic judgement:
Rubric-aligned feedback: AI generates draft feedback and indicative scores based on educator-defined assessment criteria.
Human oversight: Educators review, refine and approve feedback, retaining full responsibility for final grading decisions.
Scalability: Our research and pilots have involved over 1,000 student submissions, with typical grading-time savings of approximately 50–60%.
Meaningful engagement: By reducing repetitive marking tasks, educators can dedicate more time to individual student support, deeper feedback conversations and addressing common misconceptions.
We've also been exploring integration with institutional learning management systems and responsible AI practices, including transparency, privacy and accountability.
For me, the key question is not simply how AI can grade faster, but how it can help educators provide better feedback and create more opportunities for meaningful human interaction.
I'd be interested to hear how other institutions are approaching AI-assisted assessment.
Looking forward to learning from this community!
