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PG1, PG2 and PG3 Computing and Digital Literacy | G1, G2, G3 SEC, AI, Coding and Cyber Wellness

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by

eduKate Asia
Three students sit around open books and worksheets at a classroom table, reading, writing and discussing the work together.

What do PG1, PG2 and PG3 mean for Computing and digital literacy in Singapore secondary schools? They describe the student’s Secondary 1 Posting Group, not a national examination subject. The 2027 Singapore–Cambridge Secondary Education Certificate (SEC) separately lists Computing at G1 K127, G2 K237 and G3 K349. Digital literacy, coding opportunities, cyber wellness and the official examined subject are related but not identical.

The welcoming way to understand the choices is to begin with what the child wants to do: organise information clearly, solve a problem with code, test a spreadsheet, create a digital product or evaluate a claim online. Some of these activities happen across many school subjects; others appear in a formal Computing syllabus or school-specific programme. Each deserves accurate guidance.

This guide connects the national syllabus codes with practical examples of programming, digital information skills, school ALPs, responsible AI use and later subject choices. It is not a ranking of learners. The goal is to make Computing accessible, interesting and reliable for every family.

Independent eduKateSG parent guide. SEAB 2027 G1/G2/G3 catalogues and current MOE Full Subject-Based Banding guidance checked 16 October 2026. Specific subject offers, prescribed software and examination details should be confirmed with the school.

Quick answer: Computing versus digital literacy

  • PG1, PG2, PG3: Secondary 1 admission categories.
  • G1 Computing: 2027 SEC K127; listed tools include Word, Excel, PowerPoint and Scratch.
  • G2 Computing: 2027 SEC K237; listed tools include Excel, PowerPoint and Scratch.
  • G3 Computing: 2027 SEC K349; references include Python, JupyterLab Desktop and Excel.
  • Digital literacy: wider competencies developed across school, not restricted to Computing candidates.
  • ALP or robotics: may be a school-specific programme, not automatically an examined Computing subject.
  • Best next step: confirm the student’s exact course, level and current syllabus.

Choose the question you want answered

1. PG1, PG2 and PG3 are not computing grades

Posting Groups organise entry to Secondary 1. G1, G2 and G3 describe the level of an individual subject, and Computing has separate examined entries at all three levels for the 2027 SEC.

For example: One child may enter through PG2 and later study another eligible subject at G3 while enjoying digital design. Their school admission label does not describe all their abilities.

Try this with the learner: Write the subject name and level exactly as the school offers them, then match lessons to the current syllabus.

Keep the distinction clear: Do not look for a national PG2 Computing paper. The useful reference is G2 Computing K237.

2. Digital literacy belongs to many subjects

Digital literacy means finding, evaluating, using, creating and sharing information responsibly with digital tools. Students develop these competencies throughout school, including when Computing is not an examined elective.

For example: A Geography task may require comparing online sources, while English may require checking whether an image supports a claim. Both involve digital literacy without changing the student’s examination subject.

Try this with the learner: Invite the learner to explain where information came from and how they checked it before accepting it.

Keep the distinction clear: Taking Computing is not the only route to becoming digitally capable, just as using a computer does not automatically make someone a programmer.

3. The three SEC Computing codes

SEAB’s 2027 school-candidate directory lists Computing at G1 K127, G2 K237 and G3 K349. Each is a separate syllabus with teaching and assessment appropriate to its level.

For example: A student preparing for G1 K127 should not automatically use the software and practice questions intended for K349 simply because both articles mention computers.

Try this with the learner: Keep a screenshot-free written list of the actual subject code, examination year and teacher-specified resources.

Keep the distinction clear: An official subject catalogue lists national syllabuses, not a promise that every school can offer every option.

4. How PG1 families approach Computing

PG1 usually indicates that most initial academic subjects begin at G1, subject to the official individual offer. Digital curiosity can begin through school activities, coding clubs and ordinary classroom tools regardless of the admission group.

For example: A learner who enjoys making a Scratch animation can develop logical thinking and storytelling even if Computing is not selected as their formal upper-secondary subject.

Try this with the learner: Ask what the student made, how they knew the project worked and what change they would test next.

Keep the distinction clear: A learner’s posting group does not impose a ceiling on curiosity, creativity or the ability to develop technical skill.

5. How PG2 families approach Computing

PG2 generally begins most subjects at G2. Under Full Subject-Based Banding, appropriate subject-level changes may be possible based on school criteria, making the actual timetable more useful than a single label.

For example: One learner might take G2 Mathematics and G3 Mother Tongue while preparing a technology project through a school ALP. Different parts of that timetable answer different educational questions.

Try this with the learner: Separate the Computing subject offer from other digital activities, then identify the actual learning objective for each.

Keep the distinction clear: Do not assume participation in a technology programme changes the level of the student’s examined subjects.

6. How PG3 families approach Computing

PG3 generally starts most academic subjects at G3, but does not automatically place every student in SEC Computing K349. Electives follow school subject-combination and eligibility arrangements.

For example: A student may enjoy G3 Mathematics and prefer Art as an elective, while still building useful digital-literacy habits for research and schoolwork.

Try this with the learner: Ask which subject best fits interests, existing foundations, workload and the real school offerings.

Keep the distinction clear: Avoid implying that every PG3 student must become a coder or that Computing is more valuable than other suitable subjects.

7. Why the 2027 codes are useful

The new K-codes let a family find the right examination syllabus and compare it with older resources. SEAB lists K127 and K237 as newly introduced Computing syllabuses, while K349 has the earlier GCE O-Level reference code 7155.

For example: A parent buys a book marked 7155 and assumes it will cover every G-level. The exam code reminds the family to check scope and examples before using it.

Try this with the learner: Read the catalogue and syllabus year rather than selecting a worksheet from a search-result title alone.

Keep the distinction clear: Old materials can provide ideas, but a shared topic or similar subject title does not prove the papers are interchangeable.

8. G1 Computing can include productivity tools

The SEAB 2027 G1 Computing catalogue identifies Microsoft Word, Excel and PowerPoint as well as Scratch as listed software. These tools support practical digital problem-solving and communication.

For example: A student can create a clear document, use a spreadsheet to organise observations or build a short block-based program, each with a different purpose.

Try this with the learner: Ask which application the school is teaching and what the final output must accomplish for the user.

Keep the distinction clear: The current official syllabus and teacher determine assessed tasks; merely opening a software program does not demonstrate mastery.

9. G2 Computing uses another software scope

For G2 K237, SEAB lists Excel and PowerPoint with Scratch in the software reference. This is not identical to the G1 tool list and should not be flattened into one universal Computing exam.

For example: A learner who can make attractive slides may still need practice constructing a correct spreadsheet relationship or logical control sequence.

Try this with the learner: Inspect the task’s expected output, test the steps and use the actual G2 syllabus for examination preparation.

Keep the distinction clear: Do not assume Word skills are assessed in exactly the same way at G2 simply because G1 uses Word.

10. G3 Computing includes Python

The 2027 G3 Computing entry K349 continues from the earlier GCE O-Level Computing code. SEAB’s candidate software references include Python, JupyterLab Desktop and Excel.

For example: A learner who enjoys Scratch may later encounter Python, where typed statements and program structure need careful attention to syntax and meaning.

Try this with the learner: Prepare through teacher-approved programming practice, test cases and explanation of algorithms rather than only memorising language commands.

Keep the distinction clear: A self-taught app project is a useful interest but does not automatically cover the formal G3 assessed syllabus.

11. Algorithms are sequences with a purpose

An algorithm is a set of steps for achieving a goal under defined rules. Clear algorithms identify inputs, processing and outputs, and make their assumptions visible.

For example: A student writes steps for sorting a list of names, then notices the process does not explain how to handle two identical names.

Try this with the learner: Have the learner describe the method in plain language before choosing code blocks or typed instructions.

Keep the distinction clear: A program that appears to work for one easy example may still fail when the input or conditions change.

12. Sequence is a foundational idea

Sequence means executing steps in an intended order. It appears in programs, spreadsheet procedures and everyday tasks such as preparing a report.

For example: A student calculates a total before applying a discount and gets a different result from applying the discount to individual eligible items.

Try this with the learner: Write down each step and ask whether changing the order alters the output or violates a requirement.

Keep the distinction clear: A computer executes instructions according to its actual logic, not the intention the student hoped it would infer.

13. Selection introduces decisions

Selection uses conditions to decide which action follows. Students must understand precisely when a condition is true, false or not meaningful.

For example: A fictional library system permits book borrowing if membership is valid and the borrowing limit has not been reached. Confusing and with or changes the outcome.

Try this with the learner: Test the decision rule with examples that satisfy one condition, both conditions and neither condition.

Keep the distinction clear: A condition that sounds reasonable in ordinary English still needs accurate logical interpretation.

14. Repetition needs a stopping rule

Loops repeat steps according to a condition or count. Students can use them to avoid needless duplication, but must ensure the process is finite and produces the intended result.

For example: A program keeps asking for a number even after valid input is supplied because the stopping condition refers to the wrong variable.

Try this with the learner: Trace a few cycles on paper and explain when the loop should stop.

Keep the distinction clear: A very short program is not necessarily correct if it repeats forever or omits an important case.

15. Variables represent changing information

Variables let a program store and work with values. Good variable naming helps readers understand what the program is meant to calculate.

For example: A learner stores total_price and quantity in separate variables, then accidentally multiplies a previous price by the new quantity.

Try this with the learner: Sketch the current value of each variable after every important program step.

Keep the distinction clear: A plausible final number does not prove the correct variable was used at every stage.

16. Input validation is different from data accuracy

Validation checks whether a value satisfies rules such as type or range. Accuracy asks whether the value correctly describes reality. These are distinct checks.

For example: A form accepts a three-digit age that falls inside its programmed range, yet the user may have typed the wrong number.

Try this with the learner: Design a test that checks the input rule and a separate question about whether the recorded information is trustworthy.

Keep the distinction clear: Passing a validation check does not establish that the underlying data are true.

17. Test cases make programming evidence-based

A test case specifies an input, the expected outcome and the observed outcome. This helps students diagnose errors instead of saying a program looks right.

For example: A calculator works for 2 plus 3 but fails for negative numbers because the code assumes all inputs are positive.

Try this with the learner: Test ordinary values, boundary values and carefully chosen exceptional cases where the syllabus asks for them.

Keep the distinction clear: One demonstration is not a general proof of correctness, especially when important inputs were never tested.

18. Debugging is a method, not a punishment

Debugging locates the cause of unexpected behaviour and makes a targeted correction. It combines observation, a hypothesis and a new test.

For example: A student discovers that their animation skips a scene only when a particular button is pressed. The event rule is the useful place to investigate.

Try this with the learner: Record the failing test, identify the likely step, adjust one factor and repeat the test.

Keep the distinction clear: Making many unrelated code edits at once makes it difficult to know which correction solved the problem.

19. Scratch teaches ideas that transfer

Block-based programming can help students understand control flow, events, repetition and variables without beginning with the syntax demands of a typed language.

For example: A learner creates a small quiz in Scratch and then realises the answer-checking logic is not the same as how the interface looks.

Try this with the learner: Ask the student to explain the algorithm separately from the visual design.

Keep the distinction clear: Being able to arrange attractive blocks does not automatically show that the underlying conditions and outputs have been verified.

20. Python is not a measure of intelligence

Typed programming introduces additional vocabulary, syntax and debugging demands. A student can build this gradually with small problems and accurate explanations.

For example: A student writes a loop with the right idea but incorrect indentation. The concept and the syntax need separate corrections.

Try this with the learner: Begin with short examples, trace values and follow the school’s permitted environment and learning sequence.

Keep the distinction clear: Do not judge a learner’s future technical potential from one syntax error or from whether they began with Scratch.

21. Spreadsheets are models with dependencies

A spreadsheet can organise data and calculate results, but correct outputs depend on formulas and references. Students should know how a result changes when input values change.

For example: A total works for the first row but fails after copying a formula because one reference moved unexpectedly.

Try this with the learner: Check which cells supply the values and whether formulas should use relative or fixed references.

Keep the distinction clear: A neatly formatted spreadsheet with an incorrect formula is still an inaccurate model.

22. Charts need units and honest scales

A chart communicates relationships through labels, axes and scales. Readers should be able to identify the measured quantity before making conclusions.

For example: A graph shows a dramatic rise because the vertical axis begins close to the smallest value, making a modest change appear enormous.

Try this with the learner: Read the chart title, axes, units and range before interpreting a trend.

Keep the distinction clear: Visual impact is not proof of an important effect; the underlying data and context matter.

23. Presentations should help the audience

Slide-making combines selection of information, hierarchy and clear communication. Learning should focus on the audience’s needs rather than decorative effects alone.

For example: A report about recycling shows impressive animations but hides the actual quantity collected in tiny text.

Try this with the learner: Ask which fact the audience should remember and organise the slide around it.

Keep the distinction clear: A large number of transitions does not make the explanation more accurate or persuasive.

24. Document creation is information design

Digital documents must be readable, logically organised and appropriate to their purpose. Headings, clear terminology and sensible layout can improve an otherwise correct explanation.

For example: A set of class instructions becomes easier to follow when actions are grouped under concise headings and an example appears next to a difficult step.

Try this with the learner: Have the child test the document with a reader who was not involved in writing it.

Keep the distinction clear: A professional-looking template does not correct an unclear instruction or unsupported claim.

25. Digital source checking belongs in Computing too

Students should learn to distinguish the origin of information, its publication date, evidence and possible uncertainty. These skills help in academic subjects and everyday online life.

For example: A social post claims a school rule changed, but the screenshot is old and the school website shows a different current notice.

Try this with the learner: Compare the original official source, date and context before sharing the claim.

Keep the distinction clear: Popularity, confidence and attractive presentation are not reliable substitutes for verifiable evidence.

26. Cyber wellness is a different curriculum component

Schools develop cyber wellness through Character and Citizenship Education and student-development programmes. It supports respectful behaviour, privacy and responsible digital participation, including among students not taking Computing.

For example: A class discusses how to respond when an unkind screenshot circulates in a group chat. The lesson concerns judgement and care for others.

Try this with the learner: Encourage thoughtful online conduct and show the child how to use the school’s trusted reporting and support channels.

Keep the distinction clear: Cyber wellness is not a separate national G1/G2/G3 SEC Computing paper.

27. Passwords and identity are practical skills

Good digital habits include protecting account credentials, recognising suspicious requests and using trusted login channels. These matter regardless of an examined subject choice.

For example: A message promises a prize if a student enters their school password on an unfamiliar webpage.

Try this with the learner: Discuss why the request is suspicious and use official support to verify it rather than following the embedded link.

Keep the distinction clear: Never share the child’s login credentials with a tutor, an online stranger or an unofficial automated service.

28. Data privacy and consent need care

When students gather images, feedback or class information for projects, they should respect privacy and understand how information will be stored or shared.

For example: A learner wants to publish classmates’ full names and photographs in a coding portfolio without asking them.

Try this with the learner: Use fictional sample data or permitted anonymous information when demonstrating a project.

Keep the distinction clear: Being technically able to upload information does not mean it is appropriate or authorised to publish it.

29. AI tools can help, but require verification

Generative AI can suggest explanations, code fragments and design ideas, yet it may make errors or invent details. Students benefit most when they remain responsible for checking outputs and understanding their work.

For example: An AI suggestion produces code that appears tidy but uses a function unavailable in the school’s permitted environment.

Try this with the learner: Ask the learner to explain each step, test the result and follow school rules about permitted assistance.

Keep the distinction clear: AI-generated output must not be passed off as original assessed work when examination or school rules require personal effort.

30. Prompting is not the same as computational thinking

A prompt can help express a request to an AI system. Computational thinking also involves decomposing a problem, constructing rules, evaluating solutions and verifying outcomes.

For example: A student asks an AI tool to sort records but cannot explain what should happen when two records have equal values.

Try this with the learner: Write the sorting requirements independently and test the resulting solution against those requirements.

Keep the distinction clear: A fluent AI-generated answer is not evidence that the user understands the program or that it is correct.

31. Accessibility is part of useful digital design

Technology should help real users. Readable text, clear controls, adequate contrast and understandable instructions make tools more usable for different people.

For example: A classroom website has pale text on a light background. It looks calm but some readers struggle to see important instructions.

Try this with the learner: Ask another person to try a prototype and record which steps were difficult.

Keep the distinction clear: Ease of use should be tested with users rather than assumed from the designer’s own experience.

32. Computing and Mathematics reinforce each other

Mathematical reasoning helps with variables, patterns, conditions and data. Programming can also make mathematical relationships concrete when learners visualise and test them.

For example: A program plots a pattern but produces an unexpected jump because the starting value was entered incorrectly.

Try this with the learner: Connect each formula to its meaning and test the relationship with a small hand-calculated example.

Keep the distinction clear: An impressive graph does not substitute for checking the Mathematics behind it.

33. Computing and English reinforce each other

A student needs language to interpret a brief, name functions, document decisions and explain why a solution works. Communication is part of good technical learning.

For example: Two people read the same instructions differently because a sentence does not say whether the limit is inclusive.

Try this with the learner: Rewrite the requirement in clear language before writing the program.

Keep the distinction clear: A correct block of code may still fail the intended task when the question was misunderstood.

34. Computing and Science use similar reasoning

Scientific investigation and program debugging both use evidence: identify a claim, test it, observe the result and revise the explanation. The objectives differ, but the habits can reinforce each other.

For example: A sensor simulation reports a surprising value. The learner asks whether the algorithm, simulated environment or interpretation caused the discrepancy.

Try this with the learner: Use teacher-approved simulations and supplied data to practise careful checking.

Keep the distinction clear: A simulation is a model with assumptions, not automatic proof of how a physical device behaves.

35. Computing is not the same as D&T or Electronics

D&T develops design and making processes; Electronics studies circuits and systems; Computing focuses on digital information and computational problem-solving. Some projects draw on all three, but their SEC subjects remain separate.

For example: A small smart-home demonstration might involve a sensor, a physical enclosure and program code. Each part raises different questions.

Try this with the learner: Identify what is being examined before choosing a study guide, and connect other disciplines only when relevant.

Keep the distinction clear: The presence of a circuit or a microcontroller does not make the activity a G3 Electronics or G3 Computing qualification.

36. ALP coding is not automatically SEC Computing

An Applied Learning Programme may include robotics, programming or data projects for a whole cohort. It is school-specific and should not be confused with national examined Computing.

For example: A learner attends a robotics workshop and enjoys block coding but never registered for K127, K237 or K349.

Try this with the learner: Ask which programme the activity belongs to and which official syllabus, if any, it supports.

Keep the distinction clear: Completing an ALP project does not automatically add an SEC Computing result to a certificate.

37. How to choose Computing in Secondary 2

Upper-secondary subject selection should consider interest, prerequisites, the school-approved list and a manageable weekly workload. A student may enjoy using computers without enjoying sustained algorithm design.

For example: One learner likes digital art, another likes debugging and a third enjoys building reports in spreadsheets. These are related but different kinds of activity.

Try this with the learner: Try suitable school-approved tasks and ask about the course’s actual written and practical requirements.

Keep the distinction clear: A friend’s choice or the apparent popularity of AI jobs is not enough evidence that the elective is right for a particular child.

38. Peicai offers one useful real-school example

Peicai Secondary describes G1, G2 and G3 Computing electives for upper-secondary students from 2026. This illustrates how a specific school can offer all three levels in an approved programme.

For example: A parent comparing schools may find that one offers Computing widely while another has different elective strengths or timetable constraints.

Try this with the learner: Check school websites and MOE SchoolFinder for the current cohort and ask about entry rules.

Keep the distinction clear: One school’s published arrangement is an example, not a promise about every secondary school in Singapore.

39. Preparing for a practical Computing examination

An examined Computing subject may require using designated software and completing tasks under controlled conditions. Accurate practice must use the actual syllabus and candidate instructions.

For example: A learner can solve an algorithm at home but loses time when unfamiliar with the permitted interface or file-saving process.

Try this with the learner: Practise the approved environment and confirm what help, templates or software are allowed.

Keep the distinction clear: Do not assume private lessons, unofficial tools or home-installed AI assistants can be used during a formal assessment.

40. Preparing for written Computing explanations

Programming principles also require clear words, diagrams or pseudocode where specified. Students should explain why an algorithm handles particular inputs rather than only describe what appears on the screen.

For example: A question asks why a loop terminates. The learner names the loop but does not show how its controlling condition changes.

Try this with the learner: Trace values and use a short claim-and-evidence explanation linked to the example.

Keep the distinction clear: Knowing a programming keyword is not the same as explaining the behaviour of the algorithm.

41. A weekly learning routine that works

Digital competencies grow from a modest pattern of creating, testing, explaining and revisiting ideas. The plan should fit academic work, CCAs and ordinary rest.

For example: A student spends one short session building a feature, another session testing edge cases and a final session explaining what changed.

Try this with the learner: Keep a simple learning log: intended result, test performed, actual result and next improvement.

Keep the distinction clear: Long screen hours without clear feedback are not necessarily better learning than focused, thoughtful practice.

42. Choosing resources by examination year

The SEC begins in 2027. A student who will sit in a later year needs that later examination-year syllabus when it becomes available, even if older examples still help build foundations.

For example: A child in Secondary 1 in 2027 normally has several school years before their eventual SEC, depending on the school pathway.

Try this with the learner: Record the anticipated examination year and revisit the official syllabus catalogue rather than assuming K127 remains unchanged forever.

Keep the distinction clear: New specifications, software versions and approved subject offerings can change. Historical materials need honest labelling.

43. What can digital literacy lead to later?

Computing can support exploration of information technology, engineering, data, design and many other fields. Entry to each post-secondary programme follows its own published subject prerequisites.

For example: One student enjoys building accessible websites, while another prefers experimenting with data. Their next educational choices may be quite different.

Try this with the learner: Look at actual diploma modules, JC subject offerings or other current pathways rather than deciding from a technology buzzword.

Keep the distinction clear: A G3 Computing result alone does not guarantee entry to a named IT or AI programme.

44. The best family question tonight

A helpful conversation moves from labels to what the learner can explain and improve. Digital work is especially rewarding when students can show a working idea and discuss its limits.

For example: Ask the child to teach you something they made, identify one possible error and show how they tested it.

Try this with the learner: Celebrate the clear explanation as well as the finished screen or program.

Keep the distinction clear: The student’s original PG1, PG2 or PG3 admission arrangement does not limit a lifetime of learning new technologies.

Computing, digital literacy and SEC FAQs

Does PG2 mean my child sits a PG2 Computing exam?

No. PG2 is an admission group. A registered G2 Computing entry for 2027 is K237.

Which Computing codes exist in the 2027 SEC?

G1 K127, G2 K237 and G3 K349 appear in SEAB’s school-candidate lists.

Is Computing compulsory for every secondary student?

No. Digital literacy develops across school activities, while Computing is an examined elective subject where offered.

Is coding in ALP the same as SEC Computing?

Not automatically. A school-specific ALP may use programming without being a formally registered national Computing subject.

Does G1 Computing use Scratch?

SEAB’s 2027 G1 catalogue lists Scratch and Microsoft Word, Excel and PowerPoint among the specified software.

Does G2 Computing use Scratch?

Yes. SEAB’s reference software for K237 includes Scratch, Excel and PowerPoint.

Does G3 Computing use Python?

The 2027 G3 Computing software references include Python and JupyterLab Desktop, together with Excel.

Can a PG1 learner become an excellent programmer?

There is no Posting Group restriction on learning programming for personal interest. Formal subject offers follow school eligibility rules.

Does G3 Computing guarantee an AI career?

No. A formal qualification is one step; later courses and occupations have their own knowledge and entry requirements.

How can parents check whether code really works?

Ask for the expected output, test several inputs and let the learner explain any mismatch.

Is a single successful program run good enough?

Not always. More representative and boundary test cases may reveal errors.

Should students use AI-generated code as their own assessed work?

They must follow school and exam rules on authenticity and permitted assistance. Understanding and testing remain essential.

Is cybersecurity a separate Computing exam for everyone?

No. Cyber wellness and digital safety also appear through wider education, such as CCE.

Can a student change Computing subject levels?

Any eligible changes follow the school’s current Full SBB and subject-offering rules; they are not automatic.

What happens if the school does not offer Computing?

Ask about other current approved school programmes or future elective choices. An external club is not equivalent to SEC registration.

Does a Computing result count for polytechnic admission?

Only under the applicable route and course subject requirements. Check MOE and institution rules for the correct year.

Can Computing support Mathematics learning?

Yes, students can practise logic, relationships and data, while still addressing their formal Mathematics syllabus directly.

How do I prepare for the 2027 exam?

Identify the registered G-level, examination code, prescribed software and school-approved assessment tasks.

Should I compare siblings by their Posting Groups?

A more useful comparison is each child’s own progress with practical skills and independent problem-solving.

Where do I confirm the subject details?

Use the current SEAB G1/G2/G3 school-candidate catalogues and the school’s current subject offer.

Connect the full eduKateSG learning ecosystem

These connected pages are designed for different questions. The Computing comparison explains formal G-level syllabus differences, the digital-literacy guide explores broader responsible technology use, and the parent hubs help families make school and pathway choices.

Official MOE and SEAB sources

A happy way to continue learning

Ask the student to demonstrate one small digital creation and tell you what they tested. A clear explanation of an idea, a sensible correction and a more usable design are all forms of progress. These can be enjoyed in PG1, PG2 or PG3 and at every subsequent stage.

No single posting label determines which technologies a child can learn over a lifetime. Official subject offers provide structure; curiosity, feedback and careful practice help the learner go further.

Arrange a subject-focused consultation

Contact eduKate Singapore or message eduKateSG about the student’s actual academic level and learning needs. Bring a representative school task and the registered syllabus so any additional support is precise.