Meeting Computing Needs Across
Campus
Mark Guzdial, School of Interactive Computing
Story
• Why we should teach computing to everyone
• Making computing work for everyone at
Georgia Tech.
– Lesson Learned:
Contextualized computing education.
– What our courses are like
•Side trip into second course
– Results
• Side trip: Applying the lesson to the BS in CS.
• Finally, what does it buy us in CS?
2
Time Warp to Fall 1999
• Fall 1999:
All students at Georgia Tech must take a course in
computer science.
– Considered part of General Education, like mathematics,
social science, humanities…
– Heroes: Peter Freeman, Rich LeBlanc, Kurt Eiselt, Russ
Shackelford
• Why did Georgia Tech make that decision?
– Computing was a College.
– Making competitive distinctions for Liberal Arts
– ABET might start requiring CS.
3
More reasons for
computing across curriculum
• Everyone needs to learn about process (Alan
Perlis)
• Algorithms control our lives: The tyranny of
the computationally literate (C.P. Snow)
• The tools of learning for computational
scientists and engineers brought to the
classrom.
– Computers are cheaper than Super-Conducting
Supercolliders
4
1961 MIT Sloan School Symposium
5
Computing for Everyone
• In 1961, Alan Perlis argued
that computer science
should be part of a liberal
education.
– Explicitly, he argued that
all students should
learn to program.
• Why?
– Because Computer
Science is the study of
process.
– Automated execution of
process changes
everything
6
The Power and Fear of Algorithms
• The Economist (Sept.,
2007) spoke to the
algorithms that control
us, yet we don’t
understand.
– Credit Ratings, Adjustable
Rate Mortgages, Google
• C.P. Snow foresaw this in
1961.
– Those who don’t
understand algorithms,
can’t understand how the
decisions are made.
“A handful of people, having no
relation to the will of the society,
having no communication with the
rest of society will be taking
decisions in secret which are going
to affect our lives in the deepest
sense.”
7
Adopting Computing—without us
• At Georgia Tech and other Universities:
– Biology teaches programming for mathematical and computational
models.
– Physics teaches VPython for labs where they solve three-body
problems.
• Computer science provides the tools and metaphors for
understanding science.
• Scientists and engineers use computing to model, simulate,
and understand.
– Why shouldn’t science and engineering students?
– History repeating: Telescopes, microscopes.
– Unlike other scientific instruments, computers are already cheap and
plentiful.
• Problem: They’re doing it without us.
8
Richard Dawkins on Fresh Aire
GROSS: You close your book saying, "I am thrilled to be
alive at a time when humanity is pushing against
the limits of understanding." How do you think that's
happening in your field of evolutionary biology?
Mr. DAWKINS: Well, it's the most exciting time to be a
biologist…Since Watson and Crick in 1953, biology
has become a sort of branch of computer science. I
mean, genes are just long computer tapes, and they
use a code which is just another kind of computer
code. It's quaternary rather than binary, but it's read
in a sequential way just like a computer tape. It's
transcribed. It's copied and pasted. All the familiar
metaphors from computer science fit.
9
Back to Georgia Tech in 1999
• Key Point: Only one course met the
requirement:
CS1321 Introduction to Computing
– Shackelford’s pseudocode approach in 1999
– Later Scheme: How to Design Programs
• Why only one?
– Resource issues
– “Service Ghetto”
– The offer to help them do their own
10
CS1321: Pass (A, B, or C) vs.
WDF (Withdrawal, D or F)
Pass
02 Fall
02 Spring
01 Fall
WDF
Total
74.01%
26.74%
Female
62.99%
36.65%
Male
77.00%
22.90%
Total
65.03%
34.87%
Female
65.56%
34.44%
Male
64.81%
35.04%
Total
70.98%
29.02%
Female
59.55%
40.45%
Male
73.63%
26.37%
11
Contextualized Computing
Education
• Since Spring 2003, we teach 3
introductory CS courses.
– Responding to research results about CS
being “irrelevant”
– Based on Margolis and Fisher
“alternative paths”
• Each course introduces computing
using a context (examples, homework
assignments, lecture discussion)
relevant to majors.
• Make computing relevant by teaching
it in terms of what computers are
good for (from the students’
perspective).
12
Our Three CS1’s Today
• CS1301/1321 Introduction to Computing
Traditional CS1 for our CS majors and
Science majors (math, physics, psychology,
etc.).
• CS1371 Computing for Engineers
CS1 for Engineers. Same topics as CS1301,
but using MATLAB with Engineering problems
in homework and examples.
• CS1315 Introduction to Media Computation
13
Introduction to Media Computation
• Average 400 students/term
– Overall, CS1315 has been 51% female
– Required in Architecture, Management, Ivan Allen College
of Liberal Arts, and Biology
• Focus: Learning programming and CS concepts within
the context of media manipulation and creation
– Converting images to grayscale and negatives, splicing and
reversing sounds, writing programs to generate HTML,
creating movies out of Web-accessed content.
– Computing for communications, not calculation
14
Media Computation:
Teaching in a Relevant Context
• Presenting CS topics with
media projects and
examples
– Iteration as creating negative
and grayscale images
– Indexing in a range as
removing redeye
– Algorithms for blending both
images and sounds
– Linked lists as song fragments
woven to make music
– Information encodings as
sound visualizations
15
def clearRed(picture):
for pixel in getPixels(picture):
setRed(pixel,0)
def greyscale(picture):
for p in getPixels(picture):
redness=getRed(p)
greenness=getGreen(p)
blueness=getBlue(p)
luminance=(redness+blueness+greenness)/3
setColor(p,
makeColor(luminance,luminance,luminance))
def negative(picture):
for px in getPixels(picture):
red=getRed(px)
green=getGreen(px)
blue=getBlue(px)
negColor=makeColor(255-red,255-green,255-blue)
setColor(px,negColor)
16
Syllabus for Introductory Course
• Getting started: Defining and executing functions
• Pictures
– Psychophysics, data structures, defining functions, loops, conditionals (redeye removal, posterizing)
– Bitmap vs. vector notations
• Sounds
– Psychophysics, data structures, defining functions, loops, conditionals
– Sampled sounds vs. synthesized, MP3 vs. MIDI
• Text
– Converting between media, generating HTML, database, and networking
– A little trees (directories) and hash tables (database)
• Movies
• Then, Computer Science topics (last 1/3 class)
17
Computer Science Topics
as solutions to their problems
• “Why is PhotoShop so much faster?”
– Compiling vs. interpreting
– Machine language and how the computer works
• “Writing programs is hard! Are there ways to make
it easier? Or at least shorter?”
– Object-oriented programming
– Functional programming and recursion
• “Movie-manipulating programs take a long time to
execute. Why? How fast/slow can programs be?”
– Algorithmic complexity
18
Examples of Student Work
SoupAudio
Collage
CanonLinkedList of
(MIDI) Music
19
Student voices
• Intro CS student (female): “I just wish I had more
time to play around with that and make neat
effects. But JES [IDE for class] will be on my
computer forever, so… that’s the nice thing about
this class is that you could go as deep into the
homework as you wanted. So, I’d turn it in and then
me and my roommate would do more after to see
what we could do with it.”
• High School teacher: “This was the best (noncollege credit) workshop I have ever taken.”
• Students in multimedia data structures: “Data
structures is an important step. Use of media! It
makes it fun.”
20
A Media Computation Data Structures Course
• Driving question:
“How did the
wildebeests
stampede in The
Lion King?”
21
Connecting to the Wildebeests
It’s all about data structures
22
Similar Assignments,
but with Objects and Agents
23
Results: CS1315 “Media Computation”
Pass
04 Fall
04 Spring
03 Fall
WDF
Total
80.33%
19.65%
Female
82.90%
17.10%
Male
77.46%
22.54%
Total
89.87%
9.37%
Female
91.94%
7.58%
Male
87.50%
11.41%
Total
86.47%
12.54%
Female
88.36%
10.27%
Male
84.71%
14.65%
24
Success Rates for Specific Majors
Success rates in traditional CS1 for students in various majors average
Fall ’99 to Fall ’02, compared to Spring ’03 to Fall ’05 in Media
Computation.
25
Results: CS1371 “Engineering”
Pass
04 Fall
04 Spring
03 Fall
WDF
Total
85.03%
14.87%
Female
85.55%
14.45%
Male
84.92%
14.96%
Total
75.27%
24.27%
Female
75.54%
23.74%
Male
75.19%
24.42%
Total
73.94%
26.06%
Female
71.72%
28.28%
Male
74.49%
25.51%
26
Results of four years of evaluation
• MediaComp students are more motivated and
engaged (retention data, interviews), and find the
course social, creative, and “relevant.”
– Replicated at several institutions now.
• Students in the contextualized courses program
outside of class.
– Immediately (engineers) and even a year later
(MediaComp)
• Students in MediaComp classes (both, and new
Architecture course) spend extra time on homework
“because it’s cool.”
27
The Other Results
• We don’t know if they learn the same.
– The challenge of comparative studies when there
is no common reality.
• While engaging, majority of students do not
find the MediaComp courses relevant to their
degrees or professions.
– Many do find it relevant to their lives.
• Students distinguish between “more
MediaComp classes” and “more CS classes”
28
Next steps…
An alternative path and a minor
• What happens when you have an intro to CS course
for non-majors that students pass and even enjoy?
• Define a CS minor
– About 100 students today
• Create new BS in Computational Media
– Joint with School of Literature, Communications, and
Culture
– 58 majors in first year, 24% female
Over 200 majors today, still about ¼ female
29
How about CS?
Back to CS1321
Pass
04 Fall
04 Spring
03 Fall
WDF
Total
84.34%
15.26%
Female
89.36%
10.64%
Male
83.17%
16.34%
Total
68.26%
31.74%
Female
67.57%
32.43%
Male
68.46%
31.54%
Total
81.42%
18.45%
Female
77.86%
22.14%
Male
82.18%
17.67%
30
A Context for CS1 for
CS majors: Robotics
• Microsoft Research has funded
the Institute for Personal
Robotics in Education
– Tucker Balch, Directing
Joint between Bryn Mawr and
Georgia Tech
– http://www.roboteducation.org
• Goal is to develop a CS1 (and
CS2) with robotics as the context.
– Homework:
• Recursively follow a light
• Enter a pyramid and take a
picture of it.
• Hold a “Peacebot”
demonstration.
• Film a movie and use
MediaComp for special
effects
31
Using Context throughout the
CS Curriculum
• The future of computing is not in
merely being a good
programmer.
– Those skills are now commodities
that can be outsourced anywhere.
• When “The World is Flat”
(Friedman), we become
competitive by bridging areas
and differentiating.
32
Microsoft wants employees
who know context for CS
“The nature of these jobs is not closing the
door and coding,” (Bill) Gates said. “The great
missing skill is somebody who’s good at
understanding engineering and bridges that
[understanding] to working with customers
and marketing…We can promise these
people most of what they’re doing won’t be
coding.”
– Gates worried over decline in US computer scientists,
ComputerWorld, July 18, 2005 (by Elizabeth Montalbano)
33
The Threads™ Curriculum
• We have defined 8 Threads in
Computing:
– Computing and People
– Computing and Information Internetworking
– Computing and Media
– Computing and Platforms
– Computing and Intelligence
– Computing and Foundations
– Computing and Computational Modeling
– Computing and Devices (was Embodiment)
34
The BS in Computer Science under Threads™
• Each Thread specifies the courses needed to know
that area well.
– From introductory computing,
through advanced courses,
to beyond Computer Science
(Psychology, Physics, Computer Engineering).
• A degree is the union of any two Threads.
– Every Combination is a
full Computer Science degree,
but bridging disciplines and clearly different from “just
programming.”
– No Thread choice is necessary in first year,
Can always choose different Threads during degree.
35
Back to Computing Across Campus
• What do we get from teaching computing to
the rest of campus?
– Maybe make our students more competitive?
•Maybe attract more students?
– New problems to work on.
•The difference between Computer Science and
Computing.
– Where the interesting stuff is.
– A change in culture.
•Pedagogical methods.
– Critical design in Architecture
•Research methods
36
Computer Scientists and
Reading
• Alan Perlis, Norbert Weiner, J.C.R. Licklider, C.P. Snow
• Others included Vannevar Bush, Herbert A. Simon, Marvin L.
Minsky, Jay W. Forrester, Grace M. Hopper, Claude E.
Shannon, John G. Kemeny, Gene M. Amdahl
37
Summary
• The rest of campus needs what we have to offer.
• We have found that the way they need computing
education is different than the way we offer it to our
students.
– Maybe we need to change what we offer to our own
students.
• We have found a contextualized computing
approach works (for the measures we have now).
• There may be benefits for our CS culture in making
more connections to the rest of campus.
38
Thank you!
Mark Guzdial
http://www.cc.gatech.edu/~mark.guzdial
http://home.cc.gatech.edu/csl
For more on MediaComp approach
(including papers, software, and
slides):
http://coweb.cc.gatech.edu/mediaCompplan
Media Computation Teachers’ Site:
http://coweb.cc.gatech.edu/mediaCompteach
39
Next steps in Threads: Roles
• Threads are about conceptual focus.
• Within any Thread, might play different roles:
–
–
–
–
–
A Master Practitioner
An Entrepreneur
A Researcher
A Communicator/Teacher
A Public Policy Maker
• We are defining recommendations for these roles in
terms of experiences and elective classes in
software engineering, management, and other
areas.
40
What Georgia Tech Teaches
CS1315 (Media
Computation
CS1 in Python)
CS1316
(Structure &
Behavior—
Multimedia data
structures in
Java)
CS2260:
Media Device
Architectures
CS1301
Intro to
Programming in
Python for CS
majors
CS1331
CS1+2 in
Java
CS1332
Data
Structures
and
Algorithms in
Java
CS2110
(Low-level
programming in C)
CS1371
(Computing for
Engineering in
MATLAB (only))
CS1372
Algorithm
Design in C
Institute for Computing
Education (ICE@GT)
Summer Workshops
for High School
Teachers: Media
Computation CS1 in
Java
41
Computing and Devices
42
Computing and Information Internetworking
43
Want a job in Information Security?
• Information Internetworking +
Foundations
– Encoding and storing information
securely for organizations
• Information Internetworking +
Platforms
– Making information flow securely
between large databases and small
cell phones and PDAs.
44
Preparing for Jobs to Come
• The Future of Robotics:
Devices + People
45
Preparing for Jobs to Come
• Platforms + Media
• Platforms + People
46
For More Information…
http://www.cc.gatech.edu/threads
47