The Heat is On

For my insulator test, I used four coffee mugs of hot water at 50⁰C.  The insulators I used for my mug coverings were aluminum foil, cotton T-shirt, newspaper, and plastic wrap.  My results were as follows:

Data Table

Recorded Water Temperatures (0C)	Material
	Foil	T-Shirt	Newspaper	Plastic Wrap
Initial	50	50	50	50
Final	43	43	40	42
Temperature Change	8	7	10	8

I had originally hypothesized that the foil would be the weakest insulator, simply because it was metal.  The foil encouraged conduction but discouraged convection.  My only conclusion for the reason it was not the worst is that the absence of convection with the foil resulted in a greater degree of heat being withheld compared to the convection that was occurring with the plastic wrap and newspaper.  Another thing I noticed on the surface of the newspaper was that it appeared to be wet on the outside, whereas the other materials were only damp on the inside when removed.  The newspaper obviously was allowing convection to occur, because water was traveling across the porous paper and then evaporating, which probably created a current that constantly cooled the water at a faster rate.  My explanation for the T-shirt being the best insulator is due to its thickness.  It did not have hardly any of the chemical properties to promote conduction by any means, and both convection and conduction must be less possible when the material in question is thicker.

            If I were conducting this lab at school, I would probably find some better insulators to work with, like rubber or parafilm.  It would also be nice to use a solid as the material generating the heat.  A hot dog fresh out a microwave would be a good way to show radiant energy in action.  Then, slicing the hot dog while it is still hot would show convection (the hot steam coming out).  Quickly wrapping the hot dog up in foil could then display conduction through the foil.

Guided Inquiry Experience from "Exploring the Physical World"

The question I selected for my guided inquiry experiment was whether a heavy pendulum or a light pendulum would come to rest more quickly. The first step of the inquiry process was planning the experiment. This involved obtaining equipment, which included three washers of varying mass, a long piece of string, a ruler for measuring the length of the pendulum, tape for marking the length on the string, a stopwatch, and a stopwatch reader (because the pendulum was being held by one hand and the weight needed to be released by the other). It also involved making note of all variables that needed to remain constant in order to get valid data for answering the question. I wanted to be sure that in comparing the time until rest for each mass that the length of the string would not change. The same stopwatch and manual timer was also used to avoid experimental error. I also wanted to run each mass three times to account for precision in the experiment. The final step of the planning process involved setting up a data table that was clear and concise for obtaining data for the task at hand.

Once the planning was completed, it was time to run the test. My results were as follows:

Washer	Time Passed Until 6” Pendulum Comes to Rest (s)
	Trial1	Trial 2	Trial 3	Average
Heavy	33.1	33.8	33.5	33.5
Medium	34.1	33.8	33.7	33.9
Light	33.6	33.5	33.2	33.4

From this data, the mass of the washer had no effect on the time it took for the pendulum to stop swinging. Just to verify this data further, I decided to run a second round of trials with the length of the string twice as long. I used the same washers for the same number of trials. My results were as follows:

Washer	Time Passed Until 12” Pendulum Comes to Rest (s)
	Trial1	Trial 2	Trial 3	Average
Heavy	52.1	51.8	50.9	51.6
Medium	51.4	51.2	50.8	51.1
Light	51.1	50.8	51.7	51.2

After viewing these results, it was clear to me that the mass of the weight on a pendulum was negligible when predicting the time the pendulum would go on swinging. By taking the time to complete a second round of experiments using a different length of string, another concept other than the initial question was accounted for. I found through guided inquiry that although mass has no effect on the time of pendulum swinging, the length of the pendulum string is proportional to the time it will take for the pendulum to come to rest. After researching the text further, I found that the equation that reflects this principle mathematically is

a_c= v²/r

where a_c is acceleration of pendulum weight, v is the velocity of the weight on the end of the pendulum, and r is the length of the pendulum string (Tillery, Enger, & Ross, 2008). The variable that is not in this equation is mass. Mass has no effect in this equation, but the length of the string does.

I was amazed at the precision of the results in this very basic experiment, especially since I was holding the pendulum by my hand as it was swinging. Any extra movement I made would throw off the true results for time, so plugging values into the equation mentioned above may be off a bit. The saving grace for this test was that the same type of error due to my movement was present to the same degree in each trial, leading to the precision of my values. To put it bluntly, my results were very precise, but they may be inaccurate, and one sure way to make the test more accurate would be to assemble a stationary fulcrum. This may lead to different stop times. However, the same result of mass being negligible should be apparent.

            I feel that any experience in which students formulate meaning based on direct observation of data is more rewarding than just giving them formulas to remember. I actually believe that searching for the formula that reflected the data received was part of the mystery that made the experience more enjoyable. This holds true for any inquiry experience. The unique aspect about today’s experience is that I had to develop the entire game plan for answering the question at hand. When a teacher provides only the question, and students must generate not only the results of a test, but the test itself, I believe that an increased level of thinking is involved that closely resembles the type of thinking that engineers must face when inventing a new process. One of the key functions of a K-12 STEM education is having the students “design investigations to gather data” (Lantz, 2009). The difficulties that an instructor may face with incorporating this method are lost time or safety concerns due to a general confusion as to what must be done to answer the question. It is always important then to remember that guided inquiry is “most successful when students have had numerous opportunities to learn and practice different ways to plan experiments and record data” (Banchi & Bell, 2008). Once students can become comfortable with these methods in a team environment, they are well on their way to becoming the next generation of engineers. Starting a lesson like this using amusement park rides is very exciting for children of all ages. I would have the students discuss whether the ride moves faster when it is completely filled with passengers or when it is empty. With all friction forces aside, the speeds should be the same, even though the force of the ride with the people is greater. You could also relate this fundamental property of mass and gravity to Galileo's experiment on the Leaning Tower of Pisa. These all provide either a background or an enrichment of the task at hand: to design the process. That is the most important goal for students when completing a guided inquiry lesson. It provides them with a sense of creativity and workmanship that can then be used to produce processes and answers to other questions in the future.

Banchi, H., & Bell, R. (2008). The many levels of inquiry. Science & Children, 46(2), 26–29.

Lantz, H. B. (2009). What should be the function of a K–12 STEM education? SEEN Magazine, 11(3).

Tillery, B. W., Enger, E. D., & Ross, F. C. (2008). Integrated science (4th ed.). New York: McGraw-Hill.