Nearly 40,000 Discussion Posts Later: A MyTA Case Study

Trish C. teaches online at a large private university in the Southwest — up to nineteen sections at once, on top of a consulting job that keeps her on client sites all day. Her courses used to run on a brutal clock: into the classroom at six in the morning, locked out by her day job until mid-afternoon, and then the backlog.

"I can't get back in until 2:30, three o'clock in the afternoon — and there's like twelve messages waiting. People are waiting for me to unlock things all day long."

Nights weren't hers either: back at the hotel at ten, then "at least an hour doing stuff." The stuff was grading. Discussion boards are where online courses live, and every post has to be read, scored against a rubric, and answered when points come off. Across nineteen sections, that isn't a workload. It's a lifestyle.

Now the grading is done before she opens her laptop

MyTA connects to her LMS and grades with her rubrics — her word counts, her citation rules, her per-question quirks, her phrasing. While she's on a client site, it reads the boards, scores every post, grades the essays criterion by criterion, and drafts the feedback in her voice. What used to be an evening of reading and typing is now a review queue: she opens it, checks the scores, publishes.

"So it looks like I'm in the classroom during the day. Students are being responded to."

That's the part that matters to her students, who get feedback the same day instead of at midnight — and to her chair, who sees an instructor present in every section, every day.

Nothing ever reaches a student on its own. Grades publish to the LMS only when she publishes them. The assistant grades; the instructor decides.

Twenty weeks, measured by the platform

Put the big number in human terms: at a conservative three minutes per post — read it, score it against the rubric, write the feedback — 39,881 posts is roughly two thousand hours of grading attention. MyTA produced the first draft of all of it; Trish reviewed and published on her schedule instead of the backlog's.

Her students noticed the difference before anyone told them anything had changed. "I had another student yesterday that was like, oh my god, your feedback is so good."

The hardest customer it will ever have

Trish is not an easy grader of graders. Early on she ran the same assignment through MyTA and through the grading workflow she had built for herself — and told us hers was stricter. Then she held MyTA to that standard: citation checking on every assignment, no exceptions ("I could actually get in a lot of trouble for passing students on without checking their citations"), scores that always match their feedback, rules that differ from one discussion question to the next.

MyTA absorbed all of it, because that's the design: the instructor's standards are the spec, not a suggestion. The verdict on whether it got there isn't a quote — it's twenty unbroken weeks and 1,616 graded essays after the toughest user it will ever meet stopped grading the grader and went back to teaching.

What the hours are for

"Since getting the grading locked down really well, I'm able to actually go into the forums and actually respond to students."

And, unprompted, in the same recorded session — the sentence that is the whole product:

"MyTA should free up the time that I have to spend grading and give me back to the students."

Try it against your own rubric

MyTA connects to your LMS, grades with your rubrics in your voice, and never publishes a grade without you. If you want to feel the first step before creating anything, start with the free instructor tools — upload the rubric you already have and see it become something a system can grade with: myta.courseops.ai/free-tools. When you're ready, MyTA is free to try with one course at myta.courseops.ai.

*Course-level aggregates only; no student data appears in this study or was used in preparing it. Instructor identified with permission as Trish C.; institution described at her preference. Quotes are from recorded working sessions, May-June 2026, lightly edited for clarity. The hours figure is illustrative arithmetic on the stated per-post assumption, not a platform measurement.*