Deploy GenAI for continuous longitudinal analysis of student development to enable ipsative feedback, and scaffold feedback literacies for all students¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The authors recommend starting from known feedback challenges and asking what role GenAI can play. Because assessors rarely follow students across modules, a barrier to ipsative feedback exists; they propose GenAI systems that track students' skills, thinking, and conceptual understandings developing over time rather than grading assignments in isolation. They further argue future feedback processes must scaffold feedback literacies and evaluative judgement so all students can critically evaluate and act upon multiple modes of feedback, to avoid amplifying attainment differentials.

Design Implications¶

Context¶

Requirements¶

• Design of GenAI integration must be intentional and recognise established conceptualisations of feedback; equity of access and respect for students who object to GenAI must be ensured

Constraints¶

• The authors warn that failure to develop evaluative judgement risks amplifying existing attainment differentials through Matthew Effects

Target Learners¶

• higher education students

Target Learning Goals¶

• evaluative judgement
• feedback literacies
• understanding of skill development over time

Related Strategies¶

• Use automated collaboration assessments as scaffolds for reflection rather than ground truth
• Institutional governance should establish practical conditions supporting AI literacy, learner agency, and critical evaluation rather than relying on prohibition and detection
• Staged institutional implementation: audit interactions, map to teaming levels, build AI literacy, co-design, and evaluate iteratively
• Use longitudinal role dynamics to inform group formation, role assignment, and targeted support in collaborative learning

Examples¶

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Key Sources¶

• Winstone, N. E., Gravett, K., Bearman, M., Noble, C., Jensen, L. X., Jones, A., & Nicola-Richmond, K. (2026). The care-full craft of feedback in an age of generative AI. Assessment & Evaluation in Higher Education, 51(5), 911-927. https://doi.org/10.1080/02602938.2026.2643333