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Students know:

The orbits of Earth around the sun and of the moon around Earth, together with the rotation of Earth about an axis between its North and South poles, cause observable patterns.
These include day and night; daily changes in the length and direction of shadows; and different positions of the sun, moon, and stars at different times of the day, month, and year.
The apparent motion of the sun from east to west results in patterns of change in length and direction of shadows throughout a day as Earth rotates on its axis.
The length of the day gradually changes throughout the year as Earth orbits the sun, with longer days in the summer and shorter days in the winter.
Some stars and/or groups of stars (constellations) can be seen in the sky all year, while others appear only at certain times of the year.

Students are able to:

Using graphical displays (e.g., bar graphs, pictographs), organize data pertaining to daily and seasonal changes caused by the Earth's rotation and orbit around the sun. Organize data that include the following:
- The length and direction of shadows observed several times during one day.
- The duration of daylight throughout the year, as determined by sunrise and sunset times.
- Presence or absence of selected stars and/or groups of stars that are visible in the night sky at different times of the year.
Use the organized data to find and describe relationships within the datasets.
Use the organized data to find and describe relationships among the datasets, including the following:
- Similarities and differences in the timing of observable changes in shadows, daylight, and the appearance of stars show that events occur at different rates (e.g., Earth rotates on its axis once a day, while its orbit around the sun takes a full year).

Students understand that:

Similarities and differences in patterns can be used to sort, classify, communicate and analyze daily changes in length and direction of shadows, day and night, and the seasonal appearance of some stars in the night sky.

Analyzing and Interpreting Data

Patterns