Methodology

How work proceeds from scoping to final delivery. The same disciplined sequence applies whether the task is a single course comparison or a program-level review.

Seven stages, each with a record

Each stage has a defined output, so progress is visible and every finding can be traced back to its source and reviewer.

  1. Scoping

    Agree the purpose, the decision the work supports, who owns that decision, the materials in scope, timelines, confidentiality terms and how AI assistance may be used.

    Output: written scope and agreed definitions
  2. Source-material review

    Collect outlines, outcomes, assessment information and calendars. Check them for completeness, version and currency, and flag gaps before analysis starts.

    Output: source inventory and issues list
  3. Structured analysis

    Normalize outcomes into comparable statements, noting level, scope and assessment. AI assistance may be used here, within agreed controls.

    Output: structured outcome sets
  4. Mapping

    Compare outcomes systematically and classify each as aligned, partial, no match or referred for expert review, citing the supporting evidence.

    Output: draft mapping matrix and evidence trail
  5. Quality assurance

    Consistency checks across the full set, sampling against independent comparison, and verification of every citation.

    Output: QA notes and corrections
  6. Expert review

    Qualified reviewers, from QACanada or your institution as agreed, confirm, revise or reject findings and resolve referred items.

    Output: validated matrix and review log
  7. Reporting and delivery

    Summary report, limitations and recommended next steps, delivered in agreed formats and walked through with your team.

    Output: final deliverables and handover

Principles behind the method

Traceable

Every finding links to its source text, its rationale and the person who confirmed it.

Consistent

Definitions and thresholds are fixed in advance and applied uniformly.

Proportionate

The depth of analysis matches the stakes and volume of the decision.

Human-led

AI may assist the analysis; qualified people validate it and the institution decides.

Confidentiality and data handling

Course materials are often unpublished, and PLAR files can contain personal information. Handling terms are agreed during scoping and may include a confidentiality agreement, de-identification of learner information, restrictions on which tools may be used, and return or deletion of materials at the end of the engagement.

[Confirm your standard confidentiality terms, where files are stored, retention periods and whether you will sign institutional agreements.]

Apply the method to your context

We can start with a pilot on a defined sample so you can see the method and outputs before committing further.