Dial Your Course

Goal

This started with a simple question: how does an online course show it delivers the student hours a credit promises? A credit carries a set number of student hours, and the syllabus commits to them. Online, that evidence lives in the course package itself, so a clean, consistent way to check it helps.

Course review is usually done by reading, one course at a time. Dial Your Course checks the countable things in a single, consistent pass and hands the course back with fixes ready to approve.

It answers three questions. Does the work fit the hours the credit allows? Are the objectives written in verbs a student can be observed performing? Is every outcome the course claims actually evidenced by something it grades? Assessment validity follows from there: which assignments could a model complete on its own, and what process evidence does the rubric already collect?

This did not begin with a rubric. It began with the checks performed by hand, cycle after cycle, as a peer and lead reviewer for Quality Matters and OSCQR. The tool automates the countable part of that review and declines to automate the part that takes judgment.

Audience

Faculty and instructional designers preparing an online course for launch or review. No technical background assumed.

Formal review comes once a year, and for most faculty it is the first time anyone reads their course closely. That is a hard moment to discover a missing alt attribute, an outcome that was never attached to a rubric, or a module that drifted past the hours the credit allows. This is a rehearsal for that review, not a replacement for it. It reports to you and nobody else. Nothing is submitted, scored, or sent to an administrator.

Process

Export the course from Canvas, drop the file in, choose the checks. Nineteen of them run. Every finding names the standard it comes from and where in the course to fix it. Approve the changes you want, and the tool writes them back and hands you a package ready to reimport, plus a short list of the few things only Canvas itself can do.

Your course content never leaves your browser. No account, no server, no vendor, and no AI reads your course. A Canvas export contains no student data by design, so none enters the tool, and nothing you drop in is uploaded, stored, or used to train any model.

It reports only what it can prove. A check that cannot be computed is never reported as a pass, and nothing changes without your approval.

Technology

• A browser-based tool: vanilla JavaScript, no backend, no account, no database.
• Reads a Canvas Common Cartridge (.imscc) export and writes a corrected package back, entirely on your own device.
• The nineteen checks are deterministic rules, not AI: seat hours, outcome alignment, accessibility, workload, AI-resistance. Your course is never sent to any AI to be read, stored, or used for training.
• Applies the SUNY OSCQR rubric alongside its own alignment and workload criteria.
• Optional AI is a future feature only, for the authentic-assessment module, and is designed to run solely through the institution’s sanctioned AI (for example a district Google agreement, under which institutional content is not retained and is not used to train the model). Opt-in, working from aggregate course information, never student data.
• Hosted on GitHub Pages.

Outcomes

The tool turns a review that used to happen by reading into one deterministic pass that names every finding and where to fix it. It catches the small, easy-to-miss things and surfaces them clearly: a missing alt attribute, an outcome not yet attached to a rubric, a module whose hours could be brought back in line with the credit.

It carries the countable part of a peer and lead reviewer’s Quality Matters and OSCQR practice into software while leaving the judgment calls to the person, and it hands back a corrected package ready to reimport. Nothing is submitted, scored, or seen by anyone but the person running it.

Status

A working prototype in testing, held as intellectual property with a demo available on request. It applies the SUNY OSCQR rubric under a Creative Commons license, alongside alignment and workload criteria of its own, and is not affiliated with or endorsed by SUNY. It runs entirely in the browser, no account and no upload. Questions? Drop me a note.