Why we still can't stop plagiarism in undergraduate computer science (2018)

Original Article ↗ Hacker News Discussion ↗

Project‑based and Exam‑heavy Approaches

  • Several comments endorse ungraded or low‑weight homework plus:
    • A substantial project built over the term.
    • A timed, in‑person practical where each student must modify their own project; tasks are chosen to both prove authorship and stress-test design/complexity.
  • Variants: oral/whiteboard exams, viva voce defenses of projects, pen‑and‑paper finals, and “no take‑home” weekly in‑class assignments.
  • Benefits: plagiarism becomes pointless, understanding and architecture are directly tested.
  • Costs: extremely time‑ and staff‑intensive, hard to scale, often “brutal” with lower pass rates; fairness and accessibility issues (e.g., large cohorts, weaker language skills).

Role and Weight of Homework

  • One camp: homework should be primarily for practice; grades should come mostly or entirely from proctored exams.
    • Optional or low‑weight homework often leads to more exam failures, but that’s seen by some as the student’s responsibility.
  • Another camp: the deepest learning and “real‑world” skills come from large, graded projects and sustained homework; exams can’t fully measure that.
  • Suggested compromises: homework to qualify for the exam (or provide bonus points), or multi‑part assignments where suspected plagiarists get extra work.

AI/LLMs and Changing Cheating Patterns

  • Many note that traditional plagiarism signals (identical code, whitespace quirks) are largely obsolete; LLMs can generate and “rewrite” solutions.
  • Instructors report:
    • More students getting perfect homework scores and then failing exams.
    • Students turning in AI‑generated work they cannot explain in oral exams.
  • Proposed responses: heavily exam‑weighted grading, in‑lab coding with logging/keystroke replay, and using LLMs to generate many variant problems.

Incentives, Institutions, and Culture

  • Strong view that degree value as a hiring filter drives cheating: when the diploma matters more than the learning, cheating is rational.
  • Some argue universities, especially revenue‑driven ones with many international students, have weak incentives to crack down hard; enforcement and sanctions are often mild.
  • Others insist institutions must protect their signal: unchecked cheating will erode program reputation and harm honest students.

Honor Codes, Ethics, and Empathy

  • Honor codes are seen as:
    • Weak direct deterrents but useful as legal/administrative evidence that students knew the rules.
    • Culturally dependent; cheating remains common in many “honor code” environments.
  • Debate over how much to factor desperation, mental health, and unequal preparation into responses to cheating:
    • One side emphasizes strict, consistent consequences to protect trust.
    • The other stresses understanding underlying causes and avoiding life‑ruining penalties for a single bad decision.