Frequently asked questions
Answers about mapping methodology, deliverables, AI use, human review, confidentiality and how engagements work.
Mapping and methodology
What does learning-outcome mapping involve?
We compare the learning outcomes of a sending course or program against those of a receiving one, classify each comparison as aligned, partial, no match or referred for expert review, and record the evidence for each finding. The result is a matrix and evidence trail that make the basis of an academic decision explicit.
What if course outlines are incomplete or out of date?
Source materials are reviewed before analysis begins. Missing or outdated information is flagged so it can be obtained or so its effect on the findings can be recorded. We do not fill gaps with assumptions.
Can you use our existing templates and criteria?
Yes. Where your institution already has approved criteria, templates or equivalency databases, the work is designed around them.
Deliverables and scope
What will we receive?
Typically a mapping matrix, an evidence trail, a gap and partial-match analysis, a review log and a summary report. For PLAR and transfer-credit work, deliverables may also include criteria, rubrics, templates and procedure guides. Formats are agreed at the outset.
How is an engagement scoped?
After an initial conversation, we propose a written scope covering purpose, materials, deliverables, review points, confidentiality terms and timeline. Many institutions start with a pilot on a defined sample.
How long does a project take?
It depends on the number and complexity of courses or programs, the state of the source materials and review availability. [Add indicative timeframes once confirmed, e.g. typical duration of a pilot.]
How are fees structured?
[Describe your pricing approach, e.g. fixed fee per agreed scope, or confirm that fees are quoted after scoping.]
AI use and human review
How do you use AI?
Where agreed, AI assists with reading and structuring outlines, suggesting candidate alignments, flagging ambiguity and drafting summaries. It is one tool within a documented method, never a substitute for review.
Does AI make credit or recognition decisions?
No. Every AI-assisted finding is confirmed, revised or rejected by a qualified person, and academic decisions remain with your institution's designated authority.
Who reviews the findings?
Findings are reviewed by qualified reviewers before they are reported. Depending on the agreement, these may be QACanada consultants, subject-matter experts or your own faculty. Items requiring disciplinary judgement are always referred to an appropriate expert.
Can we do the work without AI?
Yes. The method works with or without AI assistance. Whether and how AI is used is agreed during scoping.
Confidentiality
How is confidential information handled?
Handling terms are agreed during scoping and can include confidentiality agreements, de-identification, restrictions on tools and return or deletion of materials. [Confirm standard terms, storage location and retention.]
Will our data be used to train AI models?
No institutional or learner data is used to train public AI models. AI tools are used only where your institution has approved them and only within the agreed controls.
Working together
Do you work with institutions across Canada?
[Confirm geographic coverage, language capacity (e.g. English and French) and whether on-site work is available.]
Do you offer training?
Where appropriate, yes: practical guidance and training for staff who will run or review a specific workflow developed with us. QACanada does not sell general AI courses.
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