CTAI, Class 6

Stage: Middle | Hours/Year: 100 Components: Advanced CT Skills (40 hrs) + Introductory AI Concepts (20 hrs) + Interdisciplinary Projects (40 hrs) Delivery: CT worksheets + AI Foundation Handbook + Project-based learning modules Taught by: Subject teachers (for CT) and Computer teachers (for AI Literacy); projects assessed by Computer teacher

Curricular Goals

Goal	Description
CG-1	Develops CT skills: decomposition, pattern recognition, data representation, generalisation, abstraction, and algorithms to solve problems where such techniques of CT are effective.
CG-2	Develops spatial and visual reasoning.
CG-3	Gain foundational knowledge of AI, its types, and domains.
CG-4	Understand key ethical terms such as bias and fairness in relation to AI.
CG-5	Demonstrates proficiency in using a computer and other devices, computer applications for learning and practical purposes, such as data analysis, preparation of visual representations and communication of ideas.

Competencies

Code	Competency
C-1	Approaches problems using programmatic thinking techniques such as iteration, symbolic representation and logical operations, and reformulates problems into a series of ordered steps.
C-2	Learns systematic arithmetic reasoning, iterative patterns, and multiple data representations, to devise and follow algorithms, with an eye towards understanding correctness, effectiveness, and efficiency of algorithms.
C-3	Learns to visualise, manipulate, represent, and understand spatial relationships between objects.
C-4	Applies abstraction and generalisation to identify core structures and patterns enabling reusable procedures.
C-5	Demonstrate knowledge of AI tools through different projects and activities.
C-6	Identifies ethical issues and applies ethical principles to make informed decisions regarding AI usage.
C-7	Uses computers or any other appropriate devices and software/applications for creating visual representations of ideas, organising and analysing data, conducting simple online research, gathering images, and designing infographics.

Note: CG and Competency codes are shared across the Middle Stage (Classes 6-8). The learning outcomes below differentiate the Class 6 level.

Learning Outcomes, CT

Abstract Thinking

Students will be able to interpret and solve multi-step problems with layered and abstract clues, using:

Advanced viewpoints and cross-sections of 3-D objects, Combined transformations of shapes (multiple flips, rotations, reflections, cuts/folds), Changes in orientation, position, order, and direction (clockwise, counter-clockwise, diagonal), Identifying hidden, overlapping, or implied parts in complex visual patterns, Symmetry across multiple axes and composite mirror/water image reasoning, Visual reasoning involving scale, proportion, and spatial relationships

Content creator note: A significant jump from Class 5. Key new elements: cross-sections of 3D objects, combined (compound) transformations, diagonal directions, overlapping parts, multi-axis symmetry, and reasoning about scale and proportion. Problems move from concrete visual puzzles to abstract spatial reasoning.

Pattern Recognition

Students will be able to identify, extend, and justify complex patterns involving multiple simultaneous changes, formed using:

Numbers with mixed operations and logical rules, Shapes/images with changing attributes (size, position, count, orientation), Letters and symbols with positional or alphabetical logic, Patterns involving alternation, skipping, grouping, or cyclic behaviour, Mixed patterns combining numbers, shapes, and letters with dependency rules

Content creator note: Class 6 introduces two major advances: (1) students must now JUSTIFY patterns (not just identify them), and (2) specific pattern types are named, alternation, skipping, grouping, cyclic behaviour, and dependency rules. Mixed operations in number patterns and multiple attribute changes in shape patterns increase complexity.

Decomposition

Students will be able to break down higher-order problems involving interdependent clues and constraints, using information from:

Numerical clues involving place value, operations, factors, multiples, and comparisons, Properties of 2-D and 3-D shapes (faces, edges, vertices, diagonals, angles), Multi-step transfers or exchanges (money, quantities, digits, objects) with conditions, Tables, grids, or charts requiring cross-referencing of multiple data points, Conditional rules for counting, grouping, sorting, or eliminating possibilities, Visual representations that encode numerical or logical values

Content creator note: Key advances over Class 5: (1) clues are now "interdependent" with explicit "constraints," (2) number properties expand to include factors, multiples, and comparisons, (3) 2D shape properties (diagonals, angles) are added to 3D, (4) cross-referencing of data points is explicit, and (5) elimination strategies are introduced.

Algorithmic Thinking

Students will be able to follow, analyse, and apply multi-layered rules and procedures to solve complex problems involving:

Number sequences formed using combined operations and logical conditions, Movement on grids involving direction, distance, turns, and path constraints, Step-wise changes where values increase/decrease based on rules, Multi-step instructions involving swaps, shifts, transfers, and rearrangements, Ordering people, objects, or events using multiple attributes or clues
Logical flow of steps, identifying necessary vs redundant information (NEW)

Content creator note: Class 6 adds three capabilities: (1) ANALYSING rules (not just following), (2) "combined operations and logical conditions" in sequences, and (3) identifying necessary vs redundant information in algorithmic procedures. Grid movements now include distance and path constraints. "Shifts" and "rearrangements" are added as operations.

Learning Outcomes, AI

Learners will be able to:

Summarise basic ideas and concepts of AI and its applications
Describe key differences between machine intelligence and human intelligence
Explain the difference between automation and AI using practical, real-world cases
Differentiate the three fundamental AI methodologies: supervised, unsupervised, and reinforcement learning
Develop the skill of organising and representing data in various forms (text, numbers, images, sounds)
Recognise simple patterns in data and make decisions based on observations
Demonstrate understanding of ethics and digital responsibility in the use of AI, including digital footprints, privacy, and responsible technology behaviour
Practice essential internet safety protocols (secure passwords, safe online behaviour, basic privacy measures) while using digital and AI tools
Apply conceptual knowledge of AI to everyday activities by recognising human-centred design and ethical principles in how AI works and interacts with people

AI Syllabus (20 hours)

#	Topic	Hours	Key Content
1	Introduction to AI and Everyday Examples	5	What AI is; difference between AI and automation; human vs machine intelligence; AI concepts and types (supervised, unsupervised, reinforcement learning)
2	Basic Data Concepts	5	Data types (numbers, text, images, sound); simple data organisation and representation using tables or charts
3	Simple Pattern Recognition and Decision Making	5	Identifying patterns in data or daily routines; making simple decisions based on observations
4	Ethics and Digital Responsibility	5	Basic online safety, privacy, passwords, ethical use of technology; understanding digital footprints

Pedagogy Suggestions

For CT, Complex puzzles, riddles, and games building on earlier CT abilities, Independent activities: data collection, organisation, analysis, varied representations, flow charts, CT resource book aligned chapter-by-chapter with Class 6 Mathematics textbook

For AI, Fundamental AI concepts through explanations, demonstrations, and hands-on experiences, Group discussions and collaborative projects integrating CT and AI, Discussions, debates, and case studies on ethical use of AI, Experiential, inquiry-based learning opportunities

For Interdisciplinary Projects (40 hours), Cross-subject projects applying CT and AI to problems from Maths, Science, Social Studies, English, Projects designed to be engaging and hands-on rather than academically demanding, Focus on curiosity, collaboration, and innovation

Assessment Methods

Written tests, Interactive group activities, Practical examinations, Teacher Observation Journal, Thematic projects, Reflections and group discussions, Project presentations, assignments, reflective journals

Key Content Areas for Teaching

CT Content

Cross-sections and advanced 3D: Visualising cross-sections of 3D objects, compound transformations
Multi-axis symmetry: Symmetry across multiple axes, composite mirror/water images
Scale and proportion: Visual reasoning about scale, proportion, and spatial relationships
Pattern justification: Not just finding patterns but explaining WHY they work
Cyclic and dependency patterns: Alternation, skipping, grouping, cyclic behaviour
Cross-referencing data: Decomposition problems requiring data from multiple sources
Necessary vs redundant information: Algorithmic thinking that involves filtering information
Factors, multiples, comparisons: Mathematical properties as decomposition tools

AI Content

AI fundamentals: What AI is, how it differs from automation, human vs machine intelligence
Three AI types: Supervised learning, unsupervised learning, reinforcement learning (conceptual, not technical)
Data literacy basics: Types of data, organising data, representing data
Pattern recognition in data: Simple pattern identification and observation-based decisions
Digital safety and ethics: Passwords, privacy, digital footprints, responsible technology use
Human-centred AI design: Recognising ethical principles in AI interactions

Transition Notes

Class 6 is the entry point for the Middle Stage. Key shifts from Preparatory Stage:

CT is no longer just embedded in Maths/TWAU, it has its own dedicated time allocation, AI is introduced as a completely new component, Interdisciplinary projects become a formal requirement, Computer teachers are now involved in teaching, Assessment methods expand significantly (practical exams, thematic projects, reflective journals), Students are expected to ANALYSE and JUSTIFY, not just identify and follow