Can Students Cheat Their Way to a Biology Degree? Vulnerability of Biology Course Grades to Academic Dishonesty in the Era of Generative AI

Synthesis: Chan et al. (2026) report a case study of one biology department in the 2025–2026 academic year examining how vulnerable course grades are to academic dishonesty in the era of Generative AI. Analyzing syllabi from all core required biology courses, they found instructors perceived only in-person proctored exams as minimally vulnerable; all other graded categories were at least somewhat vulnerable, with outside-of-class assignments seen as highly vulnerable. On average, about a third of a student's grade was highly vulnerable and 80% was at least somewhat vulnerable to academic dishonesty. The study highlights how current grading may be undermining the validity of course grades as measures of student learning.

The Vulnerability of Modern Grading

A course grade is typically understood as a measure of student success that communicates achievement to employers and graduate programs. Thirty years ago, most undergraduate biology courses administered a few high-stakes, in-person proctored exams on which a grade depended — making cheating difficult and risky. The convergence of widespread Generative AI adoption and the shift toward coursework completed outside a physical classroom has introduced new challenges that potentially threaten the integrity of a college biology degree.

What the Case Study Found

The researchers analyzed the syllabi from all offerings of core required biology courses in a term to determine the percentage of graded coursework vulnerable to academic dishonesty, based on instructors' perceptions within that department.

1. Only in-person proctored exams were seen as minimally vulnerable. All other graded categories were perceived as at least somewhat vulnerable to academic dishonesty.
2. Outside-of-class assignments were perceived as highly vulnerable. Take-home work — the category most exposed to generative AI — was seen as the least protected.
3. About a third of a student's grade was highly vulnerable, and roughly 80% was at least somewhat vulnerable, on average, in core required biology courses.

The findings suggest that current grading in biology courses may be substantially exposed to AI-mediated academic dishonesty, prompting instructors to rethink how they grade in order to protect the validity of course grades as measures of student learning.

Implications

The case study frames the integrity problem as partly a design problem: grading architectures that rely heavily on unsupervised, take-home coursework are structurally vulnerable in the generative AI era. Responses may include rebalancing toward proctored or in-class assessment, authentic assessment designs that are harder to outsource, and clearer norms around AI use. The work connects to broader debates about how Assessment must change to preserve meaning and validity when AI can produce fluent work on demand.

Connected Concepts

• Academic Integrity
• Generative AI
• Biology Education
• Assessment
• Assessment Validity
• Higher Ed
• Authentic Assessment
• AI Education

Connected Articles

• Kirsanov Beyond Detection AI Online Assessments 2026 — Beyond Detection: How Students Use—and Hide—AI
• Lopez Lopez Academic Integrity AI Study Practices 2026 — Academic Integrity in the Age of AI
• Beyond Detection Authentic Assessment AI 2025 — Beyond Detection: Redesigning Authentic Assessment
• Kofinas Generative AI Authentic Assessment Integrity 2025 — The Impact of Generative AI on Academic Integrity of Authentic Assessments
• Coauthorship Integrity Reconceptualising Assessment Validity For The Age Of Gene — Coauthorship Integrity

Citation

Chan, B. G., Anderson, E. P., Lu, S., Abdellatif, N., Cooper, K. M., & Brownell, S. E. (2026). Can Students Cheat Their Way to a Biology Degree? Vulnerability of Biology Course Grades to Academic Dishonesty in the Era of Generative AI. EdArXiv preprint.