Use AI to draft student-lifecycle tests for an Ellucian Student migration

Start with a process staff can follow from beginning to end: registration through account charges, a course drop through any required adjustment, or an application update through an interface and report. Name the offices, systems and reports involved. Then identify who can approve the expected result at each handoff.

Seton Hall's July 2026 Banner SaaS update describes functional testing alongside preparations for cross-functional, end-to-end tests. That dated project example is a useful prompt to test how offices work together. It doesn't establish how other institutions have configured their systems.

For the Banner path, Ellucian uses the name Ellucian Student powered by Banner. Confirm your contracted target, deployment, modules and release before writing system-specific steps. The method here proposes a separately approved AI drafting tool; it doesn't describe a native Ellucian testing feature.

Have the test lead collect the current requirement IDs, approved process descriptions, relevant academic-calendar rules, role descriptions and interface specifications. Ask each office to confirm the version it approved. Mark unresolved decisions clearly; a draft policy is not a rule the test should enforce.

Use synthetic students and transactions. Don't paste student records, financial-aid documents, credentials or production extracts into an unapproved tool. Follow the institution's approved handling arrangements for any internal requirements.

Ask the tool to produce a test ID, requirement ID, starting conditions, user role, steps, expected results, records to compare and responsible reviewer. Require a separate list of unanswered questions. If the source doesn't define a fee adjustment or eligibility condition, the draft must identify the missing rule.

A useful instruction is: 'Draft normal and exception cases only from these approved requirements. Cite the requirement ID for each expected result. Mark missing details for the named office to answer. Do not invent screens, fields, API behavior or institutional rules.'

The Registrar checks registration rules and effective dates. Student Accounts checks charges, adjustments and balances against approved calculations. Financial Aid reviews any aid-related result within its authority. IT checks the interface sequence, supported access and error handling against the agreed specification.

Review one draft together before generating dozens more. Remove duplicated cases and split any case that combines unrelated actions. Ask whether another tester could follow the steps and identify a pass or failure without guessing what 'works correctly' means.

NIST's voluntary AI Risk Management Framework calls for testing in conditions representative of intended use and recognizes the role of human judgment. For this proposed drafting method, keep staff's corrections and unanswered questions so the test lead can decide whether the tool is helping.

Use the sequence below for each group of tests. Approval of a test case authorizes its use in the agreed test environment; the project still needs actual execution results and its normal release decision.

The examples below are suggested checks, not universal Ellucian behavior. Include only the functions and interfaces in your migration scope. Put your actual requirement IDs, report names and expected values into the test cases.

Illustrative example: a synthetic student drops a course. The Registrar specifies the test date and expected enrollment record. Student Accounts calculates the account result under the approved policy. If Financial Aid must review the change, that office defines its own check. IT and the report owner then trace the agreed downstream records. The AI draft should not decide the refund or aid outcome.

Run approved cases in the designated test environment using the agreed configuration and test data. Record the build or release, configuration version, test-data reference, tester, execution time and actual result. Attach the relevant report, transaction reference or error message in approved project storage.

Keep monetary calculations and control totals in approved rules, queries or calculation tools. AI may help draft a description of a difference, but staff must verify the underlying amounts and decide what correction is permitted.

For a failure, assign an owner and record what must change. Retest the corrected case and any connected process the change could affect. A case that wasn't run, or is waiting on an unresolved rule, remains open.

After a small trial, compare the drafts with staff's corrections and record the time spent reviewing them. Continue, revise the prompt or stop based on that result. Bring the completed tests and unresolved issues to the institution's normal go-live review. Altioras Global's AI services can help scope this drafting work with the staff who own the processes.