Computational Thinking for Everyone Jeannette M. Wing President’s Professor of Computer Science...

Computational Thinking for Everyone

Jeannette M. WingPresident’s Professor of Computer Science

Carnegie Mellon Universityand

Assistant DirectorComputer and Information Science and Engineering Directorate

National Science Foundation

2008 Jeannette M. Wing

2CT for Everyone Jeannette M. Wing

Outline

• Computational Thinking• A Vision for our Field• The Two A’s to CT

• Research and Education Implications

Two and a Half Years Later…

• External Response and Impact

• Reality Check


My Grand Vision for the Field

• Computational thinking will be a fundamental skill used by everyone in the world by the middle of the 21st Century.

– Just like reading, writing, and arithmetic.– Imagine every child knowing how to think like a computer scientist!

– Incestuous: Computing and computers will enable the spread of computational thinking.

– In research: scientists, engineers, …, historians, artists

– In education: K-12 students and teachers, undergrads, …J.M. Wing, “Computational Thinking,” CACM Viewpoint, March 2006, pp. 33-35.

http://www.cs.cmu.edu/~wing/

http://www.cs.cmu.edu/~wing


The First A to Computational Thinking

• Abstractions are our “mental” tools

• The abstraction process includes– Choosing the right abstractions– Operating simultaneously at multiple layers of abstraction

– Defining the relationships the between layers


The Second A to Computational Thinking

• The power of our “mental” tools is amplified by our “metal” tools.

• Automation is mechanizing our abstractions, abstraction layers, and their relationships– Mechanization is possible due to precise and exacting notations and models

– There is some “computer” below (human or machine, virtual or physical)


Two A’s to C.T. Combined

• Computing is the automation of our abstractions– They give us the audacity and ability to scale.

• Computational thinking– choosing the right abstractions, etc.– choosing the right “computer” for the task


Research Implications


CT in Other Sciences, Math, and Engineering

Biology - Shotgun algorithm expedites sequencing of human genome - DNA sequences are strings in a language - Protein structures can be modeled as knots - Protein kinetics can be modeled as computational processes - Cells as a self-regulatory system are like electronic circuits

Credit: Wikipedia

Brain Science - Modeling the brain as a computer - Vision as a feedback loop - Analyzing fMRI data with machine learning

Credit: LiveScience



Geology- Modeling the earth’s surface to the sun, from the inner core to the surface- Abstraction boundaries and hierarchies of complexity model the earth and our atmosphere

Credit: NASACredit: University of Minnesota

Chemistry [Madden, Fellow of Royal Society of Edinburgh]

- Atomistic calculations are used to explore chemical phenomena- Optimization and searching algorithms identify best chemicals for improving reaction conditions to improve yields



Mathematics - Discovering E8 Lie Group: 18 mathematicians, 4 years and 77 hours of supercomputer time (200 billion numbers). Profound implications for physics (string theory) - Four-color theorem proof

Credit: Wikipedia

Credit: Wikipedia

Astronomy - Sloan Digital Sky Server brings a telescope to every child - KD-trees help astronomers analyze very large multi-dimensional datasets

Credit: SDSS

Engineering (electrical, civil, mechanical, aero & astro,…) - Calculating higher order terms implies more precision, which implies reducing weight, waste, costs in fabrication- Boeing 777 tested via computer simulation alone, not in a wind tunnel

Credit: Boeing


CT for Society

Economics - Automated mechanism design underlies electronic commerce, e.g., ad placement, on-line auctions, kidney exchange - Internet marketplace requires revisiting Nash equilibria modelSocial Sciences

- Social networks explain phenomena such as MySpace, YouTube - Statistical machine learning is used for recommendation and reputation services, e.g., Netflix, affinity card


CT for Society

Law - Stanford CL approaches include AI, temporal logic, state machines, process algebras, petri nets - POIROT Project on fraud investigation is creating a detailed ontology of European law - Sherlock Project on crime scene investigation

Medicine - Robotic surgery - Electronic health records require privacy technologies - Scientific visualization enables virtual colonoscopy

Credit: University of Utah

Humanities - What do you do with a million books? Nat’l Endowment for the Humanities Inst of Museum and Library Services


CT for Society

Entertainment- Games- Movies - Dreamworks uses HP data center to renderShrek and Madagascar - Lucas Films uses 2000-node data center to produce Pirates of the Caribbean.

Credit: Dreamworks SKG

Credit: Carnegie Mellon University

Sports - Lance Armstrong’s cycling computer tracks man and machine statistics - Synergy Sports analyzes digital videos NBA games

Credit: Wikipedia

Arts - Art (e.g., Robotticelli) - Drama - Music - Photography

Credit: Christian Moeller


Educational Implications


Pre-K to Grey

• K-6, 7-9, 10-12• Undergraduate courses

– Freshmen year• “Ways to Think Like a Computer Scientist” aka Principles of Computing

– Upper-level courses

• Graduate-level courses– Computational arts and sciences

• E.g., entertainment technology, computational linguistics, …, computational finance, …, computational biology, computational astrophysics

• Post-graduate– Executive and continuing education, senior citizens

– Teachers, not just students


Question and Challenge to Community

What are effective ways of learning (teaching)computational thinking by (to) children?

- What concepts can students best learn when? What should we teach when? What is our analogy to numbers in K, algebra in 7, and calculus in 12?

- We uniquely also should ask how best to integrate The Computer with learning and teaching the concepts.


Simple Daily Examples• Looking up a name in an alphabetically sorted list

– Linear: start at the top– Binary search: start in the middle

• Standing in line at a bank, supermarket, customs & immigration– Performance analysis of task scheduling

• Putting things in your child’s knapsack for the day– Pre-fetching and caching

• Taking your kids to soccer, gymnastics, and swim practice– Traveling salesman (with more constraints)

• Cooking a gourmet meal– Parallel processing: You don’t want the meat to get cold while

you’re cooking the vegetables.• Cleaning out your garage

– Keeping only what you need vs. throwing out stuff when you run out of space.

• Storing away your child’s Lego pieces scattered on the LR floor– Using hashing (e.g., by shape, by color)

• Doing laundry, getting food at a buffet– Pipelining the wash, dry, and iron stages; plates, salad, entrée,

dessert stations• Even in grade school, we learn algorithms (long division,

factoring, GCD, …) and abstract data types (sets, tables, …).


External Community Response


External Community …

• Outside of CMU• Outside of Computer Science• Outside of Science and Engineering• Outside of US

• Impact on research and education through NSF


Research Impact


“Computational Thinking,” Andrew Hebert (Director, MSR/Cambridge), p. 20, 2006.


Volume 440 Number 7083 pp 383-580,March 23, 2006


Spearheaded by Alan Bundy


Also, report by Conrad Taylor on my talk atGrand Challenges in Computing Conference,British Computer Society, London, March 2008


Reach Through NSF


CDI: Cyber-Enabled Discovery and Innovation

• Paradigm shift– Not just our metal tools (transistors and wires)

but also our mental tools (abstractions and methods)

• It’s about partnerships and transformative research.– To innovate in/innovatively use computational

thinking; and– To advance more than one science/engineering

discipline.

• Fortuitous timing for me …

Computational Thinking for Science and Engineering


CDI Response

• 1800 Letters of Intent, 1300 Preliminary Proposals, 200 Final Proposals, 36 Awards

• FY08: ~$50M invested by all directorates and offices


Range of Disciplines in CDI Awards• Aerospace engineering• Atmospheric sciences• Biochemistry• Biophysics• Chemical engineering• Communications science and engineering• Computer science• Geosciences• Linguistics• Materials engineering• Mathematics• Mechanical engineering• Molecular biology• Nanocomputing• Neuroscience• Robotics• Social sciences• Statistical physics

… advances via Computational Thinking


Range of Societal Issues Addressed

• Cancer therapy• Climate change• Environment• Visually impaired• Water


Educational Impact


Colleges and Universities are Revisiting Curricula

• Carnegie Mellon: Tom Cortina’s 15-105• MIT: John Guttag’s 6.00 (for freshmen)• Georgia Tech:

– UG: “Threads”, Mark Guzdial, “Learning Computing with Robots,” Tucker Balch and Deepak Kumar (Bryn Mawr)

– Grad: Alexander Gray and Nick Feamster

• Columbia: Al Aho• Princeton: PICASso, for non-CS graduate students

• …

• Villanova, Haverford, Bryn Mawr, Georgetown, …• U Wisconsin-La Crosse, …


Reach Through NSF


CISE

• CPATH– Revisiting undergrad curricula– Enlarge scope to include outreach to K-12

• Broadening Participation in Computing– Women, underrepresented minorities, people with disabilities

– Alliances and demo projects


CPATH Awards Specific to CT

• Brown• De Paul• Georgia State• North Carolina Agricultural and Technical State

University• Middle Tennessee State University• Penn State University• Towson University• University of Illinois, Urbana-Champaign• University of Nebraska• University of Texas, El Paso• Utah State• Villanova• Virginia Tech• Washington State


Broadening Participation

• AP Revision– Academic Advisory group includes NSF, ACM, CSTA, university reps (e.g., Cortina), and high school teachers

• New Image for Computing– Working with Image of Computing and WGBH (Boston)

• Alliances– e.g., ARTSI (HBCU/R1 Robotics, Touretzky, et al.)


Beyond CISE

Challenge to Community: What is an effective way of teaching (learning) computational thinking to (by) K-12?

• Computational Thinking for Children– National Academies Computer Science and Telecommunications Board (CSTB): Workshops on CT for Everyone. Collaborating with Board on Science Education.

• Cyber-enabled Learning– Education and Human Resources (EHR) Directorate, Office of Cyberinfrastructure (OCI), Social, Behavioral, and Economic Sciences (SBE), and CISE


Other Educational and Outreach Activities

• Peter Denning’s “Rebooting Computing Summit”, Jan 2009

• Andy van Dam is CRA-E “Education Czar”• ACM Ed Council• CS4HS: Lenore Blum’s vision: “CS4HS in every state!”

• Women@SCS Roadshow• Image of Computing Task Force: Jill Ross, Rick Rashid, Jim Foley


Two and a Half Years Later: Research

Computational Thinking


ComputingCommunity

NSF

CMU

Microsoft

Center for CT

computer science, arts, humanities, …

CDI

all sciences and engineering

NEH,ILMS


Research Challenges and Opportunities

• CT for other sciences and engineering and beyond– It’s inevitable– They need us, they want us

• It’s about abstractions and symbolic “calculations” not just number-crunching


Two and a Half Years Later: Education

NSF

ComputingCommunity



Rebooting

APCPATHBPCK-12

National Academies

workshops

ACM-EdCRA-E

CSTA


Educational Challenges and Opportunities

• Science, Technology, Engineering, and Mathematics (STEM) Education continues to be a huge challenge

• ~15,000 school districts in the US• HS science and math teachers• Public perception of STEM disciplines


Bigger Picture: Societal and Political Issues

• Climate Change• Energy• Environment• Economics• Human Behavior• Sustainability• Healthcare• National security• …

Competitiveness, Innovation, Leadership


Broad Charge To You

• Help the community define a strategy for determining what, if anything, of computational thinking makes sense to teach at the K-12 level.

• where– community = computer scientists, educators, learning/cognitive scientists

– what, if anything, of computational thinking = concepts/principles/skills underlying computing

– K-12 = especially early grades


Questions

• What are the fundamental concepts of CT? Elemental?

• What would be an effective ordering of these concepts?

• How best should we integrate The Computer with teaching the concepts?


Long-term view

• Analogy– What physics did for itself decades ago.– What math did and continues to do periodically.

• It’s NOT just curriculum design.– How do children learn what when?


Short-term agenda (suggestion)

• Workshop 1– Identify

concepts/principles/skills

• Community input

• Workshop 2– Propose one or more

models of “sequencing” the concepts

– Propose a strategy for incorporating it in an early grade or K-12 curriculm.

– Next steps?

• In parallel, work with or track other efforts and organizations.


Thanks for Helping to Spread the Word!

Make computational thinking commonplace!

To fellow faculty, students, researchers, administrators, teachers, parents,

principals, guidance counselors, school boards, teachers’ unions,

congressmen, policy makers, …

Thank you!

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