eduKate Singapore

VIEW THIS AS

Auto mode follows the Route Engine until you choose a viewpoint.

YOU ARE HERE

ROUTE CHECK

CONNECTED TO

WHAT NEXT

Use the canonical route for this room, or HELP if you are unsure.

Next useful routeCanonical hubHELP

PG1, PG2 and PG3 AI for Studying vs AI-Written Homework | 2027 SEC Authentic Work, Feedback and Coursework

—

by

eduKate Asia
Student using an iPad while listening to study instructions.

Can students in PG1, PG2 or PG3 use artificial intelligence to study for the 2027 SEC without compromising their own homework and assessed coursework? The important distinction is between authorised learning support and work that falsely represents someone else’s or an AI system’s output as the student’s own. Schools and SEAB set subject-specific assessment conditions; a tool’s ability to generate an answer is not permission to submit it.

Singapore MOE’s AI-in-Education Framework uses Agency, Inclusivity, Fairness and Safety as its central principles. The Singapore Student Learning Space includes AI-enabled features designed and reviewed for educational purposes, while external tools require their own attention to suitability and privacy. Students should understand the task, verify the information and remain responsible for their decisions.

This guide offers clear parent examples in English, Mathematics, Science, History, Computing, Art, D&T and Nutrition and Food Science. It discusses why AI can invent sources, produce incorrect calculations or misrepresent a coursework process, and how students can use appropriate feedback to strengthen independent learning without anxiety or moralising.

Independent eduKateSG guide, 17 October 2026. Official MOE AI-in-Education and Student Learning Space guidance and SEAB’s 2027 SEC subject catalogues reviewed. Always follow the actual school task, age-appropriate service conditions and the candidate’s current syllabus, particularly for coursework authenticity and exams.

Quick answer: five responsible AI checks

  • Allowed? Confirm whether the exact school activity permits the intended assistance.
  • Owned? Can the learner independently explain and reproduce their work?
  • Verified? Have sources, calculations and examples been checked?
  • Private? Is the tool approved for any data being entered?
  • Attributed? Have any required references or disclosures been included?
  • Not a ranking: PG1/PG2/PG3 are school entry groups, not technology entitlements.

Choose the AI and academic-integrity question

1. Start with the difference between learning and submitting

An AI tool can help a learner ask a question or obtain a suggested explanation, but formally assessed work must follow the school’s authenticity and permitted-assistance conditions. A convincing generated response is not automatically the student’s own demonstrated learning.

Illustration: A student asks an AI tutor to explain algebra, then tries a fresh equation independently. Another copies an AI solution verbatim into an assessed assignment.

Useful next action: Encourage the first kind of use where school rules permit it and check the conditions before using AI in any submission.

Important boundary: The distinction is the student’s actual understanding, work and authorised assistance—not whether the text sounds polished.

2. PG1, PG2 and PG3 do not determine AI permissions

Posting Groups indicate Secondary 1 entry arrangements. G1, G2 and G3 are levels of individual subjects. Rules about device use, homework, coursework and electronic examinations come from the relevant school or examination authority.

Illustration: A PG2 learner is allowed to use a digital quiz for revision but not an external text generator for an assessed report.

Useful next action: Read the instructions for the actual assignment instead of inferring permissions from the student’s Posting Group.

Important boundary: No academic level creates a general right to use a prohibited device or tool during an examination.

3. The MOE AI in Education Framework has four principles

MOE’s AI-in-Education Framework emphasises Agency, Inclusivity, Fairness and Safety in teaching and learning. These are helpful lenses for choosing a tool and understanding the role of student judgement.

Illustration: A tool creates quick homework answers but does not help the child explain a single step.

Useful next action: Ask whether the system develops independent agency, provides equitable access, treats people fairly and protects safety.

Important boundary: These principles are guidance, not permission to submit AI-generated assessed work.

4. Agency means the learner remains in charge

Student agency includes choosing goals, checking evidence, explaining decisions and deciding when a suggestion is wrong. AI should support rather than displace these acts.

Illustration: A child receives a generated paragraph and revises its structure after independently checking the source.

Useful next action: Ask the student why each final sentence belongs in the response.

Important boundary: Accepting every automated suggestion is not the same as exercising independent judgement.

5. Inclusivity requires accessible learning

A helpful education tool can offer different explanations or formats so that more learners can engage with a concept, while maintaining appropriate curriculum standards and safeguards.

Illustration: A learner benefits from a clear stepwise verbal explanation of a graph after a dense written description was confusing.

Useful next action: Use alternative authorised explanations that preserve the underlying mathematical or scientific meaning.

Important boundary: Making content accessible does not mean lowering expectations about evidence and accuracy.

6. Fairness matters when judging outputs

AI systems can reflect biases in training data or prompts. Learners should examine stereotypes, missing viewpoints and unsupported assumptions in generated examples.

Illustration: A career explanation assumes every student in one Posting Group should pursue the same occupation.

Useful next action: Challenge the assumption and look at actual interests and eligibility rather than generated stereotypes.

Important boundary: Technology should not convert school posting labels into social judgements.

7. Safety includes privacy and wellbeing

Tools may process student prompts, uploads or account information. Families should use approved systems and avoid exposing unnecessary personal details or private school materials.

Illustration: A learner pastes a classmate’s full name, student ID and confidential feedback into an unknown website.

Useful next action: Remove identifying information and follow school rules about which tools may be used.

Important boundary: Technical convenience is not permission to disclose another person’s private information.

8. SLS has purpose-designed AI features

The Singapore Student Learning Space provides AI-enabled features reviewed for appropriate educational, data-security and safety purposes. School access and permitted uses still depend on current arrangements.

Illustration: A learner has an approved SLS activity but wants to replace it with an unrelated public chatbot.

Useful next action: Use the teacher-assigned learning environment and ask about acceptable alternatives.

Important boundary: The existence of AI features inside SLS does not approve every third-party service.

9. Check the school instruction before opening a tool

Some assignments permit research, feedback or collaboration; others require unaided work. The same AI assistance may be appropriate during practice and prohibited during assessment.

Illustration: A teacher asks students to draft an original response without outside language generation.

Useful next action: Read the brief for permitted help and produce the work personally.

Important boundary: What is acceptable for a home revision exercise may not be acceptable for a supervised assessment.

10. What counts as authorised feedback?

Feedback can identify gaps or suggest areas for improvement without supplying the entire answer. The school sets any boundaries on what students may receive or use.

Illustration: A student asks for help identifying which sentence in a self-written paragraph lacks evidence.

Useful next action: Request targeted feedback and then write the correction independently where permitted.

Important boundary: A tool silently rewriting the full response can undermine the learner’s authorship.

11. A prompt should ask for understanding

Prompts that request explanation of a concept, a different example or a checking question can support independent learning. Prompts that merely demand the completed assignment often bypass the skill being assessed.

Illustration: Instead of ‘Write my History answer’, the learner asks ‘What makes a historical inference different from a fact?’

Useful next action: Practise answering a new teacher-approved problem after receiving the explanation.

Important boundary: An apparently sophisticated prompt can still be used inappropriately if it produces prohibited assessed content.

12. Ask an AI tutor to explain, not guarantee

A system can offer a possible explanation, but students should compare it with textbooks, teachers and known principles. Learning means checking whether the model fits the task.

Illustration: An AI gives a formula but the student notices it uses a wrong unit for acceleration.

Useful next action: Identify the conflicting detail and verify against the approved subject resource.

Important boundary: An automated answer’s confidence should not determine whether it is correct.

13. AI can invent citations

A generated essay may cite sources that do not exist or misrepresent a genuine publication. This is especially risky in History, Social Studies and coursework.

Illustration: A chatbot supplies a convincing-sounding report title about Singapore schools but no traceable document.

Useful next action: Search for the original source and confirm the quotation or statistic before using it.

Important boundary: A plausible reference format is not evidence of an authentic source.

14. AI can misread graphs

A language model may infer a trend without reading the axis, base or units accurately. Learners should return to the original data before accepting a summary.

Illustration: A generated answer says a chart increased by 20% when it rose from 20% to 30%.

Useful next action: Calculate the percentage-point difference and relative change correctly.

Important boundary: Fluent chart commentary cannot replace direct examination of the evidence.

15. AI can make algebra mistakes

Automated solutions may contain invalid simplifications, sign mistakes, domain omissions or arithmetic errors. A student who copies the result may learn the wrong rule.

Illustration: An output cancels a factor while ignoring values that made the original denominator zero.

Useful next action: Substitute a valid test value and compare the transformations.

Important boundary: A concise machine-generated solution is not proof of mathematical equivalence.

16. AI can choose the wrong Physics model

A generated explanation can apply a remembered formula to the wrong physical quantity. Students should identify the system, known values, units and conditions independently.

Illustration: An AI treats the height of a speed–time graph as acceleration.

Useful next action: Read the graph axes and identify the actual gradient or area relationship.

Important boundary: A correct equation used in the wrong situation still produces a wrong explanation.

17. AI can misrepresent Biology processes

Biological explanations involve material sources, energy, structures and mechanisms. A model may use familiar words yet describe a scientifically false process.

Illustration: An output says most plant biomass is created from minerals in soil while discussing photosynthesis.

Useful next action: Trace the correct material and energy inputs using the approved syllabus.

Important boundary: A compelling narrative is not a substitute for accurate biological relationships.

18. AI can confuse historical dates

History answers require chronology and contextual source reasoning. Generated text may reverse event order or attribute later knowledge to earlier witnesses.

Illustration: An AI says a law enacted later was the cause of an earlier event.

Useful next action: Construct a timeline and compare the claim with verified references.

Important boundary: A smooth paragraph may contain impossible historical causation.

19. AI can flatten different viewpoints

Social Studies and Literature may involve multiple perspectives. A generated answer can prematurely declare one view correct without considering the evidence or context.

Illustration: A policy summary calls every supporter selfish without examining the stated reasons and consequences.

Useful next action: Identify the affected groups and assess each claim fairly.

Important boundary: A system’s confident moral judgement does not replace careful source evaluation.

20. Generated vocabulary can sound unnatural

Language models can suggest impressive expressions that do not match a student’s intended meaning, language level or audience. Clarity is more valuable than unnecessary ornament.

Illustration: A learner replaces ‘helpful’ with an obscure word that makes a formal email confusing.

Useful next action: Read the sentence aloud and explain why the vocabulary fits this recipient.

Important boundary: Complexity is not an automatic measure of English proficiency.

21. AI translation requires language awareness

Automated translations may mishandle register, idioms or grammatical relationships, particularly in language-specific school contexts. Students need teacher-approved materials for formal assessed language tasks.

Illustration: A Chinese or Malay learner receives a translation that changes the tone of a polite request.

Useful next action: Compare with the actual textbook and ask a qualified teacher about unfamiliar forms.

Important boundary: A machine translation should not be represented as independent language production.

22. An AI-created study quiz can be useful

Where permitted, a generated practice quiz can help retrieval when questions and answers are checked for accuracy. The student still has to answer without seeing the key.

Illustration: A learner asks for five new fraction examples, verifies them and completes them independently.

Useful next action: Use a small, correctly checked set and review mistakes after attempting.

Important boundary: A quiz containing fabricated facts or off-syllabus content can create confusion.

23. Feedback needs a target

A vague request for improvement can produce a rewritten answer with little educational value. A precise request can reveal the weakest reasoning step.

Illustration: A child asks whether the evidence in paragraph two actually supports the claim rather than asking for a perfect essay.

Useful next action: Keep the original student draft visible and perform the actual revision independently.

Important boundary: A completely replaced answer may erase the evidence of what the child understands.

24. Teach-back checks whether learning happened

A student can explain a solution aloud or write it afresh without the AI response in view. This reveals whether assistance supported understanding or simply supplied output.

Illustration: A learner reviews an AI example of quadratic factorisation, closes it and explains another problem.

Useful next action: Use a fresh example or changed numbers to test transfer.

Important boundary: Being able to repeat the first solution while looking at it is not enough.

25. Use a four-step AI checking routine

A reliable practice routine is ask, verify, attempt independently and reflect. It treats the system as one resource rather than the owner of the task.

Illustration: A student requests a concept explanation, checks the school notes, solves a separate question and records the earlier mistake.

Useful next action: Build these steps into occasional permitted practice sessions.

Important boundary: A checklist helps only if the learner genuinely completes each step.

26. What the 2027 SEC actually certifies

The SEC records a student’s examination subjects and their G-levels. Formal assessment seeks evidence of the candidate’s own performance under the examination rules.

Illustration: A child uses AI to make a project look professional but cannot explain the steps supposedly performed.

Useful next action: Align preparation with the syllabus and the authorised conditions of each assessment.

Important boundary: A certificate cannot meaningfully reflect capability if submitted evidence falsely attributes the work.

27. ESS provides an explicit authenticity example

The 2027 G3 Exercise and Sports Science K354 syllabus warns that AI-produced content is not considered the candidate’s own work and that passing off such work may lead to disciplinary consequences.

Illustration: A candidate asks an AI tool to fabricate a personal training log with sessions never completed.

Useful next action: Write the development log from the actual permitted supervised activity and cite external sources as required.

Important boundary: This subject’s explicit rule does not mean families may invent equivalent wording for every other syllabus; check each subject’s rules.

28. Art portfolios must reflect the student

A formally assessed Art portfolio can include research and visual development, but authenticity matters. Generated imagery or alterations are subject to the school’s exact instructions about outside assistance and original work.

Illustration: A student asks a generator to create an apparently hand-drawn portfolio stage that never happened.

Useful next action: Confirm permitted media and document genuine independent exploration.

Important boundary: Fabricated process images cannot serve as truthful evidence of artistic development.

29. D&T projects need genuine design decisions

A design project assesses the learner’s understanding, decisions, prototypes and evaluation. Generating a completed report can hide the very skills the coursework is meant to observe.

Illustration: A student provides a brief to a chatbot and copies a full design rationale without having tested the product.

Useful next action: Use approved feedback to clarify the brief, then record actual design choices and tests.

Important boundary: The teacher-supervised task should not be manufactured externally on the candidate’s behalf.

30. NFS investigations need real observations

Nutrition and Food Science coursework may involve planning, cooking, testing and evaluation under school supervision. Inventing sensory results or photos is both educationally weak and misleading.

Illustration: A learner asks AI to produce convincing taste-test findings for a recipe they never prepared.

Useful next action: Record only the authorised observations and explain their limitations.

Important boundary: An automatically written report is not a substitute for a genuine practical investigation.

31. Biotechnology data must be authentic

Where a structured science project involves experimental results, the candidate should document actual measurements, approved procedures and the teacher’s supervision requirements.

Illustration: A model proposes perfectly smooth data after the laboratory experiment produced an outlier.

Useful next action: Discuss the genuine anomalous observation and what it suggests.

Important boundary: Replacing inconvenient scientific data with synthetic numbers is a form of misrepresentation.

32. Computing programs need independent testing

A student may use permitted learning support to understand an algorithm, but a formally assessed practical task follows its own software and assistance rules.

Illustration: A chatbot writes a program that appears to work for one input but fails on zero.

Useful next action: Trace the program and test ordinary and boundary inputs in the approved environment.

Important boundary: Code output copied without comprehension or permission does not establish the learner’s competency.

33. Spreadsheets can contain silent AI errors

Generated formulas may reference the wrong cells, mishandle rounding or ignore units. Students should check dependencies and sample calculations.

Illustration: A spreadsheet uses a relative reference where a fixed reference is required, changing totals when copied.

Useful next action: Hand-calculate a sample row and inspect the formula.

Important boundary: A neat report with incorrect formulas is still wrong.

34. Privacy begins before upload

Students should not upload private school files, classmates’ work or personal data to an unapproved system. Even a harmless-looking question may include identifying details.

Illustration: A learner shares the full list of classmates’ names and marks when asking for chart advice.

Useful next action: Use fictional or anonymised examples where permitted and choose school-approved tools.

Important boundary: An external AI system is not automatically authorised to receive protected school records.

35. Copyright matters with source material

Text, images, artworks and recordings can carry rights and attribution requirements. Students should use material according to school rules and the source’s permissions.

Illustration: A student feeds an entire paid workbook into a public service and redistributes the generated copy.

Useful next action: Use legitimately accessible material and cite sources appropriately.

Important boundary: A tool’s ability to process content is not proof that sharing or reproducing it is authorised.

36. The child should know who can see the work

Families benefit from understanding whether an AI service retains prompts, uses data for improvement or allows organisational oversight. The right settings and service depend on the school.

Illustration: A student believes a public chat is private and types personal medical details into it.

Useful next action: Review the service and school policies before using it for learning.

Important boundary: Do not assume all systems have identical storage or privacy practices.

37. Age and access rules still apply

External apps and services have their own eligibility and access requirements. A student should use age-appropriate, school-permitted educational tools.

Illustration: A younger learner is offered a commercial site that requires an account intended for adults.

Useful next action: Use an approved student environment and ask the school about alternatives.

Important boundary: Educational value does not override a platform’s access rules.

38. Parents can ask for a process explanation

A child who can explain how a draft changed, why a formula works or where a claim came from has more meaningful evidence of learning than a polished file alone.

Illustration: A student points to an edited paragraph and says which original reasoning gap was repaired.

Useful next action: Ask to see the before-and-after reasoning rather than the final format alone.

Important boundary: A perfect-looking submission may conceal dependence on outside help.

39. Teachers remain responsible for assessment conditions

Only schools and examining authorities can define permissible assistance for a particular school task or national examination. The parent guide can direct questions but not grant an exception.

Illustration: A child is unsure whether AI-generated brainstorming is allowed in a D&T portfolio.

Useful next action: Ask the subject teacher before using that help in assessed work.

Important boundary: A tutoring company’s statement is not an official examination instruction.

40. No universal ‘AI permitted’ label exists for SEC

A tool permitted for ordinary study may be prohibited during a timed examination or coursework, and different subjects may have different guidance.

Illustration: A student assumes that because SLS includes AI features, a personal AI app can be opened during an e-exam.

Useful next action: Read the specific candidate instruction and allowed software list.

Important boundary: The existence of technology in an exam centre is not permission to use arbitrary digital assistants.

41. Authenticity need not produce fear

The aim of assessment rules is to make work fair and meaningful. Students can seek help appropriately without treating every question or useful explanation as misconduct.

Illustration: A learner feels uncertain whether asking the teacher for a concept explanation is allowed.

Useful next action: Use the teacher’s published guidance and ask clarifying questions early.

Important boundary: Responsible support and unauthorised replacement of assessed work are different actions.

42. Distinguish editing feedback from ghostwriting

Feedback that identifies a confusing sentence can encourage the student to rewrite it. Ghostwriting produces content attributed to someone who did not create it.

Illustration: A tutor revises an entire History essay until none of the student’s original reasoning remains.

Useful next action: Focus on comments, questions and modelled techniques, then request a fresh student response.

Important boundary: A substantially rewritten final answer can misrepresent the student’s own ability.

43. Acknowledge sources transparently

Where assessment rules require source acknowledgement, students should record relevant source titles, dates and links. AI use should be disclosed or cited according to the exact school policy.

Illustration: A learner uses external information to explain a science phenomenon but provides no traceable reference.

Useful next action: Keep a modest source log and confirm the teacher’s required format.

Important boundary: A citation-looking sentence invented by AI is not valid acknowledgement.

44. A source log can be very simple

A concise record of what material helped, what claim was verified and where it came from supports honest research. It does not need to be a decorative document.

Illustration: A student notes the SEAB syllabus, a teacher handout and a public data source for an economics example.

Useful next action: Record the exact useful information and access details as the school directs.

Important boundary: A long bibliography with unrelated or unread sources is not a stronger investigation.

45. AI bias can affect career advice

Generated suggestions may reproduce assumptions about subject levels, industries or family background. Education choices deserve evidence from actual courses and the learner’s interests.

Illustration: An AI says every PG1 child should aim at a single post-secondary pathway.

Useful next action: Correct the premise and examine eligibility, strengths and choices individually.

Important boundary: A machine’s recommendation must not become a permanent label for a child.

46. Confidence is not truth

AI outputs are fluent because of language generation, not because every fact has been verified. Students need independent checking for current regulations and exam requirements.

Illustration: A generated answer invents a 2027 SEC examination date or says a subject is compulsory.

Useful next action: Check current official MOE, SEAB and school notices before making plans.

Important boundary: A confident answer with no authoritative source is not an examination rule.

47. A useful Mathematics AI session

A focused practice session can involve a student attempting a problem first, asking for a hint about the failed step, then retrying without the answer visible.

Illustration: A learner gets stuck expanding brackets and asks why the distributive rule applies.

Useful next action: Request a simpler demonstration and independently solve an analogous expression.

Important boundary: Starting with the full solution every time may reduce the student’s opportunity to think.

48. A useful Science AI session

A student can use authorised tools to explore conceptual distinctions, such as the difference between observation and inference, then test the explanation on teacher-provided data.

Illustration: A learner asks whether bubbles alone prove oxygen was produced during an experiment.

Useful next action: Identify what gas test and contextual evidence the course actually requires.

Important boundary: Never treat a generated experimental protocol as permission for unsafe home practice.

49. A useful English AI session

A child may ask for feedback on the logic of an original paragraph, then revise it personally. The precise goal matters more than stylistic polish.

Illustration: A student asks which sentence fails to explain why a quotation supports their point.

Useful next action: Use the response as a question to investigate and rewrite independently.

Important boundary: Submitting a fully generated composition is a different activity from learning to improve one.

50. A useful Humanities AI session

A student can use a tool to generate alternative questions about a historical source, while verifying all factual context before answering.

Illustration: A learner has a teacher-provided poster and asks for three questions about origin and purpose.

Useful next action: Answer the questions from the actual source and current syllabus.

Important boundary: Do not let generated historical context invent facts beyond the source.

51. A useful Computing AI session

Programming support can explain loops, variables or test cases, but the child should still understand and check code. School-approved tools and assessment rules remain binding.

Illustration: A student asks why a loop fails to terminate, then traces the changing variable.

Useful next action: Run a small permitted test and explain what changed.

Important boundary: A program that runs after an AI fix does not prove the student understands the logic.

52. Feedback should be followed by transfer

The best test of learning is whether the student can apply the correction to a fresh task without repeating the AI’s answer.

Illustration: A learner repairs one inference and then solves a different passage question independently.

Useful next action: Select a new problem that tests the same idea in changed context.

Important boundary: Repeating the identical example with the answer visible is not evidence of transfer.

53. An error log is more valuable than chat volume

Students can record the original misconception, corrected idea and one later independent example. This creates a focused revision plan.

Illustration: A student writes ‘Confused average speed with acceleration’ and links it to an accurate new question.

Useful next action: Keep the log short enough to revisit weekly.

Important boundary: Many chat messages do not automatically create durable knowledge.

54. Parents should support agency, not police every keystroke

A family can establish expectations about permitted use and independent work without turning learning into constant suspicion. The child should understand why the rules exist.

Illustration: A parent asks the student to explain what assistance they used on a homework task.

Useful next action: Keep a respectful conversation about process and what was learned.

Important boundary: Monitoring alone does not replace trust, clear instructions and educational feedback.

55. Use AI only when it solves a real learning need

Sometimes a textbook diagram, teacher explanation or ten minutes of independent practice is more effective than an AI conversation. Choosing not to use AI is also a thoughtful decision.

Illustration: A student understands a fraction question and could solve it faster on paper than prompting a chatbot.

Useful next action: Choose the simplest suitable tool for the actual problem.

Important boundary: AI use is not a measure of modernity or educational status.

56. Every learner deserves equitable options

Students have different access to devices and connectivity. Good educational practice should offer suitable alternatives and never make unauthorised paid software a hidden condition of success.

Illustration: A classmate cannot afford a commercial subscription that another student uses for revision.

Useful next action: Use accessible school-approved resources and teacher support.

Important boundary: Paying for more tools does not guarantee deeper understanding.

57. AI tools cannot confer subject-level eligibility

A student may become more confident through practice, but formal G-level changes and examination registration follow school and MOE rules. No app can make an administrative decision.

Illustration: A learner uses AI to study ahead and assumes that means an automatic move from G2 to G3.

Useful next action: Discuss readiness and official criteria with the school.

Important boundary: Personal progress is valuable, but it does not replace an authorised subject-offer process.

58. A later examination year needs a later check

The 2027 SEC begins a new qualification naming framework, but a child entering Secondary 1 in 2027 will normally sit later. AI tools, syllabus details and permitted-assistance instructions can change.

Illustration: A family relies on a 2027 K354 authenticity summary for an exam several years later.

Useful next action: Revisit the relevant official syllabus and school instructions before any assessed task.

Important boundary: Never present a current rule as guaranteed forever.

59. A family agreement can be short

A sensible home agreement might say: attempt the task, use approved help only, verify important facts, explain the answer and disclose assistance where required. It should be understandable to the child.

Illustration: A teenager writes a two-sentence personal rule for using digital support on homework.

Useful next action: Discuss what the agreement means for a real assignment and ask the teacher about any uncertainty.

Important boundary: A family agreement cannot override formal examination or school rules.

60. A positive closing question

The best outcome of educational AI is a learner who can do more for themselves, identify errors and judge sources. The tool should recede as understanding grows.

Illustration: A child initially needs a hint for a graph question, then explains a fresh graph accurately without assistance.

Useful next action: Celebrate the independent explanation and the decision to check evidence.

Important boundary: PG1, PG2 and PG3 are admission arrangements, not rankings of who deserves technological opportunity.

Questions parents ask about student AI use

Can students use AI to study for the 2027 SEC?

Educational support can be useful where permitted; formal assignment and examination rules control allowed assistance.

Does being PG3 give a child special AI permissions?

No. Posting Group is not a software-use authorisation.

What are MOE’s four AI education principles?

Agency, Inclusivity, Fairness and Safety.

Does MOE provide any AI-enabled learning features?

Yes. SLS includes reviewed AI-enabled learning features under MOE governance arrangements.

Can AI rewrite my child’s examined coursework?

Do not present generated or externally written work as the student’s original assessed work. Follow subject rules.

Does SEAB mention AI in Exercise and Sports Science?

The 2027 K354 syllabus explicitly requires authentic work and prohibits passing off AI-generated content as one’s own.

Can AI help make a study quiz?

Where authorised, it can provide supplementary practice questions, but students should verify accuracy.

Can AI invent academic references?

Yes. Always verify a reference, quotation and numerical claim against the original source.

Can a generated graph explanation be wrong?

Yes. Check the chart axes, scale, values and conclusion independently.

Can AI produce mathematically wrong answers?

Yes. Test the reasoning and compare with teacher-approved methods.

Can the child share classmates’ marks with an AI?

Do not upload private student information to unapproved services.

Does AI use need to be disclosed?

Follow the school and particular assessment instructions on acknowledgement and permitted assistance.

Is giving feedback the same as ghostwriting?

No. Feedback can guide the student’s revision; ghostwriting replaces the student’s own work.

What if a student already submitted AI-generated work?

Follow school procedures honestly and seek guidance from the relevant teacher or coordinator.

Can a student use personal AI software during an e-exam?

Only if expressly authorised, which should never be assumed from ordinary home use.

How can parents check understanding?

Ask the student to explain the result and solve a new similar problem unaided.

Should families pay for expensive AI tools?

Not automatically. Choose school-approved, appropriate learning resources that fit actual needs.

Can students upload paid textbooks without permission?

Copyright and school sharing rules still apply.

Is AI a guarantee of higher SEC grades?

No. Understanding, authenticity, subject knowledge and formal examination performance remain essential.

Which sources control the rules?

The school’s instructions, the exact SEAB subject syllabus and MOE’s official AI-in-Education guidance.

Connected eduKateSG learning guides

These pages cover the underlying subjects, examination components and student skills. The AI guidance here is an integrity-and-learning companion, not a substitute for the registered subject’s formal assessment rules.

Official MOE and SEAB references

A good conversation at home

Ask the learner what they understood better after using a digital tool, which part they checked and whether they could explain the answer again without the tool. That creates a constructive habit of agency instead of fear.

The aim is not to discourage curiosity about AI. It is to support capable, honest students who understand their own work and can use technology responsibly at any subject level.