How Wayground's AI Extension Flags AI-Written Student Work While You Grade

Thirty submissions. You're halfway through grading and three of them look off. The writing is cleaner than usual. The structure is a little too tidy. The argument doesn't sound like this student. You could stop, open a separate AI detection tool, paste the text, wait for a result, come back to your grading, and repeat that for every submission you're not sure about. Or you could keep grading, knowing that Wayground is already flagging what needs your attention in the same sidebar you're working in.

That's the distinction that matters for teachers who use Google Classroom daily. Detection doesn't have to be a separate step. It can happen while the review is already happening.

Why Google Classroom doesn't detect AI (and what that means for teachers)

Google Classroom does not have a built-in AI detector. As of 2026, Originality Reports in Google Classroom check student work against web sources for plagiarism, meaning copied or unoriginal text. They do not run an AI classification on the writing itself. Google has not publicly committed to adding classifier-based AI detection, and their own researchers have noted caution about detector accuracy.

This leaves a real gap for teachers. According to a 2026 study from the Higher Education Policy Institute, 94% of students are using generative AI on assessed work. Turnitin's own submission data shows that between October 2025 and February 2026, approximately 15% of English-language essay submissions contained more than 80% AI-generated writing, up from 3% in 2023.

The number of submissions that need a second look is growing. The workflow most tools propose for catching them: add a detection step before you grade, or after you grade, or run a separate platform for every assignment. Each of those options adds time to a process that's already measured in hours.

The more useful question isn't which detector is most accurate. It's where the detection fits in the work you're already doing.

What Wayground's extension shows when it flags AI-written content

When you're reviewing a student's submission in Google Classroom, Wayground's Chrome extension is active in the browser sidebar. As you grade, the extension surfaces flagged passages in the same view, without you opening anything extra or switching tabs.

When a passage is flagged, the sidebar shows which sentences or paragraphs triggered the flag and the source it matched, displayed side-by-side with the student's text. For AI-generated content, the flag identifies the passage and indicates the match. For copy-pasted content, it shows the original source. These are two different problems, and Wayground distinguishes between them, but they appear in the same place.

The flag is not a verdict. It is a signal that something in this submission warrants closer attention. The teacher is the one who decides what to do with that signal, with the context that only a teacher has: this student's writing history, their multilingual learner status, whether the flagged sentence is from a source they properly cited, whether something in the student's circumstances explains the pattern.

A standalone AI detector gives you a score and a percentage. It doesn't know who the student is. It doesn't know the assignment context. It doesn't know that the teacher is three seconds away from the grading rubric and the student's prior submissions. Wayground's flag arrives in that context, not outside of it.

The grading and detection workflow inside Google Classroom

The workflow is the same one teachers already use for essay grading with Wayground. Detection is not an addition to that workflow. It surfaces within it.

Step 1: Open the assignment in Google Classroom

Submissions appear in your Classroom tab as usual. The Wayground extension is active in the sidebar.

Step 2: Select your rubric and begin grading

From the sidebar, choose the rubric for this assignment. Wayground reads each submission and generates suggested scores for each criterion alongside inline feedback. You're reviewing the submission and seeing scores at the same time.

Step 3: Flagged passages appear as you grade

If Wayground identifies AI-generated writing or copy-pasted content in the submission you're currently reviewing, the flag appears in the sidebar alongside your rubric scores. You see the flagged passage, the source it matched, and the context, all while you're still looking at the same submission.

Step 4: Decide before you post

You review the flag in the same way you'd review a low score on a criterion: with judgment. Is the flagged sentence a properly cited passage from the student's source list? Is this a multilingual learner whose formal written English consistently scores higher than their spoken level? Does the flagged paragraph explain a concept that this student has demonstrated understanding of in class discussions?

If something requires follow-up, you note it before posting scores. If it doesn't warrant action, you post. Either way, you haven't opened a separate window or broken the review you were already running.

Step 5: Post to the gradebook

Scores and feedback post directly to your Google Classroom gradebook from the sidebar. No export, no re-upload, no manual entry.

When a flag appears: how to respond

A flag from Wayground, like any flag from any detection tool, should open a conversation, not a disciplinary case.

The most reliable next step is to ask the student to walk through their work. This isn't an interrogation. It's a standard learning conversation that works whether or not AI was involved.

• ›"Walk me through what you were arguing in this paragraph."
• ›"What was the hardest part of this to figure out?"
• ›"If you were going to revise this section, where would you start?"

A student who wrote their own work can engage with these questions, even imperfectly. They'll remember what they were trying to say. They'll have an opinion about the feedback. A student who outsourced the writing to AI will typically struggle to explain specific claims or describe their process in any concrete way.

This conversation also opens outcomes that a detection flag alone never does. Many students who use AI didn't fully understand that it constituted a violation, or made a bad decision under pressure. A conversation surfaces that context. A flag routed directly to academic misconduct paperwork doesn't.

If you do decide to escalate: document the flag, save the original submission, and follow your district's academic integrity protocol. Don't notify a student or family based on a flag alone. Give the student the opportunity to explain their work in person first.

One more thing worth noting: AI detectors, including the one Wayground uses, have higher false positive rates for students whose written English is more formal or structured than their speaking level. Research has found false positive rates as high as 61% for non-native English speakers in some studies. Multilingual learners, students with strong formal writing skills, and students who write in a precise academic style are flagged more often. Every flag needs teacher context to interpret correctly.

How Wayground's approach compares to running a separate detection tool

The practical difference is workflow structure.

With a standalone AI detector, the process looks like this: grade submission, then open detection tool, paste text, interpret score, return to grading, decide whether score changes anything, move to the next submission. For a class of 30, that's 30 additional detection cycles on top of 30 grading cycles.

Wayground in your Google Classroom grading workflow

Wayground's extension handles the grading and the flagging in the same session because they were already in the same session. A teacher who uses Wayground to grade is already getting detection. A teacher who uses a standalone detector is already doing everything Wayground does, plus one more step every time.

Turnitin's Google Classroom integration (launched May 2026) is meaningful for schools that already have an institutional licence. For individual K-12 teachers without institution-wide procurement, Wayground offers the same grading-plus-detection workflow without the licence barrier.

What the extension doesn't replace

The flag surfaces what the AI can see. It doesn't provide what only a teacher can.

It doesn't know that a particular student spent three study halls on this essay and came to office hours twice. It doesn't know that another student's formal writing style is a product of years of academic English instruction outside of class, not AI assistance. It doesn't know that this is the first assignment in four months where a struggling student produced writing at this level, and that the improvement might be real.

AI detection tools are one part of how teachers approach academic integrity, not the whole framework. Assignment design that makes wholesale AI use harder to sustain, explicit classroom conversations about how AI can and can't be used, a writing baseline established early in the year, these things work in combination with detection, not instead of it.

Wayground flags what the tool can identify. The teacher decides what the flag means for this student, in this class, at this point in the year.

Detection that fits the work you're already doing

Adding a separate AI detection step to a grading process that already takes hours is a reasonable thing to resist. The question worth asking isn't "how do I add detection?" but "where does detection fit without adding to the queue?"

Wayground's answer is the same sidebar where the rubric scores are, the same session where the submission is being reviewed, the same tab where the gradebook post happens. The flag arrives while the context for interpreting it is already open.

Grading 30 essays is the work. Detection that happens inside that work, rather than beside it, is the difference.