Meeting Computing Needs Across Campus

1. Meeting Computing Needs Across Campus Mark Guzdial, School of Interactive Computing

2. 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?

3. 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. • Solved a problem for Engineering • Making a competitive distinction for Liberal Arts

4. New reasons: Computational Thinking • 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 classroom (Jeanette Wing). • Computers are cheaper than Super-Conducting Supercolliders

5. 1961 MIT Sloan School Symposium

6. 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

7. 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.”

8. Adopting Computing:With CS? • 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 our world • Jeanette Wing’s “Computational Thinking” • Scientists and engineers use computing to model, simulate, and understand. • Why shouldn’t science and engineering students? • History repeating: Telescopes, microscopes. • Computers are already cheap and plentiful.

9. 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.

10. 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

11. CS1321: Pass (A, B, or C) vs. WDF (Withdrawal, D or F)

12. Contextualized ComputingEducation • 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).

13. Our Three CS1’s Today • CS1301/1321 Introduction to ComputingTraditional CS1 for our CS majors and Science majors (math, physics, psychology, etc.). • CS1371 Computing for EngineersCS1 for Engineers. Same topics as CS1301, but using MATLAB with Engineering problems in homework and examples. • CS1315 Introduction to Media Computation

14. 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 • Computing for communications, not calculation

15. 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

16. MediaComp in Undergraduate, High School, and Teacher Workshops • Introductory media computing in Python • Both majors and non-majors. • At Georgia Tech, course is 300-400 students/term, 51% female • Required in Liberal Arts, Architecture, and Management. • (Enables BS in Computation Media, 27% female) • Introduction to object-oriented programming in Java • Introduction to data structures in Java • Used at Georgia Tech, Gainesville College, Lindfield College • Introduction to programming and CS AP • Integrating Alice and Media Computation

17. Some Media Computation Examples: A Sunset Effect • How do we turn this beach scene into a sunset? • What happens at sunset? • Theory: As the sun sets, less blue and green is visible, which makes things look more red.

18. A Sunset-generation Function def makeSunset(picture): for p in getPixels(picture): value=getBlue(p) setBlue(p,value*0.7) value=getGreen(p) setGreen(p,value*0.7)

19. SlowSunset as a movie def slowsunset(directory): canvas = makePicture(getMediaPath("beach-smaller.jpg")) for frame in range(0,100): #99 frames printNow("Frame number: "+str(frame)) makeSunset(canvas) # Now, write out the frame writeFrame(frame,directory,canvas) def makeSunset(picture): for p in getPixels(picture): value=getBlue(p) setBlue(p,value*0.99) #Just 1% decrease! value=getGreen(p) setGreen(p,value*0.99)

20. SlowSunset frames

21. Example Movies

22. Background subtraction • Let’s say that you have a picture of someone, and a picture of the same place (same background) without the someone there, could you subtract out the background and leave the picture of the person? • Where the same (x,y) pixel differs in color (by some threshold value), assume it’s the person • Could you change the background? • When a pixel color differs, take the color from the new background at the same (x,y)

23. Person (Katie) and Background, and new version

24. Fading by background subtraction • Background subtraction: def swapbg(person, bg, newbg,threshold): for x in range(1,getWidth(person)): for y in range(1,getHeight(person)): personPixel = getPixel(person,x,y) bgpx = getPixel(bg,x,y) personColor= getColor(personPixel) bgColor = getColor(bgpx) if distance(personColor,bgColor) < threshold: bgcolor = getColor(getPixel(newbg,x,y)) setColor(personPixel, bgcolor) Threshold as an input. Using the frame number

25. SlowFadeout

26. Example Movies

27. Examples of Student Work Soup-Audio Collage Canon- LinkedList of (MIDI) Music

28. Examples of Teacher Work

29. A Media Computation Data Structures Course • Driving question: “How did the wildebeests stampede in The Lion King?”

30. Connecting to the WildebeestsIt’s all about data structures

31. Similar Assignments,but with Objects and Agents

32. Results: CS1315 “Media Computation”

33. 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.

34. Results: CS1371 “Engineering”

35. 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.”

36. “Did the class change how you interact with computers?” • Results from a survey a year later: • “Definitely makes me think of what is going on behind the scenes of such programs like Photoshop and Illustrator.” • 'I understand technological concepts more easily now; I am more willing and able to experience new things with computers now’ • 'I have learned more about the big picture behind computer science and programming. This has helped me to figure out how to use programs that I've never used before, troubleshoot problems on my own computer, use programs that I was already familiar with in a more sophisticated way, and given me more confidence to try to problem solve, explore, and fix my computer.’

37. The Other Results • We don’t know if they learn the same. • The challenge of comparative studies when there is no shared experience of computing. • 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”

38. 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% femaleOver 200 majors today, still about ¼ female

39. How about CS? Back to our own CS1

40. A Context for CS1 for CS majors: Robotics • Microsoft Research has funded the Institute for Personal Robotics in Education • Tucker Balch, Deepak Kumar, Doug Blank • Joint between Bryn Mawr and Georgia Tech • http://www.roboteducation.org • Goal is to develop a CS1 with robotics as the context. • Added a camera and media computation abilities

41. Robot Movies • Robots have cameras, and Myro has media computation primitives. • Wonderful project by Jay Summet: Creative and Collaborative • Robots are characters. • One robot is camera • How do you zoom?Aim and go forward! • Post-processing media computation, e.g., for eerie disappearing effects.

42. Example movie

43. 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.

44. 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)

45. 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.

46. Back to Computing Across Campus • What do we in CS get from teaching computing to the rest of campus? • Maybe make our students more competitive (via diversity and breadth)? • Maybe attract more students to the field? • 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

47. Computer Scientists andReading • 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

48. Summary • The rest of campus needs what we have to offer. • The Power of Computational Thinking • 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 how we offer intro computing to our own students. • We have found a contextualized computing approach works (for the measures we have now). • There may be benefits for CS in making more connections to the rest of campus.

49. Thank you! Mark Guzdial http://www.cc.gatech.edu/~mark.guzdial http://home.cc.gatech.edu/csl For more on Threads: http://www.cc.gatech.edu/threads For more on MediaComp approach (including papers, software, and slides and workshops): http://coweb.cc.gatech.edu/mediaComp-plan Media Computation Teachers’ Site: http://coweb.cc.gatech.edu/mediaComp-teach

50. 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 (non-college credit) workshop I have ever taken.” • Students in multimedia data structures: “Data structures is an important step. Use of media! It makes it fun.”