Top 200 Vocabulary for Secondary 2 Computing Foundations | Algorithms, Scratch, Spreadsheets and SEC Pathways

Secondary 2 Computing vocabulary helps Singapore students prepare for digital tasks now and make informed upper-secondary subject decisions later. These 200 practical computing terms cover hardware, files, the internet, spreadsheets, Scratch, algorithms, debugging, media creation, security and AI literacy. Start with the numbered word list below, then use the examples to learn how a computer-based solution actually works.

Important syllabus clarification: this is an independent eduKateSG study selection, not a compulsory MOE Secondary 2 Computing syllabus or an official 200-word examination list. Computing is offered as a specialised subject at upper secondary in participating schools, while lower-secondary computing-related experiences vary through digital literacy, school programmes and the Code for Fun initiative. Under the 2027 SEC framework, Computing is listed at G1 (K127) and G2 (K237), alongside G3 subject arrangements; subject availability and choices depend on the school.

Quick information:

Words 1–60: parts of a computer, file management and networks;
words 61–120: spreadsheets, algorithms, Scratch and programming basics;
words 121–160: debugging, testing and presenting information;
words 161–200: cybersecurity, generative AI, ethical design and real-world problem-solving;
after the list: original step-by-step practice problems, a four-week routine, differences between Secondary 2 exploration and SEC papers, and useful sources.

Top 200 Secondary 2 Computing foundation words and meanings

1. Computing systems and computer hardware — words 1–20

computer — An electronic system that accepts input, processes data and produces output according to instructions.
hardware — The physical components of a computer system.
software — Instructions and programs that enable a computer to perform tasks.
processor — The component that carries out instructions and coordinates computation.
central processing unit — The main processor often abbreviated CPU.
memory — Electronic space used to hold information for processing.
random access memory — Main working memory that typically loses its contents when power is removed.
storage — Hardware or services retaining files and data for later use.
solid-state drive — A storage device using electronic memory rather than rotating disks.
hard disk drive — A storage device using magnetic rotating disks.
motherboard — The main circuit board connecting computer components.
input device — Equipment that supplies data or commands to a computer.
output device — Equipment that presents results from a computer.
keyboard — An input device containing keys for text and commands.
mouse — An input device used to control a pointer.
touchscreen — A display that also detects touch input.
microphone — An input device that captures sound.
webcam — A camera used to provide digital video input.
printer — An output device transferring digital content to physical media.
operating system — Software managing hardware resources, files and application execution.

2. Files, data units and digital organisation — words 21–40

bit — A binary digit with value zero or one.
byte — A group of eight bits, often used as a unit of digital data.
kilobyte — A data unit commonly defined as one thousand bytes.
kibibyte — Exactly 1,024 bytes, abbreviated KiB.
megabyte — A data unit commonly defined as one million bytes.
gigabyte — A data unit commonly defined as one billion bytes.
terabyte — A data unit commonly defined as one trillion bytes.
file — A named collection of digital information.
folder — A container used to group files and other folders.
file extension — A suffix that often signals a file’s format.
document format — A representation specifying how written content is stored.
spreadsheet file — A digital workbook containing cells, calculations or charts.
image file — A file representing visual information such as a photograph or drawing.
audio file — A file containing recorded or synthesised sound data.
video file — A file representing a sequence of moving images and often audio.
compression — Representing data using fewer bits, sometimes with or without loss.
backup — An additional copy kept so information can be restored after a problem.
version history — A record of earlier states of a file or project.
metadata — Data describing other data, such as file dates or dimensions.
file path — A description of a file’s location within a directory system.

3. Networks, the internet and communication — words 41–60

network — A group of connected devices sharing information or resources.
local area network — A network connecting devices within a limited area.
wireless network — A connection using radio signals instead of cables.
router — A device directing data between networks.
modem — Equipment converting data signals for a particular communication link.
internet — The worldwide system of interconnected networks.
World Wide Web — A system of linked resources accessed over the internet.
website — A collection of related web pages or resources.
web browser — An application for visiting websites and viewing web content.
search engine — A service that retrieves information based on queries.
uniform resource locator — A web address identifying a resource, often called a URL.
hyperlink — A selectable connection from one digital resource to another.
server — A system providing resources or services to connected clients.
client — A device or program requesting a service from another system.
cloud storage — File storage accessed through remote networked servers.
download — Receiving data from another system onto a device.
upload — Sending data from a device to a remote system.
bandwidth — The amount of data a link can carry within a unit of time.
latency — The delay before data begins arriving or an action receives a response.
packet — A small unit of data transmitted through a network.

4. Spreadsheets, calculations and useful information — words 61–80

spreadsheet — A grid-based application used to organise and calculate data.
workbook — A spreadsheet file containing one or more worksheets.
worksheet — One tab or sheet within a spreadsheet workbook.
row — A horizontal sequence of cells.
column — A vertical sequence of cells.
cell — The intersection of a spreadsheet row and column.
cell reference — An identifier such as B3 pointing to a particular cell.
range — A selected rectangular or other group of spreadsheet cells.
formula — A calculation instruction usually beginning with an equals sign.
function — A predefined operation such as SUM or AVERAGE.
SUM — A spreadsheet function adding specified numerical values.
AVERAGE — A function computing the arithmetic mean of selected values.
COUNT — A function counting cells containing numbers.
IF function — A function returning different results based on a logical test.
relative reference — A cell address adjusted when a formula is copied.
absolute reference — A cell address fixed using appropriate spreadsheet notation.
sort — Rearranging records by a chosen field or order.
filter — Showing only records meeting specified criteria.
chart — A visual display of data such as bars or lines.
data validation — Rules restricting which values can be entered in a cell.

5. Algorithms, flowcharts and computational thinking — words 81–100

algorithm — A precise set of steps for accomplishing a task.
computational thinking — Framing and solving problems through concepts useful in computing.
decomposition — Breaking a complicated task into smaller manageable parts.
pattern recognition — Identifying repeated features across problems.
abstraction — Ignoring irrelevant detail to focus on essential structure.
sequence — Instructions performed in a specified order.
selection — Choosing different actions according to a condition.
iteration — Repeating steps until a defined condition is reached.
condition — A statement used to decide whether an action should occur.
Boolean value — A logical value that is true or false.
flowchart — A diagram showing operations and decisions in a process.
pseudocode — Structured natural language used to describe an algorithm.
start symbol — A mark identifying where a flowchart begins.
process symbol — A flowchart shape representing an action or calculation.
decision symbol — A flowchart shape representing a branching condition.
input step — An operation accepting information into a program.
output step — An operation displaying or producing a result.
trace table — A record following variable values through an algorithm.
termination — The point at which a process finishes.
edge case — An unusual valid input near the limits of a problem.

6. Programming basics and Scratch foundations — words 101–120

program — A set of computer instructions intended to perform a task.
programming language — A defined system for writing machine-executable instructions.
Scratch — A visual block-based programming environment used in education.
sprite — A programmable visual object in Scratch.
stage — The area where Scratch objects appear and interact.
event — An occurrence that triggers a programmed response.
event handler — Code responding when a specific event occurs.
block — A drag-and-drop instruction unit in visual programming.
script — A connected sequence of programming blocks or instructions.
variable — A named storage location whose value can change.
assignment — An operation storing a new value in a variable.
loop — A control structure repeating instructions.
forever loop — A loop intended to repeat continuously until stopped.
repeat loop — A loop repeating a specified number of times.
conditional branch — Instructions selected when a logical condition is satisfied.
operator — A symbol or function carrying out a calculation or comparison.
comparison operator — An operator such as greater-than used to compare values.
random number — A value selected according to a stated random process.
coordinate — A numbered position locating a sprite on a stage.
broadcast message — A signal used to coordinate different Scratch scripts or sprites.

7. Debugging, testing and reliable programs — words 121–140

bug — An error in a program’s design or implementation.
debugging — Finding and correcting the cause of incorrect program behaviour.
syntax error — Code that violates a programming language’s grammar.
logic error — Instructions that run but produce an unintended result.
runtime error — A problem arising while the program is executing.
test case — A specified input and expected outcome used to assess behaviour.
expected output — The result a correct solution should produce for a test.
actual output — The result the program really produces.
test plan — An organised selection of cases and checks for a program.
boundary testing — Testing values at or near allowed limits.
unit test — A check of an individual component or function.
integration test — A check that components work correctly together.
error message — Information reporting a detected problem.
step-through — Examining a program one instruction at a time.
breakpoint — A point where execution is paused for inspection.
refactoring — Reorganising code while preserving its intended behaviour.
code comment — A note explaining a choice or purpose within source code.
readability — How easily a human can understand the code.
documentation — Written explanation of a program, system or process.
reproducibility — The ability to obtain the same result by repeating stated steps.

8. Digital documents, media and presentation — words 141–160

word processor — Software for creating and editing formatted text documents.
text alignment — Positioning text relative to a margin or chosen axis.
heading style — Consistent formatting identifying a document section.
paragraph spacing — The space separating paragraphs.
bullet list — A list where each item begins with a marker.
table — An arrangement of information in rows and columns.
slide — One screen or page of a digital presentation.
slide layout — The arrangement of text and other elements on a presentation slide.
contrast — A difference in visual qualities that helps distinguish content.
visual hierarchy — Ordering items so the most important receive attention first.
image resolution — The amount of pixel detail in an image.
pixel — A small picture element in a digital raster image.
aspect ratio — The relationship between an image’s width and height.
crop — Removing outer parts of an image to change framing.
caption — Explanatory text accompanying an image or figure.
timeline — A visual or written sequence of events.
storyboard — A plan showing stages of a video or presentation.
transition effect — A visual effect occurring between slides or clips.
accessibility — Making content usable for people with different needs.
alt text — A concise written description of meaningful image content.

9. Cybersecurity, AI and digital responsibility — words 161–180

password — A secret used to verify an account user’s identity.
passphrase — A sequence of words used as a potentially memorable secret.
multifactor authentication — A login process requiring more than one verification factor.
phishing — A deceptive message designed to steal information or cause unsafe action.
malware — Software intended to cause harm or unauthorised activity.
virus — A type of malicious program capable of infecting other files or programs.
ransomware — Malware attempting to deny access or demand payment.
privacy — Control over access to information about a person.
personal data — Information relating to an identifiable individual.
encryption — Transforming information to make it unreadable without appropriate access.
digital footprint — Records and traces left by online activity.
copyright — Legal rights over original creative expression.
licence — Terms defining how software or content may be used.
open source — Software whose source code is made available under a specified licence.
generative AI — An AI system producing outputs such as text or images.
AI hallucination — A plausible-looking AI output that is false or unsupported.
deepfake — Synthetic or altered media made to imitate a person or event convincingly.
misinformation — False information shared without necessarily intending deceit.
disinformation — False information intentionally spread to mislead.
fact-checking — Checking claims against reliable evidence and original sources.

10. Real-world computing choices and future pathways — words 181–200

user requirement — A need the proposed software or solution should satisfy.
design constraint — A limit such as time, budget, equipment or accessibility.
prototype — An early version developed to test a proposed solution.
user interface — Controls and visual elements through which a person interacts with software.
user experience — How usable and suitable a system feels during a task.
usability testing — Observing users attempting tasks to identify design weaknesses.
feedback loop — Using observed outcomes to refine a process or product.
data quality — How accurate, complete and suitable collected information is.
data visualisation — Using charts or graphics to communicate data patterns.
automation — Using a system to perform tasks with reduced repeated manual work.
simulation — A model used to explore what might happen in a system.
sustainability — Maintaining long-term social and environmental viability.
e-waste — Discarded electrical and electronic equipment.
energy efficiency — Achieving useful work with reduced energy input.
digital inclusion — Helping people access and use technology despite different barriers.
ethical design — Building technology with attention to fairness, safety and consequences.
collaboration — Working with others towards a shared objective.
problem statement — A clear description of what needs to be solved.
evaluation criteria — Standards for judging whether a solution is suitable.
continuous improvement — An ongoing cycle of testing, learning and refinement.

Why Computing vocabulary matters even if the student does not choose Computing later

Almost every student uses technology to locate information, work with documents and communicate. Yet knowing how to tap a familiar icon is not the same as understanding how data flows through a system, why a calculation is wrong or how to check an online claim. Computing vocabulary turns vague actions such as “the computer did something strange” into questions that can be tested. What input was supplied? What instructions ran? Which output was expected? What actually happened?

Consider a student’s report in which a spreadsheet displays a surprising total. The learner may blame the computer. But the problem could be an incorrect cell reference, numbers stored as text, a missing row, or a formula copied with an unintended relative reference. The definitions of formula, data type, cell reference and debugging help diagnose the issue. Once the error is identified, the student can repair it rather than repeating a guess.

This skill applies beyond Computing. In Science, data must be measured and interpreted. In Mathematics, an algorithm describes steps and a model simplifies reality. In English and Humanities, verifying information matters. In design subjects, a prototype can reveal a mistaken assumption about what users need. Computing connects these disciplines through systematic thinking.

Worked example 1 — Hardware, software, input and output

Imagine a student recording an oral presentation. The microphone is an input device that captures sound. The computer uses software to process and store the recording, and headphones act as an output device for listening. The processor follows instructions; working memory supports current operations; long-term storage preserves the saved audio file. Naming the components helps the student distinguish where a problem may occur.

If no sound appears during playback, check step by step. Was the correct microphone selected? Did the app receive permission? Was the level too low? Was the file saved? Were the headphones connected to the output device? Each question tests a different possible cause. “Reinstall everything” is not a good first solution because it ignores the system’s structure and may remove useful settings.

The same reasoning can explain a printer problem. A document might exist correctly while a disconnected printer cannot receive it. A file can be saved to the wrong folder even when the text was entered correctly. Learning how components cooperate makes technology less mysterious and more manageable.

Worked example 2 — A byte, kilobyte and kibibyte are not all interchangeable

One byte contains eight bits. In decimal notation, a kilobyte commonly means 1,000 bytes; a kibibyte (KiB) means 1,024 bytes. Software and devices do not always display storage units in identical ways. If one product uses decimal units and another uses binary-based units, its reported capacity may appear different even when no file has disappeared. Distinguish a unit’s definition before performing arithmetic.

For a simple practice calculation, a file described as 5 MB in decimal terms contains about 5,000,000 bytes. That is not a promise about the number of characters, photographs or pages it stores; those depend on compression, format and content. A photograph, an editable document and an audio recording use different representations. A useful response explains what unit is being compared and why that matters.

Students should not conclude that a larger file is automatically better. A high-resolution picture may be helpful for printing but slow to transmit, while a heavily compressed image may lose useful detail. The right format depends on the task.

Worked example 3 — Spreadsheet formulas for a school activity

A class is comparing the cost of stationery for a project. In column A it enters each item, column B contains quantity, and column C contains price per item. In column D, each row’s amount can be calculated as quantity multiplied by unit price. If the first data row is row 2, a common formula is =B2*C2. Copying the formula downward uses relative references so it updates for subsequent rows.

Now suppose every item also needs the same fixed delivery cost or multiplier stored in cell F1. A formula that refers to $F$1 can keep that address fixed when copied. Without understanding absolute references, a student may unintentionally change the referenced cell in each row. The result might look like a valid number but be wrong. Therefore, always explain which quantity should change and which should stay constant.

Once the values are correct, a chart might help compare categories. A bar chart is useful for comparing separate item costs. A line chart is usually better when showing a quantity changing through ordered time. The chosen chart must answer the question rather than simply make the work look colourful. Axis titles, units and a sensible scale are part of the explanation.

Worked example 4 — An algorithm for checking a bus fare budget

Write a simple problem: a student wants to know whether their available balance covers a specified journey cost. The algorithm could be expressed in plain language. First read the balance and estimated fare. Next compare the balance with the fare. If the balance is at least as large, output “sufficient”; otherwise output “top up before the journey”. This is an example of sequence and selection.

A flowchart would start with an input, move to a decision such as balance >= fare, and branch to two outputs. The algorithm does not need sophisticated software; it can be tested with pencil and paper. Try a balance equal to the fare, a balance just below it and a negative input if allowed. The equality case is a useful boundary test. Students should explain why it belongs in the “sufficient” branch.

The algorithm is only as reliable as its assumptions. Actual fares may depend on concession eligibility, route and transport rules. An illustrative classroom algorithm is not a substitute for checking current fare information. Computing models are useful when the inputs and rules match reality.

Worked example 5 — A Scratch sprite and an event

Imagine making an original educational game where a character must move to a safe destination on a map. In Scratch, the character is a sprite and the on-screen area is the stage. A green-flag event might reset the position. Keyboard events can trigger movement. A conditional branch can check whether the sprite touched a target region and then display a success message.

Use a variable such as score to record progress. Initialise it when the game starts; otherwise the previous run might leave an unwanted value. A loop may check for movement repeatedly. A broadcast message can coordinate one sprite with another, for example when the game changes from a welcome screen to its playing scene. These are building blocks of behaviour, not just colourful shapes to drag around.

A simple test plan includes pressing each control, moving into a boundary, resetting the game and repeating the task. Students should record what they expected and what happened. Debugging is not a punishment for failure. It is the natural process of testing whether instructions express the intended idea.

Worked example 6 — Why a program can be syntactically valid but wrong

Suppose a student writes steps to calculate the average of five quiz scores. The correct arithmetic mean is the sum of the five scores divided by five. A program that adds the scores but divides by four may run without any error message. That is a logic error. It differs from a syntax error, where the program violates the rules of its programming language and may not run at all.

A trace table follows values at each step. Test simple data such as five scores all equal to ten: the expected average is ten. If the program outputs 12.5, the calculation contains a problem. The deliberately simple test makes the mistake obvious. More complex cases can follow after the basic method passes.

Debugging becomes much more efficient when students learn to isolate one cause. Do not alter three unrelated parts of a program at once without a plan, because it becomes difficult to tell which change solved or created the problem. A version history or backup helps recover earlier working states.

Worked example 7 — Creating a useful presentation rather than a decorated one

A group prepares a presentation about reducing food waste. The title should communicate the main question. Each slide should contain one or two related messages, with images that add meaning rather than distract. A readable heading, clear chart, and concise explanation help the audience understand. This is visual hierarchy: guiding attention towards what matters.

Accessibility is practical. A chart relying only on red and green may be difficult for some viewers to distinguish, so labels or contrasting shapes are useful. A photograph should have suitable alt text in an accessible digital file when the image conveys information. Tiny text that looks neat on a laptop may be unreadable from the back of a classroom.

Students can check the presentation by asking someone unfamiliar with the project to summarise the message. If the person cannot identify the key finding, revise the structure before adding more transitions. Effective computing-related communication is not measured by the number of animations used.

Worked example 8 — Cybersecurity and a suspicious school message

A student receives an urgent message claiming that their school account will close unless they enter a password through a link. The message uses a familiar logo but comes from an unfamiliar address. This could be phishing. A safe response is to avoid using the suspicious link and verify the instruction through the school’s known channels or a trusted adult.

Even a strong password does not prevent every attack. Multifactor authentication adds another layer of security, but users still need to be cautious about fraudulent prompts and sharing sensitive information. A backup protects important schoolwork from some kinds of data loss, but it should be stored and managed appropriately. Different controls address different problems.

Digital responsibility includes protecting classmates’ information. Do not share an image of a class list, contact details or private messages casually. Before uploading a file to a third-party service, consider what it contains, who can access it and whether school rules allow it. Responsible behaviour is part of computing competence, not an unrelated moral lecture.

Worked example 9 — AI-generated answers require verification

A generative AI tool may produce a polished explanation of a Science concept that sounds authoritative. The answer could still contain a wrong formula, invented statistic or non-existent source. Students should ask which claims can be checked and consult the original textbook, experiment instructions or credible references. The tool can support learning, but its fluency is not proof.

Deepfakes raise a related issue. A realistic video or voice clip can be synthetically generated or edited, so visual confidence alone does not establish authenticity. Check the origin of striking material, compare reliable reports and avoid forwarding harmful content. Singapore’s 2026 MOE updates to AI literacy and Cyber Wellness underscore why students should learn responsible verification habits.

When using AI assistance for school assignments, follow school rules and distinguish the student’s own reasoning from tool output. Copying an answer without understanding defeats the purpose of the exercise. A useful workflow asks the tool for alternative explanations, then tests them with an independent worked example.

Worked example 10 — Decide whether Computing is a good later subject

Computing may suit students who enjoy turning problems into structured steps, experimenting with programs, interpreting data or making useful digital products. But enjoyment of computer games alone does not determine readiness, and lack of prior coding experience does not necessarily rule it out. Students should investigate the actual course offered by their school, including the subject level, assessment methods, prerequisites and practical opportunities.

Under the 2027 SEC structure, G1 Computing K127 and G2 Computing K237 are listed as new examinations, and G3 Computing has its own subject arrangements. Those are later upper-secondary examination pathways; they should not be presented as compulsory Secondary 2 tests. The content and software requirements can differ by level and examination year. Check the current SEAB syllabus before making a subject choice.

A reasonable way to explore the subject in Secondary 2 is to complete a small project: identify a simple problem, draw a flowchart, build a Scratch prototype, test it with a friend and write down what did not work. This activity reveals more about interest and perseverance than a claim that “everyone must become a programmer”. Computing also includes critical and ethical thinking, user experience and useful workplace applications.

Common Computing terms that students confuse

Hardware / software: physical equipment versus the programs operating on it.
Memory / storage: working space for running tasks versus longer-term retention.
Internet / Web: interconnected networks versus a service operating on them.
Download / upload: receiving data versus sending it to another system.
Algorithm / program: a structured solution method versus executable instructions.
Variable / value: a named location versus the information currently held there.
Syntax / logic error: malformed instructions versus an incorrect method.
Formula / function: a constructed calculation versus a predefined operation.
Authentication / privacy: verifying identity does not by itself control every use of personal information.
AI output / evidence: generated material may be useful but is not automatically verified fact.

A four-week Computing foundations learning plan

Week 1 — Understand the system and organise files

Choose words 1–60. Draw the input–process–output path for one familiar activity such as recording speech or printing a page. Create a clear folder structure for schoolwork and practise saving, renaming and restoring a sample file. Discuss why backups and version history matter. Ask the learner to explain each step without looking at the glossary.

Week 2 — Spreadsheets and algorithms

Use words 61–100. Construct a small budget workbook with quantity, unit price and calculated cost. Check an edge case and create a simple chart. Then write a flowchart for a yes-or-no decision. The learner should state the intended input, the processing rule and the expected output.

Week 3 — Programming and debugging

Use words 101–140. Build a small original Scratch activity with one event, one variable, one loop and one conditional test. Attempt at least three test cases and write down any unintended behaviour. Debug a specific issue, retest it and retain the earlier version in case the change introduces a new problem.

Week 4 — Digital media, security and everyday transfer

Use words 141–200. Build a concise presentation explaining the prototype and its user. Check accessibility and suitable source attribution. Discuss a fictional phishing scenario and a questionable AI-generated answer. Finish by having the learner define ten mixed terms and apply each to a fresh situation without copying definitions.

Questions parents can ask about Computing

Ask what problem the student is trying to solve, who will use the solution, which inputs are necessary and how they know the result is correct. Avoid doing the programming on the student’s behalf. A useful response from a parent may be “What happens if the input is zero?” or “How could you test that?” These questions help the learner think independently.

Students do not need the most expensive laptop for basic algorithms or block-based programming. Appropriate school devices and free educational resources may be sufficient for foundational activities. Parents should confirm the actual software and equipment required for any specialised course before spending money.

Frequently asked questions

Is Computing a compulsory Secondary 2 MOE examination?

No. This article is a foundation and future-pathway guide. Lower-secondary digital learning varies by school, while Computing may be offered as a specialised upper-secondary subject.

Are these 200 official Computing vocabulary words?

No. They are an independent learning selection, not a prescribed examination glossary.

What is new about the 2027 SEC Computing syllabuses?

G1 Computing K127 and G2 Computing K237 are listed in the 2027 SEAB syllabuses. Candidates should check current subject-level requirements and school availability.

Does a student need prior coding experience?

Not always. Foundational algorithmic thinking, willingness to test mistakes and the ability to learn new tools are useful starting points. Entry conditions vary.

Why teach spreadsheets before advanced coding?

Spreadsheets make data, variables, formulas and verification visible in common practical situations.

Can Scratch teach real computing ideas?

Yes. Events, selection, iteration, variables and testing are important computational concepts even when represented by visual blocks.

Should students trust AI-generated source links?

Not without checking. Follow the link and verify that the source exists and actually supports the claim.

How do I know whether a project is finished?

Check the original user need, test realistic and unusual cases, correct material errors and document remaining limitations clearly.

Official guidance and further reading

For later national examinations, see the 2027 SEC G1 syllabus list (Computing K127), 2027 SEC G2 syllabus list (Computing K237), and 2027 SEC G3 syllabus list. These are upper-secondary examination guides rather than a Secondary 2 word list. For broad digital competencies see MOE’s EdTech Masterplan 2030 and MOE 2026 announcements on AI literacy and Code for Fun.

Continue through eduKateSG vocabulary resources, Secondary 2 Mathematics vocabulary, Secondary 2 Design & Technology vocabulary and Secondary 2 CCE and cyber wellness vocabulary. The connected skills are calculation, designing, verifying and responsible communication.