AI Assisted Grade justification in WISEflow at BI
THIS IS RELEVANT TO YOU BECAUSE:
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You work with assessment and want to understand how AI can support grade justification in a high‑stakes, compliance‑driven context.
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You need real evidence, based on assessor experience, of how AI performs when generating grade‑aligned, criteria‑based justification text.
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You’re exploring how AI can strengthen consistency, quality, and clarity of grade justifications without removing academic ownership.
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You’re evaluating whether AI can reduce workload, support tight delivery deadlines, and improve structure, while still requiring human oversight.
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You want insight into practical considerations such as workflow friction, prompt design, and what needs to be in place (e.g., good marking guidance) for AI support to work effectively.
A FIRST LOOK AT WHAT'S INSIDE...
This report uncovers insights from a quality‑first pilot at BI, where assessors tested UNIwise’s AI‑assisted Grade Justification module in WISEflow. The pilot was designed to answer a crucial question:
Can AI generate academically sound, criteria‑aligned justification text that assessors can trust and refine?
The answer, based on hands‑on experience across multiple exam flows, is encouraging. Assessors found that the AI produced strong, coherent draft arguments that often required only light editing. The tool helped articulate the difference between grade levels and provided a clearer structure for explaining why a student received a particular grade, one of the most persistent communication challenges in assessment.
Practical workflow findings are equally important. Although the prototype required manual copy‑paste, assessors still experienced value because the AI removed the “blank‑page problem” and made it easier to start drafting. With planned enhancements like one‑click insertion and prompt re‑use, future iterations are expected to significantly reduce friction and improve everyday usability. On an institutional level, the pilot highlights how AI‑supported justification can help meet strict turnaround expectations, such as Norway’s 14‑day deadline, by improving structure and reducing drafting effort, without compromising academic integrity.
For educators, programme leaders, and assessment teams evaluating the role of AI in feedback and compliance, this report offers grounded, evidence‑based insights into what already works well, what needs refinement, and how AI can meaningfully support assessment practice at scale.