MX000 - Mathematics and Statistics - Curriculum Levels 2–5

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What is Mathematics and Statistics?

Mathematics is more than just numbers. It is the exploration and use of patterns and relationships in quantities, space and time. Statistics focuses on patterns and relationships in data. Ākonga are equipped with powerful communication and problem solving tools for investigating, interpreting and making sense of the world. Using symbols, graphs and diagrams to investigate patterns and relationships, ākonga model real-life and hypothetical situations in a range of contexts: social, cultural, scientific, technological, health, environmental and economic. Mathematics and Statistics develops the ability to think creatively, critically, strategically and logically. Ākonga also learn to structure, organise, process and communicate information.

What this course involves

Individualised courses are designed to give ākonga a strong basis in the fundamentals of mathematics and statistics and to build confidence in the development and application of basic skills.

Each curriculum level develops the concepts of statistics, probability, geometry, measurement, number and algebra, which are applied to practical problems. In the lower curriculum levels, the focus is on core skills of numeracy, measurement, money, reading tables and graphs, using a calculator, basic arithmetic and shape patterns. After mastering these, ākonga progress towards an understanding of whole numbers, decimals, fractions, percentages and integers, and learn the skills needed to construct and interpret statistical graphs.

Other topics covered include: perimeter, area and volume, investigating mass, capacity, time and temperature, ratios, mean and range, exploring patterns, equations and locating position. Curriculum Level 5 is the foundation for NCEA Level 1.

Concepts are connected in new topics such as trigonometry. There is even greater emphasis on solving realistic problems using a variety of approaches and clearly and concisely communicating the thought processes.

Delivery Modes

Recommended prior learning

No prior learning needed.