|Grade span:||5 to 8|
|Duration:||45 to 60 minutes|
Description:This sample lesson is one example of how you can implement the Math Tools practice. In this activity, students will predict how many M&Ms are in a bag, then collect data and graph their findings in MS-Excel.
- Collect data through observations
- Represent data using tables and graphs (by means of MS-Excel)
- Use data for a variety of purposes (formulating hypotheses, making predictions, testing conjectures)
- Determine probability using simulations or experiments
- Enter data into a spreadsheet, use formulas to update solutions automatically, and create a pie graph
- Use ratios and proportions to represent relationships among quantities
- Explain and justify their thinking
- PC or Macintosh with an electronic spreadsheet application such as MS-Excel, word processing software such as MS-Word for writing summaries of findings, access to the Internet (optional)
- Small bags of M&M's (one bag per student)
- Students needs to have basic keyboarding skills, know how to open, close, and save documents, and open and navigate a software application such as MS-Excel and MS-Word.
- Teachers need to know how to open, close, and save documents, how to create an MS-Excel worksheet (including using formulas), and use MS-Word.
What to Do:
- To begin this lesson, have students estimate the number and color of candies inside their small bags.
- After the estimations have been made, students open their bags to sort, classify, count, and record the M&M's. Students are then directed to write ratios to represent their findings. Technology plays an integral part in the remainder of this lesson. Following the collection of data, students use an electronic spreadsheet to create a graph of their findings. Please review and print the detailed description in Graphing Rock Candy (PDF).
- When students finish collecting data, they will compile a set of everyone's findings to estimate the number and color of M&M's in a mystery bag.
- In order to win the mystery bag, students must not only make a conjecture but also explain their reasoning using the data sets.