Top 200 Vocabulary for Secondary 3 Computing (MOE G3 Syllabus) | Python, Algorithms, Spreadsheets and Networking

Searching for Secondary 3 Computing vocabulary in Singapore? This guide explains 200 Computing terms for Python, algorithms, Boolean logic, spreadsheets, networking, digital ethics and computer systems. Each set has twenty definitions and a practical exercise so students learn how to reason through unfamiliar tasks rather than merely recognise technical words.

The 2027 Singapore-Cambridge SEC G3 syllabus index identifies Computing as K349, formerly 7155. The official K349 syllabus covers Computing Fundamentals, Algorithms and Programming, Spreadsheets, Networking and Impact of Computing. In the 2027 examination scheme, Paper 1 is written and worth 60%; Paper 2 uses a computer for spreadsheet and Python tasks and is worth 40%. These 200 terms are independently curated, not a compulsory MOE-issued vocabulary list, and the full upper-secondary syllabus may be sequenced differently by schools.

• Learn: one group of 20 terms at a time.
• Explain: what the input, output and computational process mean.
• Practise: short Python, logic and spreadsheet problems.
• Test: ordinary, boundary and invalid cases.
• Apply: accurate technical language to everyday networks and digital privacy.
• Verify: exam details against the current official syllabus and school instructions.

Top 200 Secondary 3 Computing terms and definitions

Computer systems

Computer architecture becomes useful when you explain why an unsaved document may vanish during a power interruption while a properly saved file remains on persistent storage. Main memory supports active work; secondary storage retains documents and applications. A device’s performance can also depend on the processor and how components communicate.

1. hardware — physical parts of a computing system.
2. software — instructions executed by computer hardware.
3. processor — a device executing program instructions.
4. central processing unit — a processor coordinating general computation.
5. main memory — temporary working storage for data and instructions.
6. random access memory — working memory normally losing data when unpowered.
7. read-only memory — memory typically storing persistent instructions.
8. secondary storage — non-volatile storage for files.
9. solid-state drive — storage using flash-memory chips.
10. hard disk drive — storage using magnetic disks.
11. optical media — storage read using reflected light.
12. input device — equipment supplying data to a computer.
13. output device — equipment displaying or producing results.
14. peripheral — a supporting connected device.
15. interface — the specification for device connections.
16. data bus — electrical paths transporting data.
17. address bus — paths transporting memory addresses.
18. control unit — processor component coordinating instructions.
19. arithmetic logic unit — processor circuits doing arithmetic and logic.
20. computer architecture — the arrangement and operation of computer components.

Mini-task: Explain the different roles of working memory and saved storage in an unfinished school report.

Number systems

Data representation is not the same as the human meaning of data. Thirteen in decimal and 1101 in binary are the same numerical quantity written in different bases. One kilobyte means 1000 bytes while one kibibyte means 1024 bytes. The representation width and coding system matter when interpreting binary data.

21. bit — a binary digit representing zero or one.
22. byte — eight bits grouped together.
23. kilobyte — one thousand bytes.
24. kibibyte — 1024 bytes.
25. megabyte — one million bytes.
26. mebibyte — 1048576 bytes.
27. binary — base-two representation using zero and one.
28. denary — base-ten number representation.
29. hexadecimal — base-sixteen representation.
30. place value — value assigned by a digit position.
31. positional notation — numerals whose positions affect magnitude.
32. most significant bit — bit with greatest positional weight.
33. least significant bit — bit with smallest positional weight.
34. unsigned integer — whole-number representation without negatives.
35. signed integer — whole-number representation allowing negatives.
36. two’s complement — a fixed-width method representing signed integers.
37. overflow — a result too large for its allowed representation.
38. character encoding — a mapping from characters to numerical codes.
39. ASCII — a traditional character encoding standard.
40. fixed-width representation — a numeric encoding using a stated number of bits.

Mini-task: Write the decimal value of binary 1101 and compare kB with KiB.

Boolean logic

Boolean words describe exact rules, not impressions. For two inputs XOR is true when exactly one is true, whereas OR is true when one or both are true. A truth table checks all input combinations and helps confirm whether two different-looking expressions are equivalent.

41. Boolean value — one of the values true and false.
42. truth table — a complete listing of outcomes for possible inputs.
43. AND gate — a gate true when both of two inputs are true.
44. OR gate — a gate true if either or both inputs are true.
45. NOT gate — a gate negating its input.
46. NAND gate — a gate negating an AND output.
47. NOR gate — a gate negating an OR output.
48. XOR gate — a gate true when exactly one of two inputs is true.
49. logic circuit — connected gates performing logical operations.
50. Boolean expression — an expression evaluating to true or false.
51. conjunction — a logical AND relationship.
52. disjunction — a logical OR relationship.
53. negation — a logical NOT relationship.
54. De Morgan’s theorem — rules relating negations of AND and OR.
55. logic equivalence — expressions with identical outputs for every input.
56. operator precedence — the order in which operations are evaluated.
57. brackets — notation grouping expressions together.
58. conditional test — a Boolean expression deciding which action runs.
59. decision rule — a condition linked to a required outcome.
60. input combination — one assignment of truth values to all inputs.

Mini-task: Evaluate A AND NOT B for all four two-input Boolean combinations.

Computational thinking

Before writing code, identify valid inputs, required outputs and any constraints. Decompose a task into smaller steps. Decide which stages are sequence, selection or iteration. A loop needs a meaningful route to termination; otherwise, repeated instructions may never finish.

61. algorithm — a finite set of clear steps for a task.
62. decomposition — splitting a problem into smaller parts.
63. abstraction — ignoring irrelevant detail to model essentials.
64. pattern recognition — identifying useful similarities between problems.
65. flowchart — a diagram showing steps and branches.
66. pseudocode — structured words describing algorithm actions.
67. input — information supplied to a process.
68. output — the result produced by a process.
69. requirement — a condition the finished solution must meet.
70. sequence — steps performed in a specified order.
71. selection — choosing actions according to a test.
72. iteration — repeating instructions when required.
73. loop — a block of repeatable instructions.
74. termination — the end condition of a process.
75. flow control — rules determining the next executed instruction.
76. modular design — organising a solution as small cooperating parts.
77. incremental approach — building and testing in small stages.
78. linear search — checking items successively for a match.
79. trace table — a record of values at program steps.
80. dry run — manual execution of an algorithm to inspect behaviour.

Mini-task: State the inputs, outputs and loop stopping condition of a small attendance-checking task.

Python basics

Python has strict syntax and uses indentation to determine blocks. The text ‘5’ is not the same type as the number 5. A correct algorithm can still fail if the programmer assumes types or code indentation incorrectly, so students should explain what every important line does.

81. Python — the programming language used in K349.
82. source code — human-readable instructions written by a programmer.
83. syntax — formal rules defining valid program text.
84. statement — an instruction recognised by the language.
85. expression — code producing a value.
86. literal — a value written directly in the program.
87. identifier — a name assigned to a programming object.
88. variable — a name referring to a value.
89. assignment — binding a value to a variable name.
90. integer — a whole-number value.
91. floating-point number — a finite-precision representation of a real number.
92. string — a sequence of text characters.
93. Boolean type — the type holding true and false values.
94. if statement — a branch running when a condition is true.
95. elif statement — an additional branch checked after earlier failures.
96. else statement — a fallback branch without a new condition.
97. for loop — a loop iterating through an iterable.
98. while loop — a loop controlled by a Boolean condition.
99. indentation — leading whitespace marking Python code blocks.
100. function call — invocation of a named operation.

Mini-task: Explain why 2 + 3 equals 5 while the string expression ‘2’ + ‘3’ produces ’23’.

Collections and functions

A list is suitable when order and position matter. A dictionary maps keys to values. A parameter is the name receiving information in a function, whereas an argument is the data supplied during the call. A function’s return value can be used in another calculation, unlike text printed only for display.

101. list — an ordered mutable collection.
102. list position — an index identifying an item in a sequence.
103. slicing — extracting a subsequence using positions.
104. dictionary — a collection mapping keys to values.
105. dictionary key — a name used to find an associated mapping value.
106. mapping value — data associated with a dictionary key.
107. membership test — checking if an element occurs in a collection.
108. concatenation — joining sequences together.
109. type conversion — changing a value to a different type.
110. string formatting — arranging values into readable text.
111. built-in function — a function provided by the language.
112. user-defined function — a function created by a programmer.
113. parameter — a receiving name in a function definition.
114. argument — a value supplied when calling a function.
115. return value — data passed back by a function.
116. local variable — a variable in a function’s local scope.
117. global variable — a name defined at module level.
118. file input — reading data from stored files.
119. file output — writing data into a file.
120. delimiter — a character separating fields or data items.

Mini-task: Give an example of a list, a dictionary, a parameter and a returned result.

Program testing

Testing should be planned, not improvised after a failure. A normal input may succeed while a boundary input reveals a wrong comparison operator. An invalid value may expose missing validation. Students should record the input, expected result, actual result and smallest relevant change that fixed the defect.

121. syntax error — invalid code violating language grammar.
122. runtime error — a failure occurring during execution.
123. logic error — incorrect behaviour from otherwise valid instructions.
124. debugging — locating and repairing program defects.
125. test case — a specified input and expected result.
126. normal test — a check using typical valid inputs.
127. boundary test — a check at or near an input limit.
128. invalid test — a check using data outside the rules.
129. validation — checking that input meets its specifications.
130. verification — checking whether a solution meets its requirements.
131. range check — a test of numeric bounds.
132. presence check — a test for missing required data.
133. format check — a test for an expected pattern.
134. length check — a test of character or item counts.
135. existence check — checking whether an item already occurs.
136. check digit — a calculated symbol used to detect some entry errors.
137. backtracking — tracing steps backward from a faulty result.
138. regression testing — rechecking old functionality after changes.
139. error message — information reporting a detected problem.
140. incremental testing — testing small changes while developing a program.

Mini-task: Design boundary tests for an inclusive score range from zero to one hundred.

Spreadsheets

Spreadsheets require attention to what changes when a formula is copied. Relative references move with the formula while absolute references remain anchored. A single misplaced cell reference can silently affect a large table, even though the first output looks plausible.

141. spreadsheet — a grid-based tool for calculations and data.
142. workbook — a file containing worksheets.
143. worksheet — a tabular page of cells.
144. cell — one grid location.
145. row — a horizontal line of cells.
146. column — a vertical line of cells.
147. cell reference — an address used in a formula.
148. relative reference — a reference that changes when copied.
149. absolute reference — a reference that stays fixed when copied.
150. mixed reference — a reference fixing only its row or column.
151. formula — an expression computing a result in a cell.
152. spreadsheet function — a built-in formula operation.
153. conditional formatting — automatic styling triggered by rules.
154. Goal Seek — finding an input needed for a target output.
155. lookup — finding related data in a table.
156. VLOOKUP — a function looking up values down a table column.
157. INDEX — a function returning data from a specified position.
158. MATCH — a function returning a matched item’s relative position.
159. SUMIF — adding cells that meet a given condition.
160. COUNTIF — counting cells matching a given condition.

Mini-task: Explain why a discount-rate reference should remain fixed when a spreadsheet formula is copied.

Networking

Bandwidth measures potential data capacity and latency measures delay. An application may be slow because of high response delay even when large transfers are reasonably fast. Distinguish protocols, devices and addresses rather than using ‘Wi-Fi’ as a universal explanation for every problem.

161. computer network — connected systems exchanging data.
162. local area network — a network spanning a limited region.
163. wide area network — a network spanning extensive distances.
164. Internet — interconnected networks exchanging information globally.
165. client — a system requesting network services.
166. server — a system providing services to other systems.
167. protocol — agreed rules for exchanging information.
168. Internet Protocol — rules for addressing and routing network packets.
169. IP address — an address identifying an interface for network routing.
170. packet — a unit of data transferred across a network.
171. router — a device forwarding packets across networks.
172. switch — a device moving traffic within a network.
173. wireless networking — communications using radio signals.
174. bandwidth — a link’s potential data-carrying capacity.
175. latency — the delay involved in a communication.
176. domain name — a readable name for an Internet resource.
177. Domain Name System — a service resolving domains into DNS records.
178. HTTPS — encrypted and authenticated web communication.
179. firewall — a system filtering network traffic according to rules.
180. network security — protection of networks against threats.

Mini-task: Explain why a high-bandwidth connection can still have noticeable latency.

Digital society

Computing skills affect people. Students should not use real classmates’ personal information for sample projects without authority and appropriate safeguards. An automated answer is not automatically unbiased or correct. Ethical analysis considers permissions, evidence, harms and options for review.

181. personal data — information identifying or relating to a person.
182. privacy — control and protections over personal information.
183. consent — permission given with relevant understanding.
184. data protection — practices safeguarding information.
185. confidentiality — limiting data access to authorised parties.
186. authentication — checking an asserted identity.
187. authorisation — granting access to permitted actions.
188. encryption — encoding data to resist unauthorised reading.
189. phishing — fraudulent messages seeking credentials or information.
190. malware — harmful or exploitative software.
191. ransomware — malware attempting to extort by restricting access.
192. cyberbullying — harassment carried out online.
193. digital footprint — records left by online activity.
194. algorithmic bias — systematic unfairness in automated decisions.
195. artificial intelligence — computing approaches performing complex inference tasks.
196. machine learning — building models that learn patterns from data.
197. digital divide — unequal access to digital resources or skills.
198. intellectual property — legal protection for certain original creations.
199. responsible disclosure — reporting a security weakness through authorised channels.
200. computing ethics — judgement about technology’s impact on people and society.

Mini-task: Give one data-minimisation decision for a hypothetical student-club app.

Five worked examples: the difference between knowing words and using them

Example 1: Binary representation

The binary numeral 1101 has the place values 8, 4, 2 and 1. It represents 8+4+0+1 = 13 in denary. In hexadecimal, that same value is written D. Converting between representations does not change the quantity. By contrast, converting a storage amount involves the definition of the unit: 1 KiB represents 1024 bytes, not 1000 bytes.

Students can test their understanding by converting 1010 to decimal and then comparing how many bits are needed to encode it under a fixed-width representation. Explain why leading zeros may be present and why a signed representation is not automatically interpreted in the same way as an unsigned one.

Example 2: Logic and an access rule

Suppose A means a supervised workshop session is scheduled and B means a maintenance lock is active. The hypothetical rule A AND NOT B permits the session only when A is true and B is false. When both A and B are true, the rule gives false because the maintenance lock takes precedence. When both inputs are false, it also gives false because there is no scheduled session.

This is an educational truth-table problem, not a real access-control policy. A real system would require identity checks and more rules. The important lesson is that the Boolean expression is testable for every input combination; a sensible-sounding sentence is not enough.

Example 3: Boundary conditions in Python

An original teaching program should report whether a numeric score is within the allowed inclusive range of 0 to 100. One possible short function is:

def valid_score(score):
    return 0 <= score <= 100

The two inclusive comparison operators matter. Using 0 < score < 100 would incorrectly exclude 0 and 100. Test −1, 0, 1, 99, 100 and 101. Also note that an actual data-entry application would need to check and handle non-numeric inputs before attempting numeric comparisons. A normal-case pass does not prove validation is complete.

Example 4: A function versus printing a result

A program might store daily reading durations as a list, [12, 8, 15]. The total is 35 minutes. A function that returns the total allows the caller to store or compare it, whereas a function that only prints 35 displays text and may not provide a reusable numerical result. The difference matters if the next step computes a weekly average.

Similarly, a dictionary such as {"Mon": 12, "Tue": 8, "Wed": 15} lets a program associate day names with their durations. A list and a dictionary are not superior or inferior in every problem. They solve different access and organisation needs.

Example 5: Copying a spreadsheet formula

Imagine B2 contains a price and F1 contains a 10% discount rate. In C2, =B2*(1-$F$1) calculates the price after the discount. When copied to C3, B2 becomes B3 but $F$1 remains F1. This deliberate distinction between relative and absolute references allows the same discount rate to apply to many rows.

Without the absolute signs, the copied formula could look for a rate in F2 and then F3, where the cell may be blank or contain another value. A calculation that succeeds on the first row can fail silently later. Checking several rows and understanding formula references is therefore more important than copying a spreadsheet screenshot.

Common errors and exact repairs

Confusing bits and bytes: Name the measurement unit and convert from the correct base. Mixing OR and XOR: Compare their truth tables for both true inputs. Wrong Python type: Distinguish text from numeric values before adding or comparing. Missing indentation: Inspect which instructions belong to a branch or loop. Loop never stops: Trace which value will make its condition false.

Missing boundary tests: Check allowed endpoints as well as usual data. Wrong spreadsheet reference: Decide which part of a cell reference should move when copied. Overgeneralising network speed: State whether the problem concerns delay, capacity or another bottleneck. Ignoring privacy: Use synthetic data, minimal permissions and authorised access.

How to prepare for the 2027 Computing practical

The official G3 K349 Paper 2 is a 2-hour-30-minute laboratory examination contributing 40%. It includes spreadsheet and programming tasks using a computer with the appropriate software. Students should practise reading the task, producing a working file, testing their logic, correcting errors and saving the requested results. It is not enough to memorise the name of a programming function without being able to apply it.

For programming, begin with a tiny correct solution, test it, then extend. For spreadsheets, check copied formulas across the table. For both, keep a short log of the first incorrect assumption and its correction. A student who can explain a change and use the corrected concept on a new task is making genuine progress.

Four-week learning and revision plan

Week 1: architecture and logic

Learn groups 1–3, eight to ten terms per session. Compare working memory with saved storage, then practise binary conversions and truth tables. Complete at least one unseen example without referring to the definition. Revisit the terms you confused after two days.

Week 2: algorithms and Python

Learn groups 4–6. For a short problem, list inputs, valid values, expected outputs and algorithm steps before coding. Use functions, loops and selections that match those requirements. Explain the difference between a parameter and an argument, and between printing and returning a result.

Week 3: testing and spreadsheets

Learn groups 7–8. Build a table of normal, boundary and invalid cases. Find an intentional bug using a trace table. Copy a spreadsheet formula across several rows, observing which references move. Explain one failure as a relationship problem rather than describing the computer as ‘wrong’.

Week 4: networking, ethics and transfer

Learn groups 9–10. Explain latency and bandwidth through a simple real-life scenario, then discuss a privacy or data-access decision. Complete a mixed exercise using a fresh task and summarise the first mistake and its repair. Focus on applying meaning rather than checking off all 200 words.

Frequently asked questions

Are these 200 words an official MOE Computing vocabulary list?

No. They are a curated resource covering useful concepts from the wider upper-secondary course. The actual 2027 subject syllabus determines assessment content.

Is Python part of SEC G3 Computing?

Yes. The K349 syllabus specifies Python and spreadsheet work. Follow its quick-reference guide and the school’s current software arrangements for examination-specific details.

Why do students struggle despite memorising commands?

A familiar command may not solve an unfamiliar requirement. Students need to identify inputs, outputs, types, conditions and boundaries, then test and revise an algorithm.

Do students need to know everything in Secondary 3?

No. This guide spans upper-secondary learning. Use the school sequence rather than treating the 200 terms as an immediate homework task.

Can parents help without programming experience?

Ask what the program should do, which data it accepts, when loops stop and how the student knows the answer is correct. These questions exercise computational thinking without requiring the parent to write code.

Is Computing useful outside school?

Yes. It helps people understand how networks, devices, automated decisions and data protection affect daily life. It also develops structured problem-solving that can be used in other subjects.

Authoritative sources and next reading

See the SEAB 2027 K349 Computing syllabus, the 2027 SEC G3 subject index, Secondary 3 Mathematics vocabulary and Secondary 3 Design and Technology vocabulary. Final check: Can you describe what the program should do, show how it works and find the first cause when it fails?