NOTE: This is taken from the Teacher's Edition of Data Around Us ©2002

Data Around Us mathematical and problem solving goals:

Data Around Us was created to help students:

• Choose sensible units for measuring

The overall goal of the Connected Mathematics curriculum is to help students develop sound mathematical habits. Through their work in this and other data units, students learn important questions to ask themselves about any situation that can be represented and modeled mathemati- cally, such as: What is the role of measurement? How can benchmarks be developed to help make measurements readily accessible? Why is accuracy bandied in different ways in different situations? When can special rate methods be employed in situations when ratios occur?

The Mathematics in Data Around Us

Because Data Around Us is the closing unit in the grade 7 Connected Mathematics curriculum, it has objectives beyond developing the specific mathematical skills and understandings that comprise number sense. It offers students an opportunity to pull together many of the ideas and skills that they have been developing about proportional reasoning, area and volume, and algebra. The topic of number sense does not have the inexorable logical development that many areas of mathematics follow; the ideas may be presented in many ways. The conception of number sense that led to the sequence of topics used in this unit is as follows:

Reasoning about quantity begins with awareness of magnitude, or relative size. It involves the ability to work with both relative magnitude—including comparing and ordering numbers—and absolute magnitude—involving making sense of very large or very small numbers by building comparative analogies that are personally meaningful. An awareness of magnitude leads to a sense of measurement, the understanding that both units and counts are essential for describing quantity. The related idea that counts must be represented in an efficient way leads to an aware- ness of the various systems of numeration. Numerical information can be used to make deci- sions by comparison or to derive new information by performing operations on given data.