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Our Curriculum

Comprehensive exam-aligned curriculum for O-Level Computing (7155) and H2 Computing (9569)

We specialize in G3 (O-Level 7155) and A-Level H2 (9569). See below for G1, G2, G3 context.

G1, G2, and G3 Computing (Upper Secondary, from 2026)

From 2026, MOE offers Computing at three levels in upper secondary: G1 (Normal Technical), G2 (Normal Academic), and G3 (Express, same as O-Level). We focus on exam preparation for G3 (O-Level Syllabus 7155) and A-Level H2 (Syllabus 9569).

  • G1 Computing — Normal (Technical); computing fundamentals, networking, document processing, spreadsheets, media software, programming. We do not offer G1 tuition.
  • G2 Computing — Normal (Academic); deeper computational thinking, media software, physical computing. We do not offer G2 tuition.
  • G3 Computing — Same as O-Level Computing (Syllabus 7155). We offer G3/O-Level tuition.

O-Level Computing / G3 (Syllabus 7155)

Exam Format

Paper 1: Written Exam

  • • Duration: 2 hours
  • • Weightage: 60%
  • • Format: Multiple choice, short-answer, matching, cloze passages, structured questions
  • • Focus: Theory, algorithms, logic, data representation, networking, and impact of computing
  • • Coverage: All 5 modules (Computing Fundamentals, Algorithms & Programming, Spreadsheets, Networking, Impact of Computing)

Paper 2: Lab-Based Exam

  • • Duration: 2.5 hours
  • • Weightage: 40%
  • • Format: Computer-based practical exam
  • • Tools: Spreadsheets, Python, JupyterLab
  • • Focus: One spreadsheet question + 4-5 programming questions
  • • Coverage: Module 2 (Algorithms & Programming) and Module 3 (Spreadsheets)

Topics Covered

1. Computing Fundamentals

Computer architecture, data representation (binary, hexadecimal), logic gates, Boolean algebra

2. Algorithms & Programming

Problem analysis, algorithm design, flowcharts, pseudocode, Python programming, testing & debugging

3. Spreadsheets

Cell references, functions (logical, mathematical, statistical, text, lookup, date), conditional formatting, Goal Seek

4. Networking

Network concepts, LANs/WANs, protocols, home networks, internet, security & privacy, threats & protection

5. Impact of Computing

Industry impacts, intellectual property, copyright, communication, emerging technologies (AI, ML)

H2 Computing (Syllabus 9569)

What makes H2 Computing unique: Unlike many computing courses, H2 Computing requires mastery of two distinct skill sets. Paper 1 tests your ability to write algorithms and explain concepts on paper without a computer—a skill that requires deep understanding, not just coding ability. Paper 2 tests your practical programming skills in a computer laboratory, building full-stack web applications.

Our approach: We do both well. Our paper-first teaching method builds deep conceptual understanding through pen-and-paper practice (essential for Paper 1), then reinforces learning through hands-on Python programming and web development labs (essential for Paper 2). This dual approach ensures students excel in both the written exam and the practical lab-based exam.

Exam Format

Paper 1: Written Exam (Pen-and-Paper)

  • • Duration: 3 hours
  • • Weightage: 60%
  • • Format: 6-8 structured questions of different lengths
  • • No computers allowed - students write algorithms, pseudocode, and explanations by hand
  • • Focus: Advanced theory, algorithm design and tracing, data structure operations, Big-O complexity analysis, database normalization, network concepts
  • • Coverage: All 4 sections (Algorithms & Data Structures, Programming, Data & Information, Computer Networks)
  • • Skills tested: Algorithm writing, pseudocode fluency, theoretical understanding, written justifications

Paper 2: Lab-Based Exam (Computer Laboratory)

  • • Duration: 3 hours
  • • Weightage: 40%
  • • Format: Computer laboratory exam (4 structured questions)
  • • Tools: Python, HTML, CSS, SQLite, Flask
  • • Focus: Full-stack web application development, database operations, algorithm implementation, problem-solving through code
  • • Coverage: All 4 sections tested through practical programming tasks
  • • Skills tested: Python programming, web development (HTML/CSS), database design and queries (SQLite), Flask web framework, integration of technologies
  • • Submission: Soft copies of code and files submitted for marking

Topics Covered

1. Algorithms & Data Structures

Pseudocode, flowcharts, decision tables, modular design

Sorting: Insertion sort, bubble sort, quicksort, merge sort with complexity analysis

Searching: Linear search, binary search, hash table search

Data Structures: Stacks, queues (linear & circular), linked lists, binary search trees, Big-O notation

2. Programming

Coding standards, data types, control structures, functions/procedures

Recursion: Concept, tracing, call stack understanding

Implementation: Converting algorithms to Python code, implementing data structures

OOP: Classes, objects, encapsulation, inheritance, polymorphism, class diagrams

3. Data & Information

Data representation (binary, hexadecimal, two's complement)

Character encoding (ASCII, Unicode)

Databases: Relational databases, SQL queries, normalization (3NF), ER diagrams, SQLite operations

Social, ethical, and legal issues in computing

4. Computer Networks

Network fundamentals (LAN, WAN, IP addressing, DNS, protocols, packet-switching)

Web Applications (Paper 2 Critical): HTML structure, CSS styling, Flask framework, routing, templates, form handling, SQLite database integration

Network security (malware, firewalls, encryption, authentication, IDS/IPS)

Our Dual-Skills Approach: Paper-First Learning + Practical Lab Work

Paper-First Learning (Paper 1 Preparation): Students learn to write algorithms and trace code by hand first (matching Paper 1 format). This builds deep conceptual understanding and the ability to work without computer assistance—essential skills for the 60% written exam.

Practical Lab Work (Paper 2 Preparation): Students then verify and reinforce their understanding through hands-on Python programming, web development (HTML/CSS/Flask), and database work (SQLite). Regular lab sessions ensure students can build full-stack applications efficiently—essential skills for the 40% lab-based exam.

We do both well: comprehensive paper practice for Paper 1 mastery, and extensive lab work for Paper 2 proficiency.

Note for Integrated Programme (IP) Students

IP students skip the O-Level examination and proceed directly to JC, where they take A-Level exams. If you're an IP student in Secondary 3-4, you'll be preparing for H2 Computing (Syllabus 9569) at the JC level, not O-Level Computing. Our H2 Computing program is suitable for IP students preparing for their A-Level Computing exams.

Our Learning Approach

Exam-Aligned: All content follows official SEAB syllabuses (7155 and 9569)

Written & Practical: Comprehensive preparation for both Paper 1 (written, 60%) and Paper 2 (lab-based, 40%) components

Paper 1 Focus: Pen-and-paper practice for written exams covering theory, algorithms, and problem-solving

Paper 2 Focus: Lab-based practice with Python, spreadsheets (O-Level), and web development tools (H2) matching exam environment

Small Groups: 6-8 students per class for personalized attention

Progressive Learning: Structured 12-week curriculum building from fundamentals to advanced topics

Regular Assessments: Mock exams for both written and lab-based components to track progress

Exam Techniques: Time management, answer structuring, and exam strategy for both papers

AI-Powered Personalized Learning Platform

Adaptive Practice

Our online platform uses AI to analyze your child's performance and automatically generates personalized practice worksheets targeting their specific knowledge gaps.

  • Questions adapt to mastery level—no wasted time on topics already mastered
  • Automatic gap identification and targeted practice
  • Practice anytime, anywhere—24/7 access between classes

Fast AI-Powered Feedback

Get instant, detailed feedback on homework and assessments—enabled by AI for speed, validated by expert tutors for accuracy.

  • Instant feedback on written work and code submissions
  • Detailed explanations and corrections within seconds
  • All feedback validated by expert tutors—speed AND quality

Real-Time Progress Tracking

Parents and students can see exactly which topics are mastered and which need more practice—updated in real-time. Track improvement over time with detailed analytics showing progress on each syllabus topic. Transparent learning, instant insights, faster improvement.