Assessment Pilot Workflow Support
In assessment, a pilot needs to test whether the tool, workflow or redesigned process works inside the institution’s real conditions: marking, moderation, student communication, Moodle/platform integration, grade handling, exceptions, accessibility, support, governance and staff adoption.
This support helps universities design, run and evaluate assessment pilots with enough structure to produce useful evidence for decision-making.
Why this matters
Assessment pilots can become fragile when they are treated as technical tests only.
A tool may work well in a demo, a sandbox or one enthusiastic use case. That does not necessarily mean it is ready for wider use across departments, programmes or assessment types.
A pilot needs to show what changes in practice:
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whether workload is reduced, moved or increased;
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whether feedback quality improves;
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whether staff trust the process;
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whether students understand what is happening;
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whether Moodle/platform integration supports the workflow;
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whether evidence or analytics can be interpreted fairly;
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whether support needs are manageable;
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whether the process can scale.
Who this is for
This support is useful for:
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universities piloting AI-supported marking or feedback tools;
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institutions testing assessment platforms or Moodle workflow changes;
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digital education teams coordinating pilots across departments;
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assessment, registry or quality teams needing evidence for decisions;
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academic departments testing redesigned assessment approaches;
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project teams needing clearer pilot design, communication and evaluation.
What this can include
Support can include:
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clarifying the purpose and scope of the pilot;
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identifying the assessment types and workflows to test;
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mapping current and pilot-state workflows;
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defining roles, handoffs and decision points;
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designing staff and student communication;
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reviewing governance, data, consent and due diligence considerations;
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identifying human oversight expectations;
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designing feedback, marking and moderation processes;
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planning support routes and escalation points;
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creating evaluation questions and success criteria;
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gathering staff/student feedback;
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synthesising pilot findings into decision-support materials.
What a good pilot tests
A useful pilot should test more than basic functionality.
It should examine:
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staff setup time;
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student access and communication;
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marking and moderation workflow;
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feedback quality and usefulness;
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grade return and data movement;
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accessibility and accommodations;
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exception handling;
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support burden;
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staff confidence;
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student trust;
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whether workload is reduced or redistributed;
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whether the process can scale beyond the pilot context.
Live, sandbox or historical-submission pilots
Different pilot approaches answer different questions.
A sandbox pilot may be safer and useful for configuration, staff confidence, governance and evidence interpretation.
A live pilot may show how the process works under real assessment conditions, but it needs stronger communication, contingency planning and ethical care.
A pilot using historical submissions can support controlled testing, but may not reveal how staff and students experience the process in practice.
The right approach depends on what the institution needs to learn.
Typical outputs
Depending on scope, outputs can include:
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pilot design brief;
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current-state and pilot-state workflow maps;
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roles and responsibilities map;
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risk and governance checklist;
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staff/student communication plan;
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support and escalation plan;
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evaluation framework;
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pilot success criteria;
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findings summary;
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decision paper or next-step recommendations.
When this fits
This is a good fit when a university is considering or preparing a pilot, but needs clearer structure around workflow, risk, communication, adoption and evaluation.
It is also useful when a pilot has already begun and the team needs help making sense of what the pilot is actually showing.
Related support
See also:
Frequently asked questions
What should an assessment pilot test?
A useful pilot should test the workflow, workload, staff confidence, student communication, accessibility, grade return, support burden and evidence for decision-making, not only whether a tool functions.
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Should a pilot be live or sandboxed?
It depends on what the institution needs to learn. Sandbox pilots are safer for configuration and governance questions; live pilots show more about real staff and student experience.
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What makes AI assessment pilots difficult?
AI pilots often involve questions about human oversight, evidence interpretation, student trust, academic standards, workload, data, policy and staff adoption.
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What is the output of pilot workflow support?
Typical outputs can include a pilot design brief, workflow maps, risk checklist, communication plan, evaluation framework, success criteria and decision-support summary.