# Data Collection – Linear

On Wednesday, as part of my Innovative Teaching Grant from the Pearland ISD Education Foundation, my students and my subject partner’s students completed their first data collection lab.

### Objectives

• Model data using a linear equation.
• Interpret the slope and intercept values from a linear model.

### Procedure

Case 4 Flipping Coins Instructions

Due to larger than anticipated class sizes, time constraints, and limited 1982 pennies, students worked in groups of three to collect data for one set of pennies (pre-1982, 1982, or post-1982).  In a class of 30, four groups collected data for pre-1982 pennies, two groups collected data for 1982 pennies, and four groups collected data for post-1982 pennies.  After each group collected their data, the data was shared with the class and compared.

### Results

Pre-1982 Pennies

1982 Pennies

Post-1982 Pennies

Students found that pre-1982 pennies were the most dense and post-1982 pennies were the least dense.  Based on their results, they determined that the composition of the penny changed in 1982.

Students interpreted the slope as the “weight” per penny and the y-intercept as the “weight” of the bucket.

For homework, the students completed the Case 4 Flipping Coins Evidence Record.

Case 4 Flipping Coins Evidence Record

### Follow-up Questions

Today, I sent the students some follow-up questions using the TI-Nspire Navigator Quick Polls to assess their understanding.

I showed the students the graph below and asked “Which object weighs more?”.

The results from one class period:

Almost every student correctly identified the correct answer.  All other periods had similar results.

Then I told the students, “The equation to model Object 1 is y = 0.5x + 0.5.  The equation to model Object 2 is y = 0.7x + 0.5”.  I asked, “What is the weight of the bucket?”.

The results from one class period:

Every student correctly input the correct answer.  All other periods had similar results.

Finally, to truly test their understanding of the meaning of the slope and y-intercept, I told the students, “You weighed 5 objects and found the weight to be 10 N.  The bucket weighed 0.5 N.”  I asked them to “Write an equation to model the weight of x objects.”.

The results from four class periods:

The first two classes needed some reteaching regarding slope.  The last two classes did better, but there is still room for improvement.  My last class period did not participate in the follow-up questions due to class orientation meetings during their class period.

# Innovative Teaching Grant

In March, I applied for an Innovation Teaching Grant through the Pearland ISD Education Foundation.  The project is described below.

### Project Summary

This project will provide the hardware required for real-time data collection by students working in small groups to support three Algebra 2 standards.  Real time data collection and analysis provides the tools to allow students to focus on the collected data and provides the foundation for application of the learning from the Algebra 2 curriculum to Science classes.

### Purpose

There are three Algebra 2 standards that apply to data collection:
1.  Predict and make decisions and critical judgments from a given set of data using linear, quadratic, and exponential models.
2.  Analyze data to select the appropriate model from among linear, quadratic, and exponential models.
3.  Use regression methods available through technology to write a linear function, a quadratic function, and an exponential function from a given set of data.

The math department currently has a limited set of hardware which has been used for data collection to support these standards.  With limited equipment, the data collection must be performed by the teacher with the resulting data supplied to the students for analysis.

The purpose of the data collection project is to have students work in small groups to collect their own data, analyze and interpret the data, and predict and make decisions based on the appropriate model. In order for the students to perform the activities, we must have additional data collection equipment.

### Objectives

By the end of the school year, all PAP Algebra 2 students will have completed at least three data collection activities (linear, quadratic, and exponential), working in small groups, utilizing the hardware supplied by this grant.

### Project Description

The teacher will use pre-made activities from TI’s Math Nspired or Vernier’s websites.  Possible activities include That’s the Way the Ball Bounces – Height and Time for a Bouncing Ball, Chill Out: How Hot Objects Cool, and Making Cents of Math: Linear Relationships between Weight and Quantity.

Research suggests that real-time data collection seems to be the most effective way to connect a graph with real-world experiences. (Lapp, Douglas A., and Vivian Flora Cyrus. “Connecting Research to Teaching: Using Data-Collection Devices to Enhance Students’ Understanding.” Mathematics Teacher 93.6 (2000): 504-10. – National Council of Teachers of Mathematics. Web. 28 Feb. 2015.)

Automated data collection improves the accuracy of the data collected and allows students to focus on the positive educational impact of the development of the mathematical model rather than the methodology of the data collection.

Real-time data collection by the students will supply the foundation for the application of linear, quadratic and exponential models to the analysis of physical measurements made in science curriculum.

### Project Evaluation

Students will complete the student pages available through the pre-made activities.  The teacher will use the TI-Navigator to capture screen shots of the student’s data and to send quick polls to assess student’s understanding of concepts learned in each activity.

### Budget

3 – TI CBR2 motion sensors – \$247.17
9 – Dual-range force sensors – \$981.00

### Other Funds Secured

For the students to perform their own data collection, working in small groups (4-5 students per group), there must be a total of 10 sets (5 sets per teacher) of data collection hardware.

The math department currently has: