Computer Science Education 2.0

© 2005 SRI International Center for Technology in Learning

Computer Science Education 2.0

Chris DiGiano & Marie BienkowskiCenter for Technology in

LearningSRI International

12 October 2006

2© 2006 SRI International Center for Technology in Learning

Computer Science in Crisis?

• Students intending to major in CS between 2000 and 2004 dropped by 70%– Women’s interest in CS at its lowest point since 1971 when data was first collected

• Mis-Perception of job off-shoring• Dot-com bust

– Can no longer “…write a bad idea on the back of a napkin and retire at 23”

- Eric Roberts


Root Causes

Well known educational problems • Lack of role models • Too abstract• Not personally meaningful

Other issues• Limited impact


Louis PasteurLouis Pasteur

ThomasEdison

ThomasEdison

Niels BohrNiels Bohr

AudubonSociety

AudubonSociety

Quest for fundamental

understanding?

Yes

No

YesNo

Considerations of use?

adapted from "Pasteur's Quadrant", Donald E. Stokes, Brookings Press, 1997

Pasteur’s Quadrant

(adapted from Pasteur’s Quadrant: Basic Science and Technological Innovation, Stokes 1997)

Use-inspired basic research


DesignDesign

Prototyping,“Egocoding”Prototyping,“Egocoding”

Algorithms,LanguagesAlgorithms,Languages

ProgrammingContests

ProgrammingContests


understanding?generality?

Yes

No

YesNo


Google’s Quadrant in CS



DesignDesign

Prototyping,“Egocoding”Prototyping,“Egocoding”

Algorithms,LanguagesAlgorithms,Languages

ProgrammingContests

ProgrammingContests


understanding?generality?

Yes

No

YesNo


Google’s Quadrant in CS


Too abstract

Not personally meaningful

Limited impact


Focusing on Design in CSE

• Early Design• Scaffolded Design• Professional Design• Design as Consulting


Early Design: Build-IT

After school and summer youth-based curriculum for low-income middle school girls (grades 6-8) to develop IT fluency, interest in mathematics, and knowledge of IT careers.

• $900K NSF Grant• Partners: Girls Inc.

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Girls create their own theme-based, chat-enhanced web sites


Results & CSE Implications

• “I was thinking about being a teacher… Now I’m not so sure.”

• Positive, personal experiences may help students get through non-Google quadrant “gatekeeper” CS courses in college


“Scaffolded” Design: Group Scribbles

• Part of $1.2M NSF Grant (“Tuplespaces”)• Partners: Virginia Tech, Christopher Newport University


Results & CSE Implications

• High-quality artifacts without custom coding

• Helping college students think about distributed control

• Code-free CSE: Toolkits can help students think about Big Ideas in computer science without explicit programming

• See– Brecht, John et al. (2006) Coordinating networked learning

activities with a general purpose interface. Paper presented at mLearn 2006, the 5th World Conference on Mobile Learning.


Professional Design: TRAILS

• Training and Resources for Assembling Interactive Learning Systems

• $3.2M NSF Grant• Partners: Stanford, Penn State, Drexel, Univ. of Colorado at Boulder




Results

• Approximately 200 students at 4 university sites

• 50 major projects generated, all with feedback with educational “clients”

“Working across disciplines, I got to experience a part of what real educational software designers do... In the process, I got to learn a ton about real-life software design, work with teachers and kids on building a great product, and meet lots of cool people to bounce ideas off of and collaborate with.” — Ankur Dalal, Computer Science, Stanford 2004


Students Will Build Amazing Things in One Semester!

• Cannot stop them from creating working artifacts

• Students don’t want to build on others’ design

• But they do like to show off




Novice / Expert Design Thinking

N1: “Suggest thinking about time constraints, level of the students, costs and the overall learning good desired or how much the level of student education must increase.”N2: “Have two – prototypes; test within group; (If needed) test with other colleagues; (If needed) test with students.”

E1: …”I'd ask questions like: What were the features/variables of such studies? Under different conditions (different teaching styles, different visualization tools, different types of data sets or contexts, etc.), might [we see] different results?…”

N3: “Go to schools and observe the classrooms. Take a survey regarding teachers needs/desires.”N4: “Conduct a survey to get ideas what kind of technology is available and what level of technology knowledge do teachers have.”

E2: “…Principals and district administrators could also provide good feedback (especially since they control budgets and curricula). Check the literature or other reports for reviews on available applications, their strengths & weaknesses. Study the existing curricula and standards. Whatever we develop has to align with them.”


Novice / Expert Design Thinking

N1: “Suggest thinking about time constraints, level of the students, costs and the overall learning good desired or how much the level of student education must increase.”N2: “Have two – prototypes; test within group; (If needed) test with other colleagues; (If needed) test with students.”

E1: “…I'd ask questions like: What were the features/variables of such studies? Under different conditions (different teaching styles, different visualization tools, different types of data sets or contexts, etc.), might [we see] different results?…”

N3: “Go to schools and observe the classrooms. Take a survey regarding teachers needs/desires.”N4: “Conduct a survey to get ideas what kind of technology is available and what level of technology knowledge do teachers have.”

E2: “…Principals and district administrators could also provide good feedback (especially since they control budgets and curricula). Check the literature or other reports for reviews on available applications, their strengths & weaknesses. Study the existing curricula and standards. Whatever we develop has to align with them.”

“Satisficing”Solving

ScholarshipSelf-containment


CSE Implications

• Challenge is overcoming students’ school-survival strategies– Students are used to “Doing School” (Denise Pope)

– Design is about exploring a trade-off space• There is no “right answer”

– Good design is research-based• Need to look beyond ready-at-hand resources

• See our book on Educating Learning Technology Designers to be published by Springer in 2007


Design as Consulting: Cybercollaboration

• Cybercollaboration between Scientists and Software Developers

• $250K NSF Grant• Partners: Univ. of Colorado at Boulder,

Agentsheets, Inc.

“Science will continue to surprise us with what it discovers and creates; then it will astound us by devising new methods to surprises us. At the core of science’s self-modification is technology. New tools enable new structures of knowledge and new ways of discovery. The achievement of science is to know new things; the evolution of science is to know them in new ways.”

—Kevin Kelly, Speculations on The Future of Science


Collaborative Evolution of Scientific Tools

Scientist specifies

Developer interprets

Scientist clarifies

Developer formalizes

Scientist confirms

Developer builds

Scientist verifies

Developer inquires


Research Platform: Computational Wikis

• Your browser is your IDE• Procedures are edited and run thru the Web

• Everything is inspectable and editable• Everything can be commented on, tagged• An example is the Web service oriented WubHub from SRI’s Cheyer and Levy


Participatory Interactive Computation thru the Internet (PIKI)



Location bar is your command line

PIKI emphasizes data first, procedures later

Everything is commentable


Incremental Formalization


Manual Unit Tests

Manual Unit Test #7The result of applying the method align() on parameters

“GAGGTAGTAA, GAGATAGTAA” is 87and on“GAGGTAGTAA, GAGGTAGTAA” is 95Is 87 slightly less than 95?

Please manually verify this assertion

PASS FAIL SKIP


CSE Implications

• The computer science of requirements gathering

• Opportunities for informal participants and dilatants

• Service orientation means more human interaction but less control

• SeeDiGiano, C., Kireyev, K., Repenning, A. Evolving Tools Organically With Computational Wikis. Short paper presented at Computer Support for Collaborative Work (CSCW) 2006.


Programs in Academia

• Connect directly to industry jobs (CMU-West)

• Entice students with new content: Introduction to Media Computation– Computing education must be relevant, creative, social, and results-oriented

• Start early (UCSC+ETR Associates): project-based, pair programming for middle school girls


How should high tech industries respond to the crisis?

• Need to go beyond the classic models– Internships– Cheap tools– Projects for capstone courses– Supporting summer camps, after school programs

• Not systematic• SRI Workshop on Innovative Outreach in Industry, December 7


One radical role for us to play:Educational “Labeling”

• Embedding informal learning opportunities into technology products

• What if kids could learn about their iPod while listening to music? – How it works– The kinds of teams involved in the design

• Behind the Scenes extras on a DVD can inspire new movie makers. Why not inspire new technologists?


Educational “Labeling”

• Key is connecting these informal experiences with students lives in and out of school

• See– DiGiano, C., Kahn, K., Cypher, A., & Smith, D. C.

(2001). Integrating learning supports into the design of visual programming systems. Journal of Visual Languages and Computing, 12, 501-524.


How Can We Work Together Revitalize CS?

Documents

Computer Science Education 2.0