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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →No: the available official guidance does not show that Singapore has declared essays obsolete or that universities are replacing them nationwide. It shows a more targeted shift: assessment formats and AI rules should fit the learning goal, and the rules can differ by assignment.
What the “essays are dead” claim gets wrong
The claim that Singapore is making a radical national move away from essays is not established by the official sources available here. A matching-title article published August 30, 2026, describes a broad change in higher education, including presentations, oral defenses, in-class writing and staged submissions. Those examples are that article’s account, not evidence of a national policy or proof that universities are abandoning essays.
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What is documented is a case for choosing assessments deliberately. A NUS-hosted contribution to the Higher Education Conference in Singapore on December 3, 2024, proposes matching format to objective: a supervised in-class test may suit retention, while take-home work may suit goals involving information search and organization. That approach can change how an essay is assigned or evaluated without making essays obsolete.
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The evidence here does not establish how widely essays are used across Singaporean universities, or whether their use is increasing or declining. It does establish that assessment format is a design choice rather than a single national prescription. Essays can still be suitable when the learning goal is to develop and communicate an argument, synthesize material, or demonstrate another skill the assignment is designed to assess.
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The practical question is less “essay or no essay?” than “what does this task need to show, and under what conditions can a student show it?” An instructor might choose supervised work when the goal is to assess unaided performance, or take-home work when research and organization are part of the goal. These are examples of matching method to objective, not a report that every institution uses those formats.
Can a professor ban AI for a take-home assignment?
NUS’s Policy for Use of AI in Teaching and Learning says instructors should decide whether AI is allowed based on whether using it defeats or advances the assessment’s learning goal. For unsupervised assessment, the policy permits AI use by default when it is acknowledged. That is NUS guidance; it should not be assumed to be the rule at every Singapore institution or in every course.
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The same policy recognizes that an instructor may forbid AI for pedagogical reasons. In that case, it says crucial parts of the assessment should take place in person under the instructor’s supervision. For unsupervised work, it recommends tasks that require higher-order skills beyond simple prompting. The distinction matters: a no-AI rule for take-home work is difficult to verify through the final document alone, whereas supervised components can make the conditions of the task clearer.
What should students check before using AI?
Read the rules for the specific course and assignment rather than inferring permission from a university-wide headline or a different class. Check the syllabus, assignment brief and instructor’s current directions for what tools are allowed and whether use must be disclosed.
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- Identify whether the assignment permits, limits or prohibits AI assistance.
- Check whether the instructor requires an acknowledgement or disclosure, and what it should cover.
- Follow any stated conditions about how the work is completed, including supervision or process documentation.
- Ask the instructor if the rules are unclear before submitting work.
A course document for NTU’s “HL 2024 Approaches to Literature” illustrates why the assignment-level check matters: it specifies disclosure when AI use is permitted and Google Docs version-history conditions for an assignment that excludes generative AI. This is a course-specific document tied to an academic year, not evidence of a current university-wide NTU rule. See the course document for its stated conditions.
Can an AI detector prove that a student cheated?
NUS guidance says no: detector outputs are not conclusive evidence in disciplinary proceedings and are not, by themselves, justification to penalize a student’s work. The policy’s wording is explicit: “The verdicts of current AI tools purported to determine whether an analyzed input has been generated by AI are not admissible as conclusive evidence in a disciplinary process to charge a student with academic dishonesty or as justification to penalize student work.” This is NUS policy guidance, not a statement of every institution’s procedures.
That position does not mean that academic-integrity rules do not apply. It means an automated detector verdict alone should not be treated as proof. Students should follow the assignment’s AI rules and retain any process evidence specifically requested by their instructor.
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AI tools can generate essay-like text, but whether using them is permitted depends on the assignment’s rules and purpose. Under NUS guidance, acknowledged AI use is permitted by default in unsupervised assessment, while instructors may set different rules when the learning goal calls for them. A polished result does not by itself show that the student has met the intended learning objective; the task may require the student to research, reason, synthesize or demonstrate understanding in ways that go beyond prompting.
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