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Kehinde Owolabi says he received a zero on an introductory Python assignment after a grader concluded that his work appeared to involve too much outside help. But his follow-up account changes an important detail: he says the instructor told him the grader—not the instructor—had flagged it, and that the instructor believed the code was his. The available account does not establish the final grade.
What was the Python assignment?
In a first-person post on DEV Community, Owolabi says he was 18, had been coding since 15, and was taking CSE 110 at BYU-Pathway. He describes the assignment as a word-guessing game with a secret word, hints, a guess counter, and validation of guess length. These details come from his account; the course record and assignment materials have not been independently verified. Owolabi’s original post
Why did the submission stand out?
Owolabi says he went beyond the stated game mechanics by adding a menu, random word selection, a help screen, sound effects with a fallback, loading animations, navigation commands, and emoji. He says the feedback on the initial grade was that the work appeared to have received too much outside help. Neither the post nor the reviewed follow-up establishes that an AI detector was used.
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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →He also pointed to rough edges he said were in his code: creating a word list by splitting a string on spaces, leaving the alphabet as a possible guess, using a bare except:, inconsistent singular and plural variable names, duplicate entries, and using Windows-only winsound. Those are his descriptions, not the result of an independent code review. More importantly, imperfections do not prove who wrote a program; they are details he offered as part of his explanation of how he worked.
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Who flagged it, and what happened afterward?
In a follow-up post, Owolabi says the instructor told him the instructor had not flagged the assignment; a grader had. He quotes the instructor as saying the code looked immediately like Owolabi’s work and that it should be graded normally. This is a reported private exchange, not an independently verified transcript. Owolabi’s follow-up
The quoted message also raises a practical compatibility issue: the instructor said winsound did not work in the instructor’s environment, so it was disabled to run the program without sound. The instructor reportedly said graders might dock points for that component and suggested resubmitting without it if necessary. The follow-up does not document the eventual grade, so it would be inaccurate to say the zero was overturned or that the work ultimately received a normal grade.
Does polished or feature-rich work prove AI use?
No. A submission that exceeds the expected scope may prompt a question about authorship or permitted help, but its polish alone cannot establish how it was produced. Human suspicion, detector output, evidence of a student’s process and understanding, and the course’s formal rules are separate things. The account does not establish that detector output played any role in Owolabi’s case.
A 2024 peer-reviewed study offers limited context, not a verdict on this Python assignment. University of Reading researchers Scarfe and colleagues tested GPT-4-generated answers in five undergraduate psychology modules. They reported that 94% of AI submissions went undetected under the study’s standard procedures, and that the exam and grading systems did not include an AI detector component. The authors also describe “too good to be true” as one possible suspicion cue among several. These results concern a particular university, subject, assessment format, and method; they do not measure the accuracy of detectors on Python code or establish what happened in Owolabi’s class. Scarfe et al., PLOS ONE (2024)
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What can a student do if their own work is questioned?
Owolabi’s proposed response is to stay calm, explain relevant prior experience, point to concrete decisions in the code, and offer to walk through or demonstrate the program. Those suggestions may help explain a particular submission, but they are not a guarantee of a favorable outcome. Check the course’s own rules on permitted tools and the formal process and deadline for challenging a grade; no current BYU-Pathway policy or appeal deadline is established by the accounts discussed here.
Quick Recap
- Gather process evidence: If you have drafts, version history, notes, or test cases showing how the program developed, organize them. Share only records you actually have.
- Explain specific choices: Be ready to describe how the game logic works, why you added optional features, and what limitations or bugs you already know about.
- Ask for a concrete review: You can ask which part of the submission raised concern and whether an oral walkthrough, live coding, or a version closer to the rubric would be considered under the course process.
- Separate authorship from compatibility: If a library or feature does not work in the grader’s environment, ask whether the assignment requires that dependency and whether a fallback or simpler version is acceptable.
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