UNITED NATIONS INTERNATIONAL SCHOOL TESTIMONIAL

By Angela Hugenschmidt, Computer teacher K-8

This project attracted me because I know it is important for students to have hands-on experience when learning.  It was an opportunity to work with the science department in the Middle School with whom I have had little contact in the past.  I decided to involve the seventh graders; they are lively and intelligent students who would benefit from a hands-on experience.

We had seven groups of two or three students.  They tested the following materials:

• packaging peanuts
• soil
• bubble wrap
• air
• aluminum foil
• cotton balls
• wood shavings
• wool and felt scraps

Availability determined these choices.

The school had to purchase the software, and we installed it on the common laptop because our networked computers and DataStudio are not compatible.  The laptop would also allow us to take it to the science lab when needed.  Originally I had one temperature probe. I ordered a second one with multiple usb ports, but then I found out that at least one more part was needed.  I proceeded with the experiments using one probe and reading off the ambient temperature from a regular room thermometer. The software was new to me, so we stuck to the basic features: the graphs and the tables.

The building of the box was more complicated than it should have been. Since I had to delegate the job and I could not be there during the assembly, adjustments had to be made.  I would have preferred to do the building myself and /or with some students, but we do not have the facilities.  We fixed the central shelf with screws for stability and to get rid of the supporting ledge that interfered with the bottom insulation.  We used duct tape to ensure a tight fit for the top cover, and we used supporting blocks to hold up the bottom shelf.

The basic insulation material was foam core bought at Home Depot with an insulation value R3. It was cut with a hot wire contraption at Lud Braun’s school.  It was the neatest way of cutting because I have had experience using a knife, which gets very messy. The mathematical calculations to create neatly fitting, interlocking pieces (to avoid heat loss through adjoining cracks) were an excellent exercise for us. The students checked the dimensions and practiced the “stuffing” of the box before the actual experimenting began. We labeled each piece to ensure a perfect, easy fit each time. The students enjoyed the activity.

There was some confusion about the type of material that could be used.  The terms recyclable and recycled were not fully understood.  I think that the need for recycling cannot be taught and shown enough; reusing still-usables must be practiced every day.

Another aspect of thinking that was challenged was the principle of heat transfer, i.e. why certain materials just seem to swallow up heat while others reject it.  The idea of using aluminum foil inside the air filled plastic bags was a good idea. Even though the students in Group 4 had just learned about the reflecting heat principles, they did not understand their application and limitation.

When actually collecting the materials, the students found it hard to gather enough to fill the space all around the heating assembly.  There was another lesson to be learned: How to intelligently estimate and judge volume by comparing with the foam core pieces. There were many more ideas suggested for materials than could practically be used.One was water.  We wanted to try to contain water safely to measure its insulation value and may still do this in the future.  I am surprised that the students did not pick up on using paper, even though we spoke about it.  I will look at an exercise in using different methods of assembling paper to influence its insulating capability (crumbling, rolling, stacking, compressing.) 

The testing station was set up in the computer lab because that is where I am most of the day.  Here I could receive small groups to do the testing.  The equipment was placed on a trolley with its own outlets. The students were involved in the setting up of the graphs, and at first we learned from trial and error how to manipulate the software.  Not all of our graphs were set up the same.  Some showed larger intervals on the time axis.  It made for interesting arithmetic when estimating the time values along the axis and calculating time differences manually at first.  The tables allowed accurate readings.  The comparative interpretations were done with the science teacher. Since I have been teaching the upper Middle School classes only recently, I have not had so much experience with the setting up of the spreadsheet; this was an excellent opportunity to apply that skill.

When interpreting the data, we used these methods:

1. looking at the slopes and comparing them without using the numbers.
2. estimating the times on the graph by drawing lines from the critical points to the horizontal time axis and getting a closer estimate.
3. using the exact time records from the multiple-page computer printouts.

Record the exact times Read the exact time in seconds it took to reach the following temperatures in degrees Celsius: Use the graph’s timeline first to get an estimate. Then obtain the data from the print-outs or use the smart tool found in the DataStudio software. Subtract to find the time differences. Group #: __  Group names: ____________________________ Material: ____________________________________ Ambient temperature before heat Ambient temperature when heat is turned on 30°C above ambient going up 30°C above ambient going down 10°C above ambient going down 5°C above ambient going down Difference between 30 and 10 above ambient Difference between 10 and 5 above ambient Difference between 30 and 5 above Estimated reading from the printed line graph 0 30 Reading from the accurate table print-out 0 30

Record the exact times copied from data sheets Read the exact time in seconds it took to reach the following temperatures in degrees Celsius Group #: __  Group names: __________________________________ Material: ____________________________________  >   Ambient temperature before heat Ambient temperature when heat is turned on 30°C above ambient going up 30°C above ambient going down 10°C above ambient going down 5°C above ambient going down Difference between 30 and 10 above ambient Difference between 10 and 5 above ambient Difference between 30 and 5 above No layer 0 30 1850 2184 3010 4490       1 layer 0 30 288 400 930 1780       2 layers 0 30 223 272 940 1610       3layers 0 30 207 470 1280 2580       Peanuts 0 30 305 400 1035 1860       Soil 0 30 455 594 1096.6 1770       Bubble wrap 0 30 355 772.5 1650 2910       Air & Foil 0 30 >820 950 1730 2440       Cotton balls 0 30 457 990 3180 5280       Wood, Shavings 0 30 >330 330 1020 2350       Felt & Wool 0 30 786.66 1390 5530 11180

The spreadsheets gave a good overview, and the accompanying bar graph provided additional visual representation of the results.  Some discussion took place with the individual groups, some in whole class discussions.

To keep the tests as reliable as possible, we tried to conduct each test under equal conditions:

• Same manner of filling the space: Filling the material tightly against the cage around the heat source
• Stable ambient room temperature: No change in opening windows and doors; no change in student population during the testing time
• Same method of tightly closing the lid: Using duct tape because the wood was not good enough for applying screws multiple times.

We found some inconsistencies:

• Some of our experiments never reached five degrees above ambient temperature.  We used the 10-degree above ambient temperature for the final interpretation of the data.
• One group was short one degree in reaching the 30 degrees above ambient room temperature. We noticed the mistake too late.  We calculated the cooling time from that temperature to 10 and to 5 degrees above ambient temperature. We know the cooling time is affected, and the results are faulty even though by a small margin.
• One of the materials -cotton balls - may not be considered for the purpose of house insulation, because it cannot be collected in sufficient amounts for use as house insulation; there may also be a health hazard.
• The numbers in the experiment with no insulation didn’t match the pattern we had seen. The less effective the insulation, the faster the temperature will go down. We expected the cooling process to be shorter. A general rule in science: Experiments must be done many times before basing big decisions on the results.

Problems:

We had some problems with the software and the equipment.

DataStudio was not compatible with our networked system, so the program was installed only on one laptop. We had to rely on printouts for calculations and could not show results on a big screen or work simultaneously on all computers.

The software has many hidden features. Learning them took some time. Still some of the students ended up with different formats.  With standard formatting, the data could have been viewed comparatively on transparencies projected on a large screen by the whole class. We had only one temperature probe.

During the process we made some mistakes, which required reruns. Several times an experiments was interrupted.  Touching the mouse or keyboard during screen save; or accidentally stopping the Xplorer instead of unplugging the heat source; or letting the temperature go too high. This was very time consuming. Sessions had to be rescheduled. Sometimes students had to go off to other classes. Teaching individual groups had its advantages, but sometimes errors in handling the laptop and the tools repeated themselves. It was hard for the students to wait for the results without being distracted at the critical moment. It took much longer to bring all the experimenting to a conclusion than initially anticipated. The students and teachers learned a lot along the way. 

Suggestions:

• Build the box in plenty of time before conducting the tests.
• Have several boxes to allow many students to work simultaneously.
• Collect the materials early and judge the amounts
• Maybe have a cardboard box with volume equivalent to the total needed.
• Know the software beyond the basic features.
• Conduct other shorter experiments involving big temperature changes in order for the students to become familiar with the software and the procedures.
• Practice the language needed for the interpretation.
• Use the software and the equipment often.

Follow-up:

• In the science lab the students set up similar experiments with two materials at a time and recorded the temperature changes fixed at intervals by hand.  The process was shorter, and the results were immediate.
• A reverse way of measuring insulation efficiency could be done with ice cubes where the students could use same sized large cans and a small can for holding the ice cube. The insulation material would be stuffed around the can with the ice cube, and a transparent cover is placed on top. There is no heat source needed. The materials are readily available. Each group can run as many experiments as they are willing to prepare. The results are not so interesting mathematically since there is only one reading, but they certainly show clear rank.
• Moving the experiments outdoors could be interesting and exciting if this is feasible.
• To involve other students in the school and parents, announce the materials that will be used and have them rank their insulation efficiency. Then compare their guesses with the results.

The DataStudio software and the probes were excellent as well as the telephone support.

Electronic Educational Village