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
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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
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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/
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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
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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)
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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
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Research Implications
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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
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CT in Other Sciences, Math, and Engineering
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
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CT in Other Sciences, Math, and Engineering
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
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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
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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
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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
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Educational Implications
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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
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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.
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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, …).
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External Community Response
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External Community …
• Outside of CMU• Outside of Computer Science• Outside of Science and Engineering• Outside of US
• Impact on research and education through NSF
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Research Impact
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“Computational Thinking,” Andrew Hebert (Director, MSR/Cambridge), p. 20, 2006.
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Volume 440 Number 7083 pp 383-580,March 23, 2006
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Spearheaded by Alan Bundy
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Also, report by Conrad Taylor on my talk atGrand Challenges in Computing Conference,British Computer Society, London, March 2008
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Reach Through NSF
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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
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CDI Response
• 1800 Letters of Intent, 1300 Preliminary Proposals, 200 Final Proposals, 36 Awards
• FY08: ~$50M invested by all directorates and offices
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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
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Range of Societal Issues Addressed
• Cancer therapy• Climate change• Environment• Visually impaired• Water
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Educational Impact
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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, …
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Reach Through NSF
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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
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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
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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.)
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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
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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
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Two and a Half Years Later: Research
Computational Thinking
Computational Thinking
ComputingCommunity
NSF
CMU
Microsoft
Center for CT
computer science, arts, humanities, …
CDI
all sciences and engineering
NEH,ILMS
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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
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Two and a Half Years Later: Education
NSF
ComputingCommunity
Computational Thinking
Computational Thinking
Rebooting
APCPATHBPCK-12
National Academies
workshops
ACM-EdCRA-E
CSTA
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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
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Bigger Picture: Societal and Political Issues
• Climate Change• Energy• Environment• Economics• Human Behavior• Sustainability• Healthcare• National security• …
Competitiveness, Innovation, Leadership
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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
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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?
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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?
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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.
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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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