AI Grading for Teachers: What the Research Says, the Risks for English Learners, and a Safe Workflow

Estimated reading time: 9 minutes

AI grading for teachers means using a generative AI tool to score student work or draft feedback against a rubric. It can save time on feedback, but research shows that AI scores on essays are much less consistent than scores from trained human raters, and that AI can reproduce score gaps between student groups already present in human grading. For English Learners, the main risk is confusing developing English with weak content knowledge. This guide summarizes the evidence, explains the risks, and offers a workflow that keeps the teacher in charge of every grade.

Executive Summary

Grading writing is one of the most time-consuming parts of teaching, so AI grading tools are attractive. Several now offer rubric scores and draft comments.

The evidence supports a narrower use. A 2024 study found that ChatGPT’s holistic scores agreed with expert raters far less reliably than two trained humans agreed with each other, even though average scores were similar, and a 2025 analysis of a large benchmark found that ChatGPT reproduced a score gap between student groups already present in the human scores and rarely gave very high or very low scores. AI is more useful for drafting feedback a teacher reviews than for assigning grades. For English Learners, any rubric that blends language accuracy with content understanding needs extra care, whoever is grading.

Key Takeaways

• AI grading tools estimate rubric scores; they do not understand student intent the way a teacher does.
• In a 2024 study of essays by students in grades 6 to 12, two trained human scorers reached a weighted kappa of .79, against .23 to .52 between ChatGPT and human scores.
• The same study found no overall score penalty for English Learners, but ChatGPT agreed less with human scorers on their essays (.40 and .43, against .51 and .52 for other students), and the authors judged AI not consistent enough for higher-stakes scoring, especially when English Learners are included.
• A 2025 analysis of the ASAP 2.0 benchmark found that ChatGPT reproduced a score gap between student groups already present in human scores and gave no essay the top score.
• Use AI to draft feedback, not to assign final grades.
• Student work and grades kept by the school can be education records under FERPA; use only district-approved tools.

What District Leaders Need to Know

• Set a clear rule. Teachers remain responsible for every grade; AI output is a draft.
• Approve tools for student data. Pasting student essays into unapproved chatbots raises FERPA concerns.
• Separate language from content. Rubrics for English Learners should distinguish what students know from how well they express it in English.
• Monitor equity. If AI tools are used, check whether score patterns differ by student group.
• Train before rolling out. Teachers need to know where AI grading fails before they rely on it.

Funding Options

See what Title II funds can be used for.

District Benchmark

A high school English teacher with 150 students who assigns one essay a month and spends 10 minutes on each spends 25 hours a month grading. If AI-drafted feedback saves three minutes per essay after the teacher’s review, that is about 7.5 hours a month returned to planning or conferences. The time saved is real, but only if the teacher still reads every essay and owns every grade.

How AI Grading for Teachers Works

Definition. AI grading is the use of a language model to score or comment on student work, usually by giving it a rubric, the assignment and the student’s response.

The model predicts what a scorer would write, based on patterns in its training data and the rubric it receives. It does not know the student, the instruction that preceded the task, or the accommodations the student is entitled to. Its output can vary from one run to the next.

What the Research Says About AI Grading

Results vary by model version, prompt and task, and newer models may perform differently. The consistent lesson is that AI scores need human review.

Grading English Learners’ Work Fairly

A student at an early level of English proficiency may understand a concept well and still write about it in short, simple sentences with errors. A rubric that rewards vocabulary and grammar in every row will score that student low on content too, whether a human or an AI applies it.

1. Separate the rows. Score content understanding and language use separately.
2. Use the student’s proficiency level to set expectations for language, as described in your state’s English language development standards.
3. Allow multiple ways to show learning, such as diagrams, oral explanations or home-language notes.
4. Review AI feedback for tone and accuracy before it reaches the student.

For more on proficiency levels, see WIDA levels explained.

A Safe AI Grading Workflow

1. Use an approved tool under your district’s AI policy.
2. Remove identifying information unless the tool is approved for student data.
3. Give the rubric and exemplars, with separate rows for content and language.
4. Ask for feedback, not a grade: one strength, one priority, one next step.
5. Read the student’s work yourself and decide the grade.
6. Edit the feedback and remove anything inaccurate or generic.
7. Spot-check patterns across student groups each grading period.

What This Looks Like in Practice

Consider a ninth-grade team that agrees AI can draft comments on argument essays but never assign scores. Teachers paste anonymized essays into the district-approved tool with a two-part rubric, read each essay, set the score and edit the comment. English Learners would receive feedback that names one content strength and one language goal matched to their level. The team would save time on comments and keep every grading decision.

Common Mistakes

1. Letting AI assign final grades without reading the work.
2. Pasting identifiable student work into unapproved tools.
3. Using rubrics that mix language accuracy with content understanding.
4. Assuming AI scores are objective because they come from software.
5. Sending AI feedback to students without editing it.

Recommended Actions

Immediate (this month)

• State that teachers own every grade and AI output is a draft.
• List the AI tools approved for student work.

Medium-Term (this year)

• Revise common rubrics to separate content and language.
• Train teachers on the safe workflow and on AI’s known limits.

Long-Term (strategy)

• Write AI grading rules into the district AI policy.
• Monitor score patterns by student group where AI is used.

Questions District Leaders Should Ask

• Which AI grading tools are teachers already using, and with what data?
• Do our rubrics separate content from language for English Learners?
• Who reviews AI feedback before students see it?
• Would we notice if AI-assisted grades differed by student group?

FAQ

Can teachers use AI to grade essays?

Teachers can use AI to draft feedback within district policy, but research shows AI scores are less consistent than trained human scores, so the teacher should decide the grade.

What are the best AI grading tools for teachers?

The best tool is one your district has approved for student data and that lets you supply your own rubric. No tool removes the need for teacher review.

Is AI grading biased?

It can be. A 2025 analysis of the ASAP 2.0 benchmark found that ChatGPT reproduced a score gap between student groups that also appeared in human scores, and it rarely gave very high or very low scores. Rubric design and teacher review reduce the risk.

Is AI grading fair to English Learners?

One 2024 study found no overall score penalty for English Learners, but ChatGPT’s scores agreed less with human scorers on their essays, and any rubric that blends language and content can underrate English Learners. Separate the two and review every score.

Is it legal to put student work into AI tools?

Student work and grades that are directly related to a student and kept by the school are education records under FERPA. Use only tools your district has approved for student data, or remove identifying information.

Related Resources

• AI for Teachers
• AI Detectors for Teachers
• Report Card Comments
• AI Literacy Frameworks
• WIDA Levels Explained

Conclusion

AI can lighten the load of feedback, but it cannot carry the responsibility of a grade. Teachers who use it to draft comments, with rubrics that separate language from content and a review of every result, get the time savings without passing judgment to a tool that does not know their students.

Sources: Can AI Provide Useful Holistic Essay Scoring?, Computers and Education: Artificial Intelligence, 2024, NSF Public Access Repository; The Learning Agency, Identifying Limitations and Bias in ChatGPT Essay Scores, March 2025; The 74, AI Shows Racial Bias When Grading Essays, May 2025; Liang et al., Patterns, 2023; U.S. Department of Education, FERPA.

The Grade Only a Teacher Can Give

An English Learner’s essay may hold a sharp idea inside short sentences, and a tool scanning for polish will see only the sentences. We ask teachers to give fast, fair feedback to well over a hundred students, many at different levels of English, and the stack of essays never gets shorter.

Some districts are training teachers to let AI take the drafting while they keep the judgment. Telo AI’s 15-hour course for whole school staffs, AI for Every Teacher, is one example. Over eight weeks, four core modules, three live sessions and three classroom cycles build a weekly feedback routine, drafted against the teacher’s own criteria, in which the teacher makes every call. Each teacher then takes a two-module track for their grade band, English Learners or school leadership.

A fair grade starts with a teacher who can see the idea inside the sentence.