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Christopher Ross

For colleges and universities

AI in teaching review: policy, student data, and accountability

Artificial intelligence (AI) is already in courses and learning platforms, often ahead of the policy meant to cover it. I review what’s happening, where student data goes, and who answers for it when it goes wrong, and you get a plain written report your committees can act on.

Book a 20-minute discovery call Send the project brief instead →

$4,800 CAD flat · ten working days · credited in full toward follow-on work

Before asking where AI adds value, someone has to own it once it’s inside the course. A lot of policies don’t say who that is yet.

Delivery context: MA candidate in Learning and Technology at Royal Roads University, researching how AI should be governed inside learning environments. Curriculum developer and instructor at the M.L. Campbell Training Centre, where I developed and deliver AI-productivity training. Former Director of Technology at Yorkville University. Writer of AI Learning, Keeping It Human, a weekly read on the evidence behind AI in learning.

I don’t resell AI platforms or take a cut from the vendors I review, and the report is yours to use however you like, including to decide that the right move is to do less.

Start with the review

Ten working days, $4,800 CAD flat, a written report, and a debrief with the people who need to hear it.

Book a 20-minute call

What the review covers

  • Policy against practice. What your AI policy says, and what faculty and students are doing, course by course, in the sample we agree on.
  • The tools themselves. Which AI tools are licensed, built into your learning platform, or simply in use, what each one does with student work and data, and where that data goes.
  • Accountability. Who decides a tool is allowed, who reviews what it does, and who answers to a student or an instructor when it gets something wrong.
  • Evidence. What each vendor claims, set against the independent evidence, including where there isn’t any yet.

What you get

  • A written report with findings in priority order, each tied to what I saw and what it would take to fix.
  • A draft governance outline your committee can adapt: roles, review points, and the questions to ask before the next tool is approved.
  • A 60-minute debrief with whoever needs to hear it: a teaching and learning centre, an academic committee, IT, or all three in one room.

The fee is $4,800 CAD flat for ten working days. If you go on to further work with me, it’s credited in full.

Who this is for

  • Colleges and universities with AI already in use, whether or not a policy has caught up with it.
  • Teaching and learning centres that need an outside view before recommending a tool or a rule.
  • Institutions about to add AI features to a learning platform and want the accountability questions answered first.

Who this is not for

  • Choosing an AI-detection tool. The false-positive evidence keeps me from recommending one; if you already use one, the review looks at it like any other tool.
  • Signing off on a decision that’s already been made. The review is most useful while you can still change course.
  • Legal advice. The review gives your privacy office and counsel the facts they need; it doesn’t replace them.

How this connects to the rest of the system

  • If AI is grading, recommending, or tutoring inside the platform, the review looks at the learning platform itself, because that’s where the accountability has to be built.
  • An AI tool a student can’t use with a screen reader is a barrier, not a support, so accessibility is part of every tool the review looks at.
  • The evidence side of the review draws on the reading I do every week for the newsletter.

Find out what’s actually happening before you decide what to do about it.

Ten working days, a written report, and a debrief. $4,800 CAD flat, credited in full toward follow-on work.

Book a 20-minute discovery call

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Common questions

No. I map where student data goes and which terms govern it, and I flag the questions your privacy office and counsel will want answered. The legal judgement stays with them.

Does it matter which learning platform we use?

No. The review looks at the AI in and around whatever you run. My own build record is on Moodle and LearnDash, so for Brightspace or Canvas I work from your configuration and the vendor’s documentation.

Do you work with institutions outside Ontario?

Yes. The review is done remotely, so location isn’t a barrier.