IB DP 2 AI Maths (HL)
Ancourage Academy · IB DP · DP 2
Content reviewed: Jan 2026
IB DP 2 Mathematics AI (HL) tuition at Ancourage Academy in Singapore (Bishan & Woodlands) offers small-group classes of 3-6 students, providing final examination preparation for advanced applied mathematics pathways. Weekly 2-hour lessons use our ESB methodology to consolidate advanced statistics, complex modelling, and Paper 3 extended investigation skills. "DP success comes from connecting knowledge across disciplines—students who see patterns between subjects excel in examinations," explains our teaching faculty. Our structured approach helps students achieve examination-ready mastery with confident data science and analytical abilities.
What Makes Us Different
Our proven teaching methodology combines evidence-based approaches for maximum learning effectiveness
Ebbinghaus Memory Theory
Self-directed retrieval scheduling where students learn to identify their own weak areas and plan review cycles accordingly — developing the metacognitive skills essential for A-Level success and independent university study.
Socratic Questioning
Rigorous dialectic questioning where students must justify their reasoning and consider counterarguments — 'What evidence supports this?' and 'Where could this logic break down?' — building the analytical rigour expected in higher education.
Bruner's Scaffolding
Minimal scaffolding with maximum autonomy — tutors pose challenging problems and observe, intervening only when students are genuinely stuck — preparing students to structure their own approach to unfamiliar problems.
Key Learning Outcomes
Master Key Concepts
Deep understanding of core topics aligned with MOE syllabus
Critical Thinking
Develop analytical and problem-solving skills
Exam Confidence
Strategic exam techniques and time management
Consistent Results
Improved grades and academic performance
Course Structure
Duration
2 hours per lesson
Full coverage with interactive learning time
Class Size
3-6 students per class
Close guidance, timely feedback, and ample practice
Materials
All materials provided
No material fees — all worksheets and resources included
Curriculum Overview
- ✓Number and Algebra — Growth and decay, exponents, logarithms, financial mathematics, sequences and series.
- ✓Functions and Modelling — Advanced modelling with linear, polynomial, exponential, logarithmic, and trigonometric functions; curve fitting.
- ✓Geometry and Trigonometry — Applying trigonometry to 2D and 3D contexts, real-world measurement and modelling.
- ✓Statistics — In-depth study of descriptive and inferential statistics, probability distributions, chi-square tests, correlation and regression, hypothesis testing.
- ✓Probability — Advanced probability laws, distributions (binomial, normal, Poisson), expected value and risk.
- ✓Calculus — Differentiation and integration focused on applied contexts such as optimisation, rates of change, and modelling.
- ✓Technology use — Extensive use of graphing calculators and software to model, simulate, and solve problems.
- ✓Extended HL-only topics — Chi-square tests, Poisson distribution, advanced regression analysis, extended statistics.
- ✓Internal Assessment (IA) — Independent Mathematical Exploration linking advanced modelling or data analysis to a chosen real-world issue.
What IB DP 2 AI Maths HL students commonly work on
- 1
Advanced statistics — mastering hypothesis testing, chi-square, and Poisson distribution
- 2
Paper 3 preparation — tackling extended modelling problems requiring sustained analysis
- 3
Complex data interpretation — evaluating real-world scenarios with multiple variables
- 4
IA refinement — finalising the Mathematical Exploration with HL-level statistical depth
- 5
Model evaluation — critically assessing assumptions, limitations, and validity of mathematical models
Learning Progression
Builds On
DP 1 AI Maths HL with advanced statistics, modelling, and data analysis
Prepares For
IB Diploma examinations and university courses in data science, psychology, or applied fields
Key Transition
DP 2 demands statistical fluency — HL students must handle complex data analysis under exam conditions while evaluating model validity.
Related Courses
Explore other courses that complement your learning journey
Frequently Asked Questions
Paper 3 is an HL-only extended modelling paper where students work through a complex real-world problem step by step. It tests ability to apply mathematics to unfamiliar situations, evaluate assumptions, and communicate mathematical reasoning clearly.
AI HL provides excellent preparation for data science with its emphasis on statistics, hypothesis testing, and modelling. Universities recognise AI HL as strong preparation for programmes involving data analysis, business analytics, and quantitative social sciences.
HL includes additional statistical techniques (chi-square, Poisson), more complex modelling scenarios, and the Paper 3 exam. The IA requires greater depth in analysis. Students need stronger technology skills and ability to evaluate model limitations.
Our small-group classes are intentionally kept between 3 and 6 students so every learner receives close guidance, timely feedback, and ample practice.
Each lesson is 2 hours, providing ample time for thorough coverage of topics and interactive learning.
Yes. All lesson materials and worksheets are provided and included in the fees. Students should bring regular stationery and, where applicable, school textbooks/workbooks for reference.
Yes. Our materials and pacing align with the MOE syllabus. External syllabuses (e.g. IGCSE, IB) are available upon request.
Ready to Get Started?
Enquire now and experience our proven teaching methodology
💬 Have questions? WhatsApp us anytime — we typically respond within 2 hours