active learning in upper-division...
TRANSCRIPT
Active Learning in Upper-Division Physicslessons from the Paradigms
David RoundyOregon State University
DUE-0837829National Science Foundation
DUE-1141330
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
2 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
2 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
2 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
2 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
2 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
2 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Organization of curriculum
I 16 years ago, we began a major reform of our upper-divisionphysics curriculum.
I ∼25 incoming majors (class size 33-40 students)
I 91% of incoming majors continue to second quarter
I 68% of incoming majors obtain a degree in Physics
Junior-year Paradigms
I intensive 7-hour-a-week 3-week-long courses (2 credits)
I forces us to talk with each other
I forces students to talk with each other
Senior-year Capstones
I more conventional 3-credit courses
3 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Classroom norms
Breaking boundaries
Kinesthetic activities
Group work
Integrated labs
Group presentations
Small whiteboards
4 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Passing it onI monthly meetings of upper-division group
I regular peer teaching observationI Paradigms in Physics wiki page
I documents what we do in each courseI documents why we do what we do (e.g. stand on table)I shared problem sets
5 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Computational lab parallel to “traditional” courses
A computational lab for traditional courses
I reinforce learning in traditional courses
I save time by not having to introduce the physics
I students have a very busy schedule: just one credit
All work is done in the lab
I Today all physicists need to program
I Struggling students make little progress outside of class
I These are the students who need a computational course6 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Python and matplotlib
Reasoning
I free software, readily available to students
I ease of use and power comparable to Matlab
I used by professional scientists
I tutorials and help readily available on web
7 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching programming to physics students
No templates needed
I students write their programs from scratch
I they google for help
Pair programming
I students work in pairs: a driver and a navigator
I swap roles every 30 minutes or so
I “show and tell” when projects are done
8 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Electrostatics
The first two Paradigms cover electrostatics and magnetostatics.
Learning goals shared with the Paradigms
I how to compute distances
I curvilinear coordinates
I plotting with slices and lines through V (~r)
I integration as chopping and adding (how to set up integrals)
I taking advantage of symmetry
Learning goals specific to computing
I plotting
I writing functions and using loops
9 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Electrostatics (student work)Day 1: 4 point charges
4 3 2 1 0 1 2 3 4Distance (m)
0.0
0.5
1.0
1.5
2.0
2.5
3.0Po
tent
ial (
V)
I how to compute distances I how to plot10 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Electrostatics (student work)Day 2: 4 point charges
3 2 1 0 1 2 3X (m)
2.0
1.5
1.0
0.5
0.0
0.5
1.0
1.5
2.0
Y (m
)
15000000000.000 1500
0000
000.
000
v(X,Y,.1)
I plotting with slices11 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Electrostatics (student work)Day 3: Square of charge
10 5 0 5 1010
5
0
5
10
4000.000 4000.000
4000.000 4000.000
6000.000
8000.000
10000.00012000.000
Simplest default with labels
I chopping and adding I googling for help12 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Electrostatics (student work)Day 4: Square of charge (with varying density on left)
0 1 2 3 4 5z
0.0
0.5
1.0
1.5
2.0
2.5V
Sig = f, Potential @x=0, y=0
0 1 2 3 4 5z
01234567
V
Sig = 1, Potential @x=0, y=0
6 4 2 0 2 4 6x
6
4
2
0
2
4
6
y
Sig = f, Potential @z=.01
321
012345
6 4 2 0 2 4 6x
6
4
2
0
2
4
6
y
Sig = 1, Potential @z=.01
01234567
I visualizing in multiple dimensions13 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Computational conclusion
I all physicists do computing
I teach physics that is relevant to students
I lab-style course works great
I no templates needed
I pair programming
I python + matplotlib
14 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Challenges in thermal physics
I no thermo in our lower-division sequence
I variables p, V , T and S are unfamiliar
I students have never seen a differential in a math course
I partial derivative notation is new(∂T∂V
)p
I “everything else is held constant”I partial derivative manipulations are also new
I cyclic chain ruleI Clairaut’s theoremI ordinary chain ruleI inverse of a partial derivative
15 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Math notation vs physics notation
Physics(∂p
∂V
)S
=1(
∂V∂p
)S
physical observables
p = p(V ,S)
p = p(V ,T )
V = V (p,S)
V = V (p,T )
Math
∂u
∂x6= 1
∂x∂u
functions
u(x , y)
v(x , y)
x(u, v)
y(u, v)(∂u
∂x
)y
6= 1(∂x∂u
)v
16 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Mathematical interlude: a mechanical analogue for thermo
7 hours of thermodynamics math on a mechanical system
I integrating over a path to find work
I path independence to get potential energy
I small differences or tangent slope to find partial derivatives
I “holding everything else constant” is not possible
I partial derivative manipulations
I connection with experiment
I total differential for energy conservation
I Maxwell relations
I Legendre transformations
17 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
The partial derivative machineThe system
xy
xF
yF
I one hidden elastic system
I two controllable and measurable coordinates x and y
I two controllable forces Fx and FyI one potential energy U, not directly measurable
I can integrate work to find potential energy18 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Measuring partial derivatives(∂x
∂Fx
)y
vs
(∂x
∂Fx
)Fy
I students consistently believe these are the same
I they are taught to “hold everything else constant”
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Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Approaches for finding a derivative
I make a small change, measure a small change, take a ratioI mistake: use a very small change and get noiseI mistake: use a large change and assume linear responseI try a different small change to ensure “small enough”
I measure many values, make a plotI mistake: fit to a straight lineI find tangent line (by eye)
I mistake: seek analytic form to differentiate (black box helps)20 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
A mechanical analogue for thermo: First Law
I energy conservation and path independence: differentials
I looks like thermodynamic identity: dU = Fxdx + Fydy
I students integrate work to find potential energy
I paths from state A to state B (like pV plots)
21 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
A mechanical analogue for thermo: First Law
dU = Fxdx + Fydy
I Maxwell relation(∂(∂U∂x
)y
∂y
)x
=
∂(∂U∂y
)x
∂x
y(
∂Fx∂y
)x
=
(∂Fy∂x
)y
I can verify this experimentally
22 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
A mechanical analogue for thermo
I Legendre transform: imagine one mass is inside the black boxI you cannot change one force Fy
I you cannot measure the value y
I add potential energy of mass causing Fy :
V ≡ U − Fyy
I like enthalpy and Helmholtz free energy
I gives more Maxwell relations
23 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
What is this derivative?
(∂p
∂V
)S
24 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Name the experiment!
I give student groups specific derivatives
I students sketch an experiment to measure that derivative
I groups share their experiments with the class
25 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Name the experiment!Adiabatic compressibility
(∂p∂V
)S
=
26 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Name the experiment!General learning goals
I operational definitions of thermodynamic quantitiesI how to measureI how to fix
I what is held constant matters
I “canonical” thought experiments
I thermodynamic derivatives are physically measurable
27 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Name the experiment!Specific learning goals
I adiabatic processes:(∂T∂V
)S
,(∂T∂p
)S
and(∂V∂p
)S
I changing temperature without heating:(∂T∂V
)S
and(∂T∂p
)S
I the First Law:(∂U∂T
)V
and(∂U∂p
)S
I heat capacity:(∂S∂T
)V
and(∂S∂T
)p
I heating without changing temperature:(∂S∂V
)T
and(∂S∂p
)T
I using Maxwell relations:(∂S∂V
)T
,(∂S∂p
)T
,(∂S∂p
)V
and(∂S∂V
)p
I turning derivatives upside down: many of the above
28 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Measuring partial derivatives with experiment
Integrated labs enable tight coupling ofcoursework with experiments, includingteaching while data is being collected.
I ice-water calorimetry
I ice melting in water
I rubber band tension vs. L and T
Learning goals
I heat, heat capacity, latent heat
I work, free energy
I integrating experimental data
I measuring derivatives
I integrating to find ∆S
I Maxwell relations29 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Thermal conclusion
I connect math with tangible reality
I partial derivative machine
I name the experiment
I perform actual experiments
30 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Teaching upper-division physics well
departmental culture
I what students learn depends on what students do
→ lecture is not enough (for most students)
I math in physics courses is not like math in math courses
→ intentional and planned just-in-time teaching of math
I faculty need to agree on what is taught
→ faculty need to discuss what is taught!!!
connecting math with the real world
I integration as summation
→ computational lab and integrated lab activities
I measurable partial derivatives
→ in-class activities and experiments in thermal physics
31 / 33
Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Acknowledgements
Paradigms team
I Corinne Manogue
I Tevian Dray
I Mary Bridget Kustusch
I Henri Jansen
I Janet Tate
I David McIntyre
Energy and Entropy collaborators
I John Thompson (U. Maine)
I Michael Rogers (Ithaca College)
Students
I Eric Krebs and Jeff Schulte
I Grant Sherer
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Paradigms in Physics Computational Lab and Electrostatics Energy and Entropy Conclusion
Resources
I These slides:physics.oregonstate.edu/~roundyd/education.html
I Paradigms in Physics wiki:http://physics.oregonstate.edu/portfolioswiki
I Computational lab course website:http://physics.oregonstate.edu/~roundyd/COURSES/ph365
I G. Sherer, M. B. Kustusch, C. A. Manogue, and D. Roundy,“The Partial Derivative Machine,” 2013 PERC Proceedings.
I D. Roundy, M. B. Kustusch and C. A. Manogue, “Name theexperiment! Interpreting thermodynamic derivatives asthought experiments,” AJP (in press).
I D. Roundy and M. Rogers, “Exploring the thermodynamics ofa rubber band,” AJP (2013).
I D. Roundy, A. Gupta, J. F. Wagner, T. Dray, M. B. Kustuschand C. A. Manogue, “From Fear to Fun in Thermodynamics,”2013 PERC Proceedings. 33 / 33