Computing as a Central
Theme in Introductory
Physics
Martin S. Mason
Mt. San Antonio College
June 2012
What is computational
modeling?

Using the outputs of a computer
system to describe or predict the
behavior of a physical system.
Why Computational
Modeling?



Tackle interesting problems that can’t
be ‘solved’ analytically with freshman
physics, but can be approximated.
This is no right answer, just a series of
more accurate approximations.
A large part of what modern Scientists
and Engineers actually do!
Students need
Computational Skills
A New direction for
Physics Laboratories

What best describes your laboratory?
A.
B.
C.
D.
E.

Separate from Lecture with a different instructor / TA
Separate from Lecture with the same instructor
Integrated with Lecture (Studio or Workshop format)
Block Schedule
No Lab defined
How often is lab offered per week?
A.
B.
C.
D.
4 or more times
3 times
Twice
Once
What should we do in
Laboratory?

Laboratory activities must be designed so that students may acquire skill and
confidence in:
– Measurement of physical quantities with appropriate accuracy
– Recognition of factors that could affect the reliability of their
measurements
– Manipulations of materials, apparatus, tools, and measuring instruments
– Clear descriptions of their observations and measurements
– Representation of information in appropriate verbal, pictorial, graphical,
and mathematical terms
– Inference and reasoning from their observations
– Ability to rationally defend their conclusions and predictions
– Effective and valued participation with their peers and their teacher in a
cooperative intellectual enterprise
– Articulate reporting of observations, conclusions, and predictions in
formats ranging from
– Informal discussion to a formal laboratory report
– Ability to recognize those questions that can be investigated through
experiment and to plan, carry out, evaluate, and report on such
experiments.
What is Vpython?


a free, open-source, multi-platform,
3D programming environment
especially suitable for use by students
in introductory physics courses
(including novice programmers).
Written by David Scherer for Ruth
Chabay and Bruce Sherwood’s Matter
and Interactions course
Computational Modeling
in the lab

What do we do?
– Extend hands on experiments with
models
– Create visualizations that help with
conceptual understanding
– Develop transferable programming and
visualization skills

What don’t we do:
– Run simulations that someone else wrote
Why Do Projects?





Students as Scientists
Treat more detailed problems
Give sense of connection between
physics topics
How and Why physics is useful
It’s Fun!
Projects





Three 5 week projects.
Six hours in class and 20-30 hours outside
of class.
Project is designed to require course
material from that five week period and
before.
Projects change every semester.
Project is presented as a formal powerpoint
presentation.
Types of Projects



Create a computational model that predicts
the behavior of a physical system.
Create a computational model that
investigates something that can’t be modeled
physically.
An open ended problem chosen by the
student, Compare the behavior of a physical
system and the behavior of a computational
model with theoretical calculations.
Example



Model the behavior of a
foam rocket launched from
an elastic launcher.
Compare the results of your
model to the actual
trajectory determine from
video analysis.
Competition.
Example



Create a system of three lunar orbiting
communication satellites that always
provide a link from the north pole of the
moon to the earth.
Include the gravitational effects of both the
moon and earth on the satellites.
Show that your system is stable for 10
years.
Final Project




A mass is placed on a low friction cart
attached to a spring. At what
amplitude will the mass on the cart
begin to slip?
Video of System
Computational model
Textbook solution makes many
simplifying assumptions
Outcomes:




More students transition into summer
REU/Research programs.
Anecdotal reports are positive about the
utility of projects after transfer.
Difficult to measure impact on traditional
assessment.
Student retention was lower for first three
semester after the projects were
implemented, but has climbed back up.
Project Grades vs. Exam
Grades
Project Rank


Projects measure
different skills then
exams.
Students who do
well on exams do
not always do well
on projects and vice
versa.
Exam Rank
1
4
2
2
3
3
4
6
5
20
6
7
7
14
8
1
9
18
10
12
11
16
12
11
13
8
14
15
15
17
16
9
17
10
18
5
19
13
20
19