When Grading Becomes the Real Homework: Professors’ Invisible Labor
By Marina Kidron
We often hear students say they are drowning in home assignments, and to be fair, they’re not wrong. But there is a quieter, invisible workload that rarely makes the headlines: professors spending far more time grading, giving feedback, and managing home assignments than students might imagine.
The Hidden Load
At first glance, it might seem like students carry the bulk of the burden: reading, writing, revising. But dig deeper, and a different reality emerges:
Each assignment, especially essays or open-ended projects, requires careful reading. A professor must understand student arguments, check for logic and coherence, find factual or conceptual errors, and often compare across multiple submissions to ensure consistency in evaluation.
Real feedback is not a one-liner. Good feedback means pointing out what works, what doesn’t, offering suggestions, and often providing mini-lessons in writing, reasoning, or methodology.
Re-grading, appeals, and follow-ups often extend the process. A student may challenge a grade or ask for clarification, requiring further time.
Designing quality assignments itself is labor. Professors need to anticipate student misconceptions, craft clear rubrics, balance fairness and challenge, and sometimes adapt mid-semester based on how students perform.
Students’ Load vs. Professors’ Load: A Rough Comparison
The old comparison of effort no longer holds. Today:
- Students: With AI tools, many assignments that once took 5–10 hours can be produced in 30–60 minutes (sometimes even less). The drafting, editing, and even research can be heavily outsourced to generative models.
- Professors: Grading remains largely manual. Reading, cross-checking for originality, providing feedback, and handling appeals still takes 20–60 minutes per essay.
Why This Discrepancy Matters
- Burnout risk is real. Professors are grading longer than students spend creating.
- Feedback quality can suffer. The sheer volume makes it harder to give personalized, formative comments.
- Unequal expectations. Students expect fast grading on work they may have produced quickly with AI, without recognizing the labor on the other side.
- Institutional pressure. Research, service, and teaching all compete for time, grading still eats up evenings and weekends.
A Way Forward: Automated Grading as a Partner
This doesn’t have to remain a zero-sum game. If students are using AI to speed up creation, then professors should use AI to speed up evaluation, without losing the formative or personalized touch.
- Automated baseline grading: Mechanical checks (grammar, citation formats, rubric adherence) can be done instantly.
- AI-assisted feedback: Systems can draft preliminary comments, highlight strengths/weaknesses, and free professors to refine and personalize.
- Time reallocation: Instead of drowning in repetitive evaluation, professors can reinvest time into deeper mentoring and coaching.
Safeguarding the Human Element
Automation isn’t about replacing professors’ voices. It’s about ensuring that when students do get human feedback, it’s thoughtful, individualized, and truly developmental. The professor’s energy should go into formative guidance, not mechanical scorekeeping.
In a world where students lean on AI to finish homework in minutes, it makes little sense for professors to keep grading as if nothing has changed. Togeder offers a the right mix of automation and human insight, to make grading can become more sustainable. Professors deserve to spend their time shaping thinkers, not just checking boxes.