Baseball Bat Testing: Subjects: Topics: data. Math/Science Gathering and organizing data from an experiment Creating graphical representations of experimental data Analyzing and interpreting graphical representations of experimental Grades: 6-8 Big Ideas: wood bat). a. Certain materials provide better energy return than others (i.e. on average the composite bat will hit the ball further than the b. Graphs provide a means of quickly comparing data sets. Concepts: a. A graph can be used to identify statistical trends Objectives: a. Students will plot data from a computer simulation into a data table. b. Students will take data from a table and convert it into bar-graph form. c. Students will analyze and interpret the results of a computer simulation by comparing bar graphs from different data sets to determine which type of baseball bat (wood, metal, composite), provides the best overall energy return. d. Students will hypothesize why one type of bat provides better energy return than another. Essential? s a. How is the shape of the bar graphs similar? b. What is different about the overall shape of each bar graph? c. What does the difference in the shape of the graphs tell you about the effect of the bat s composition on a hitter s ability to make solid contact? d. Which bat would you choose and why? e. Create a hypothesis as to why the composite bat has a larger sweet spot than the wood bat. Vocabulary: Data, Plot, Histogram, Composition, hypothesis, simulation
Lesson: Introduction: Students will watch, The Science of a Bat s Sweet Spot. (1:48) 1. After viewing the video use a Venn diagram to compare and contrast wood and aluminum bats. Explain what a composite bat would be. (5:00) 2. Ask the students whether they ve heard the term, Sweet Spot. Discuss its meaning so those students who are unfamiliar with the term have a better idea. (1:30) 3. Pose the question, What factors might determine the size and location of a bat s sweet spot? (i.e. length, barrel size, weight, material) Discuss and list (3:00) 4. Once students have brainstormed factors that determine size and location of a bat s sweet spot, ask, What type of experiment could bat testers do to figure out which type of bat is best, wood, metal, or composite? Discuss (3:00) 5. The teacher will hand out the data sheet and explain that the class will be using a computer simulation to compare and contrast wood, metal, and aluminum bats. 6. Have the students get into groups of 2-3 (possibly bigger depending on the availability of computers.) If a lab or group of computers is not available the teacher could project his/her computer screen and do the activity as a group. 7. Log onto the stem simulation for comparing bats and select the wood bat. 8. Have the students select a length and weight that they will use for all of their trials. (Suggested 32in length, 28oz weight.) The length and weight should remain the same for all types of bats (wood, metal, and composite).
9. Place the length and weight selected into the appropriate spot on each data table. (make sure to do this for all three types of bats). 10. Depending on length selected, place the location of contact into the data table going up by increments of 2. E.G. 20, 22, 24, 26, 28, 30 if the length of the bat is 30. It is recommended that your last number match the length of the bat. 11. Have the students enter the number of swings they will use for their trials. The approximate length of the simulation for 1 swing per bat location is 7-10 minutes. For five swings per location it is about 25 minutes. 12. Have students run the simulation for the first location on the wood bat. Model how to record the data on the table. Have students fill in their table. (One student can run the simulation, one can read the results off screen, one can record data) 13. It is most efficient if the students keep the same location on the bat and switch to the metal bat. Run the simulation for the metal bat and record the data. Run the simulation for the composite bat. 14. Move the location on the bat up two inches (e.g. 20 up to 22). 15. Run the simulation for the wood, metal, and composite bats. Record data. 16. Continue to change the location on the bat by increments of two. Run the simulations and record the data until complete. 17. Model how to average the data and plot the result into bar graph form. 18. Have the students work together to plot their bar graphs. 19. As the groups complete their graphs discuss with them the essential questions related to the graphs. a. How is the shape of the bar graphs similar? b. What is different about the overall shape of each bar graph? c. What does the difference in the shape of the graphs tell you about the effect of the bat s composition on a hitter s ability to make solid contact? d. Can you use the shape of the graph to identify where the bat s sweet spot is located? 20. Have the students decide which bat they would choose to use in an important baseball game and why. Students may fulfill this requirement by either writing out their answer or by presenting their answer orally. Success Criteria:
Students will have succeeded in this lesson if they can: a. Correctly transfer data from the experiment into the data table b. Create an accurate bar graph from their simulation data c. Explain that the elongated top of the composite graph distances indicates that it has a larger sweet spot than that of the wood or metal bats d. Explain that the shape of the graph helps show where the sweet spot of the bat is e. Evaluate which bat is the best for use in an important game and why Sample Data Collection Sheet Material Length Weight Location - - - - - Wood 32 28 20 22 24 26 28 30 Trial 1 242 301 359 416 392 310 Trial 2 248 310 370 411 392 318 Trial 3 247 312 358 419 406 319 Trial 4 250 305 352 400 400 325 Trial 5 242 309 366 420 411 315 Average 246 307 361 413 400 317 Data Collection Sheet: Baseball Bat Testing Material Length Weight Location - - - - - Wood Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Average Metal Length Weight Location - - - - - Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Average
Composite Length Weight Location - - - - - Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Average Graphing Sheet:
Distance (Feet) Distance (Feet) Wood Bat 500 450 400 350 300 250 200 150 100 50 0 Location 1 Location 2 Location 3 Location 4 Location 5 Location 6 Sweet Spot Location Metal Bat 500 450 400 350 300 250 200 150 100 50 0 Location 1 Location 2 Location 3 Location 4 Location 5 Location 6 Sweet Spot Location
Distance (Feet) Composite Bat 500 450 400 350 300 250 200 150 100 50 0 Location 1 Location 2 Location 3 Location 4 Location 5 Location 6 Sweet Spot Location