Key points
- The student reports that the volume of coursework has tripled due to poorly designed AI-generated assignment briefs.
- University policy on artificial intelligence use flips between mandatory adoption and strict prohibition across different modules.
- Administrative reliance on large language models for marking and content creation has introduced errors and delayed corrections.
A post published on the BearBlog platform and subsequently discussed on Hacker News details how artificial intelligence integration is disrupting computer science education. The author, a scholarship recipient studying computer science and artificial intelligence, argues that institutional uncertainty is degrading the learning experience.A student says their university's confused rules about using AI have made their studies much harder and less enjoyable.A CS scholar argues that inconsistent institutional AI mandates and automated assessment generation are exacerbating existing pedagogical challenges and increasing student workload. The post received 62 points and 23 comments on Hacker News, indicating significant community interest in the structural challenges of academic adaptation.reported
The figures
The author states that the amount of work involved in their studies has tripled. They reference a specific assignment requiring 3,000 words but containing 15 distinct deliverables. The student notes they achieved a grade of B in mathematics at the GCSE level, which is the examination taken at age 16 in the United Kingdom. The Hacker News discussion thread associated with the post accumulated 62 points and generated 23 comments.reported
Behind the figures
The tripling of workload is attributed to the use of large language models for creating assessment briefs. The author argues that these models fail to account for the effort required for students to learn new material and complete technical tasks. Professors, described as being far along in their careers, reportedly skim-read these AI-generated documents, missing the inflated scope. This disconnect leads to assignments that are overly complex and poorly structured, forcing students to rush through content rather than engage deeply with the material.
What changes, what does not
University policy has become inconsistent, oscillating between mandates to use artificial intelligence and strict prohibitions against it. The author describes a scenario where students are required to use AI in one module only to lose marks for using large language models in the next. Administrative functions such as marking, feedback, course content creation and student engagement emails have shifted towards automated systems. These changes have reportedly led to a rollback of decisions within three months, creating confusion and instability for the student body.
What builders can do with it
Developers building educational technology or assessment tools should note the limitations of current large language models in understanding pedagogical effort. The material suggests that automated brief generation can produce bloated and error-prone assignments that require significant human correction. Builders must consider how their tools might interact with inconsistent institutional policies, as users may face conflicting requirements regarding AI usage. The evidence indicates that without careful human oversight, automated content creation can increase rather than decrease the workload for learners.
Why it matters
- Educational institutions adopting AI for administrative tasks risk introducing errors and inconsistencies that degrade the quality of assessment and feedback.
- The lack of clear, consistent policy on AI use creates confusion for students and may lead to penalisation for actions previously encouraged by the institution.
- Automated generation of complex assignments can result in unrealistic workloads if the system fails to account for the time required for skill acquisition.
- The rapid adoption and subsequent rollback of AI tools suggests that institutions are still struggling to find effective use cases for the technology.
Topics: education, artificial intelligence, large language models, student experience, university policy
Updated
Then / now / next
Assignments were designed by people who thought through the requirements and received approval from department members.
AI-generated briefs are used, leading to errors, late corrections and a tripling of the workload for students.
Students must navigate inconsistent policies and potentially flawed assessments while trying to complete their degrees.
Story timeline
- Then Assignments were designed by people who thought through the requirements and received approval from department members.
- 03 Nov 2026 AI is destroying my CS degree
- Now AI-generated briefs are used, leading to errors, late corrections and a tripling of the workload for students.
- Next Students must navigate inconsistent policies and potentially flawed assessments while trying to complete their degrees.
The strongest doubt
Counterpoint from the sources
The student acknowledges that assessing skill in computer science is inherently difficult and that the system was never perfect before the introduction of AI.
For readers
Policy
- Institutions must develop consistent and clear guidelines for AI use to avoid confusing students and staff.
- Automated assessment tools require rigorous human oversight to prevent errors and ensure fairness.
Researchers
- The impact of AI on student workload and learning outcomes needs further empirical study.
- The effectiveness of AI in administrative tasks like marking and feedback is questioned by students.
Consumers
- Students should be aware of the potential for inconsistent AI policies in their educational institutions.
- Learners may need to spend more time deciphering flawed AI-generated assignment briefs.
Ask the article
Local keyword search of this article; no generated answers.Did this article give you the evidence you needed?
Your choice stays on this device. No public tally.Questions readers ask
How has the workload changed for the student?
The student reports that the amount of work has tripled due to poorly designed AI-generated assignment briefs that do not account for learning time.
What is the university's current policy on AI?
The policy is inconsistent, flipping between mandatory use and strict prohibition, with students facing penalties for using AI in some modules after being required to use it in others.
What administrative tasks are being automated?
The university is using AI for marking, feedback, course content creation and student engagement emails, though these decisions have been rolled back multiple times.
Connected stories
Reading receipt
- The student reports that the volume of coursework has tripled due to poorly designed AI-generated assignment briefs.
- University policy on artificial intelligence use flips between mandatory adoption and strict prohibition across different modules.
- Administrative reliance on large language models for marking and content creation has introduced errors and delayed corrections.
Still open: Will universities eventually settle on a consistent policy for AI use in coursework?
Still open: How will the quality of computer science education be affected by the continued use of AI for administrative tasks?