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Design and non-design labs: does transfer occur?

Design and non-design labs: does transfer occur?. Anna Karelina, Eugenia Etkina, Alan Van Heuvelen, Maria Ruibal Vilasenhor, David Rosengrant, Rebecca Jordan and Cindy Hmelo-Silver Rutgers University Graduate School of Education http://www.islephysics.net

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Design and non-design labs: does transfer occur?

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  1. Design and non-design labs: does transfer occur? Anna Karelina, Eugenia Etkina, Alan Van Heuvelen, Maria Ruibal Vilasenhor, David Rosengrant, Rebecca Jordan and Cindy Hmelo-Silver Rutgers University Graduate School of Education http://www.islephysics.net http://paer.rutgers.edu/scientificabilities Funding for the project NSF grant DRL 0241078

  2. Lab task: Investigation of the behavior of the balloon Version 1: ... Version 2: Design an experiment to determine whether a helium-filled balloon and an air-filled balloon have the same drag coefficients. Version 3: ... Version 4. Use the helium balloon to determine its drag coefficient. Then predict the speed of the air balloon falling to the ground. In your report describe the experiment, your analysis and judgment. Resources available: two pages of this write-up, textbooks, internet.

  3. Time Spent on the lab activities

  4. Example of Lab report Clear description Multiple trials Correct mathematical procedure Result Judgment Non-design lab group • Determine the velocity of the balloon when air resistance and gravitational force are equal • place the sensor face downward • place the helium balloon on the floor • release the balloon • on the position-time graph find a segment with a constant slope • repeat twice more • find the average velocity • use the following equation to solve for drag coefficient • …for helium balloon Cd=0.51 • now repeat this procedure for air filled balloon… • air filled balloon - Cd= 0.61 • Drag coefficient for air and helium are indeed different.

  5. Example of Lab report Clear description Consistent and labeled sketch, chart and FBD Methods are explained and justified understanding of reason to do this Uncertainties Assumptions and effect of assumptions Results evaluation incorporates uncertainties and assumptions Design lab group The balloon is released. The motion sensor measures its upward velocity... Here is picture of the set-up. The chart is attached …The velocity increases until it reaches terminal velocity, here the net force is zero and acceleration is zero. Here are two free body diagrams for balloon at rest and at terminal velocity… The velocity was taken 3 times and averaged to allow for random uncertainty... Multiple trials • Calculated drag coefficient: Cd = 0.43… • Calculated velocity: V= 0.438±0.021m/s.. • Assumptions: • Balloon achieves terminal velocity – otherwise Fe≠Fd; • Re>10 – otherwise Fd equation is wrong • Cd is the same for air and helium – otherwise calculated velocity will be wrong. Correct mathematical procedure Result Measured velocity: V=1.216±0.228m/s The values do not overlap and therefore are not equal. Some assumptions must have been incorrect. Judgment

  6. “0” – missing “1” – inadequate “2” – needs some improvement “3” – adequate Design Non-design Scientific Abilities Ability to identify the assumptions Difference is statistically significant Chi-square = 67.90, p < 0.001 Identified relevant and significant assumptions 64% of design students 13% of non-design students Ability to evaluate/validate effect of assumptions Difference is statistically significant Chi-square = 53.3, p < 0.001

  7. “0” – missing “1” – inadequate “2” – needs some improvement “3” – adequate Design Non-design Scientific Abilities Ability to evaluate the uncertainty Difference is statistically significant Chi-square = 30.1167, p<0.001 Ability to evaluate the results by independent method Difference is statistically significant Chi-square = 16.36, p < 0.001

  8. “0” – missing “1” – inadequate “2” – needs some improvement “3” – adequate Design Non-design Physics understanding Free Body Diagram Difference is statistically significant Chi-square = 17.73, p<0.001 2% of design students 22% of non-design students have score “1” - draw wrong FBD Consistency of multiple representations Difference is statistically significant Chi-square = 7.838, p<0.025

  9. Conclusions • Design students: • Spent much more time on sense making • Wrote more profound and sophisticated lab reports • Described the procedure details, drew pictures, explained the reasoning, analyzed data, and evaluated results better • Outperformed non-design students on most of the important scientific abilities • Demonstrated better understanding of physics and logical reasoning If students consciously plan, monitor, evaluate and reflect on their actions, transfer occurs.

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