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Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Assistant DirectorComputer and Information Science and Engineering DirectorateNational Science Foundation,[object Object],and,[object Object],President’s Professor of Computer ScienceCarnegie Mellon University,[object Object],University of CaliforniaRiverside, CAFebruary 17, 2010,[object Object]
2,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],My Grand Vision,[object Object],Computational thinking will be a fundamental skill used by everyone in the world by the middle of the 21st Century.,[object Object],Just like reading, writing, and arithmetic.,[object Object],Incestuous: Computing and computers will enable the spread of computational thinking.,[object Object],In research: scientists, engineers, …, historians, artists,[object Object],In education: K-12 students and teachers, undergrads, …,[object Object],J.M. Wing, “Computational Thinking,” CACM Viewpoint, March 2006, pp. 33-35.,[object Object],Paper off http://www.cs.cmu.edu/~wing/ ,[object Object]
Abstractions,[object Object],Automation,[object Object],Computing is the Automation of Abstractions,[object Object],1. Machine,[object Object],2. Human,[object Object],3. Human + Machine,[object Object],4. Networks of 1, 2, or 3,[object Object],Computational Thinking focuses on the process of abstraction  - choosing the right abstractions  - operating in terms of multiple layers of abstraction simultaneously  - defining the relationships the between layers,[object Object],guided by the following concerns…,[object Object],3,[object Object],CT & TC,[object Object],Jeannette M. Wing,[object Object]
4,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Abstractions,[object Object],Automation,[object Object],Computing is the Automation of Abstractions,[object Object],1. Machine,[object Object],2. Human,[object Object],3. Human + Machine,[object Object],4. Networks of 1, 2, or 3,[object Object],Computational Thinking focuses on the process of abstraction  - choosing the right abstractions  - operating in terms of multiple layers of abstraction simultaneously  - defining the relationships the between layers,[object Object],as in Mathematics,[object Object],guided by the following concerns…,[object Object],4,[object Object],CT & TC,[object Object],Jeannette M. Wing,[object Object]
5,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Measures of a “Good” Abstraction in C.T.,[object Object],Efficiency,[object Object],How fast?,[object Object],How much space?,[object Object],How much power?,[object Object],Correctness,[object Object],Does it do the right thing?,[object Object],Does the program compute the right answer?,[object Object],Does it do anything?,[object Object],Does the program eventually produce an answer?  [Halting Problem],[object Object],-ilities,[object Object],Simplicity and elegance,[object Object],Usability,[object Object],Modifiability,[object Object],Maintainability,[object Object],Cost,[object Object],…,[object Object],as in Engineering,[object Object],NEW,[object Object]
6,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Computational Thinking, Philosophically,[object Object],Complements and combines mathematical and engineering thinking,[object Object],C.T. draws on math as its foundations,[object Object],But we are constrained by the physics of the underlying machine,[object Object],C.T. draws on engineering since our systems interact with the real world,[object Object],But we can build virtual worlds unconstrained by physical reality,[object Object],Ideas, not artifacts,[object Object],It’s not just the software and hardware that touch our daily lives, it will be the computational concepts we use to approach living.,[object Object],It’s for everyone, everywhere,[object Object]
7,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Sample Classes of Computational Abstractions,[object Object],Algorithms,[object Object],E.g., mergesort, binary search, string matching, clustering,[object Object],Data Structures,[object Object],E.g., sequences, trees, graphs, networks,[object Object],State Machines,[object Object],E.g., finite automata, Turing machines,[object Object],Languages,[object Object],E.g., regular expressions, …, VDM, Z, …, ML, Haskell, …,  Java, Perl,[object Object],Logics and semantics,[object Object],E.g., Hoare triples, temporal logic, modal logics, lambda calculus,[object Object],Heuristics,[object Object],E.g., A* (best-first graph search), caching,[object Object],Control Structures,[object Object],Parallel/sequential composition, iteration, recursion,[object Object],Communication,[object Object],E.g., synchronous/asynchronous, broadcast/P2P, RPC, shared memory/message-passing,[object Object],Architectures,[object Object],E.g., layered, hierarchical, pipeline, blackboard,  feedback loop, client-server, parallel, distributed,[object Object],…,[object Object]
8,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Examples of Computational Thinking in Other Disciplines,[object Object]
9,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],One Discipline, Many Computational Methods,[object Object]
10,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Computational Thinking in Biology,[object Object],Shotgun algorithm expedites sequencingof human genome,[object Object],DNA sequences are strings in a language,[object Object],Boolean networks approximate dynamicsof biological networks,[object Object],Cells as a self-regulatory system are like electronic circuits,[object Object],Process calculi model interactions among molecules,[object Object],Statecharts used in developmental genetics,[object Object],Protein kinetics can be modeled as computational processes,[object Object],Robot Adam discovers role of 12 genes in yeast,[object Object],PageRank algorithm inspires ecological food web,[object Object]
counterexample,[object Object],yes,[object Object],Fis falsified here.,[object Object],Model Checking Primer,[object Object],Finite State Machine model M,[object Object],Temporal LogicpropertyF,[object Object],F =AG p,[object Object],AF p, EG p, EF p,[object Object],M’s computational tree,[object Object],Model Checker,[object Object],11,[object Object],CT & TC,[object Object],Jeannette M. Wing,[object Object]
12,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Model Checking Problem,[object Object],Let M be a finite state machine.,[object Object],Let  be a specification in temporal logic.,[object Object],Find all states sofM such that:   ,[object Object],M, s ,[object Object],Efficient algorithms: [CE81, CES86, Ku94, QS81, VW94],[object Object],Efficient data structures: binary decision diagrams [Br86] ,[object Object]
13,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],1. Finite State Machine Mrepresents 3-residue protein,[object Object],1’. BDDefficiently represents M,[object Object],Energy Profile for FKBP-12, Computed via  Method,[object Object],Model Checking in Biology,[object Object],Goal: Predict Rate of Folding of Proteins,[object Object],2. Temporal Logic Formula      a. Will the protein end up in a          particular configuration?     b. Will the second residue fold          before the first one?     c. Will the protein fold within t ms?     d. What is the probability that (c)?,[object Object],e. Does the state s have k folded         residues and have energy c?,[object Object],Method easily handles proteins up to 76 residues.,[object Object],Model checking can explore,[object Object],state spaces as large as 276  1023,14 orders of magnitude greater thancomparable techniques [LJ07].,[object Object]
14,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],One Computational Method,,[object Object],Many Disciplines,[object Object],Machine Learning has transformed the field of Statistics.,[object Object]
15,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Machine Learning in the Sciences,[object Object],Medicine,[object Object], - Anti-inflammatory drugs - Chronic hepatitis - Mammograms - Renal and respiratory failure,[object Object],Meteorology,[object Object],Credit: LiveScience,[object Object],- Tornado formation,[object Object],Neurosciences,[object Object],- fMRI data analysis to understand language   via machine learning,[object Object],Astronomy,[object Object],- Brown dwarfs and fossil galaxies discovery     via machine learning, data mining, data federation- Very large multi-dimensional datasets analysis      using KD-trees,[object Object],Credit: SDSS,[object Object],Credit: Eric Nguyen, Oklahoma University,[object Object]
16,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Machine Learning Everywhere,[object Object],Supermarkets,[object Object],Credit Cards,[object Object],Wall Street,[object Object],Entertainment:Shopping, Music, Travel,[object Object],Credit: Wikipedia,[object Object],Sports,[object Object],Credit: Wikipedia,[object Object]
17,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
?,[object Object],18,[object Object],CT & TC,[object Object],Jeannette M. Wing,[object Object]
19,[object Object],CT & TC,[object Object],Jeannette M. Wing,[object Object]
20,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Question (Kearns): Can a Set of Weak Learners Create a Single Strong One?,[object Object],Answer: Yes, by Boosting Algorithms (e.g., [FS99]),[object Object]
21,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
22,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
23,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
24,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
25,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
26,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
27,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object]
28,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Computational Thinking in the Sciences and Beyond,[object Object]
29,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],- Atomistic calculations are used to explore  chemical phenomena,[object Object],[object Object],Chemistry,[object Object],Physics,[object Object],[York, Minnesota],[object Object],- Adiabatic quantum computing: How quickly is convergence?- Genetic algorithms discover laws of physics.,[object Object],CT in Other Sciences,[object Object],Credit: NASA,[object Object],Geosciences,[object Object],Credit: Oxford University,[object Object],- Abstractions for Sky, Sea, Ice, Land, Life, People, etc.         - Hierarchical, composable , modular,           traceability, allowing multiple projections           along any dimension, data element, or query,[object Object],   - Well-defined interfaces,[object Object]
30,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Mathematics,[object Object],  - 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,[object Object],Credit: Wikipedia,[object Object],Credit: Wikipedia,[object Object],Engineering (electrical, civil, mechanical, aero & astro,…),[object Object],Credit: Boeing,[object Object],- 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,[object Object],CT in Math and Engineering,[object Object]
31,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],  - Inventions discovered through automated search are patentable,[object Object],  -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,[object Object],Law,[object Object],CT for Society,[object Object],Economics,[object Object],- Automated mechanism design underlies electronic commerce,     e.g., ad placement,  on-line auctions, kidney exchange - Internet marketplace requires revisiting Nash equilibria model,[object Object], - Use intractability for voting schemes to circumvent impossibility results,[object Object],Humanities,[object Object],- Digging into Data Challenge: What could you do with a million books?          Nat’l Endowment for the Humanities (US),          JISC (UK), SSHRC (Canada)- Music, English, Art, Design, Photography, …,[object Object]
32,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Educational Implications,[object Object]
33,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Pre-K to Grey,[object Object],K-6, 7-9, 10-12,[object Object],Undergraduate courses,[object Object],Freshmen year,[object Object],“Ways to Think Like a Computer Scientist” aka Principles of Computing,[object Object],Upper-level courses,[object Object],Graduate-level courses,[object Object],Computational arts and sciences,[object Object],E.g., entertainment technology, computational linguistics, …, computational finance, …, computational biology, computational astrophysics,[object Object],Post-graduate,[object Object],Executive and continuing education, senior citizens,[object Object],Teachers, not just students,[object Object]
34,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Education Implications for K-12,[object Object],Question and Challenge for the Computing Community:,[object Object],What is an effective way of learning (teaching) computational thinking by (to) K-12?,[object Object],    - What concepts can students (educators) best learn (teach) when?,[object Object],       What is our analogy to numbers in K, algebra in 7, and calculus in 12?,[object Object],    - We uniquely also should ask how best to integrate The Computer       with teaching the concepts.,[object Object],Computer scientists are now working with educators and cognitive learning scientists toaddress these questions.,[object Object]
35,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Computational Thinking in Daily Life,[object Object]
36,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],straws,stirrers,milk,[object Object],   coffee   ,[object Object],   soda   ,[object Object],cups,[object Object],sugar,creamers,[object Object],lids,[object Object],napkins,[object Object],Getting Morning Coffee at the Cafeteria,[object Object]
37,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Getting Morning Coffee at the Cafeteria,[object Object],straws,stirrers,milk,[object Object],   coffee   ,[object Object],   soda   ,[object Object],cups,[object Object],sugar,creamers,[object Object],lids,[object Object],napkins,[object Object],Especially Inefficient With Two or More Persons…,[object Object]
38,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Better: Think Computationally—Pipelining!,[object Object],straws,stirrers,milk,[object Object],   coffee   ,[object Object],   soda   ,[object Object],cups,[object Object],sugar,creamers,[object Object],lids,[object Object],napkins,[object Object]
Computational Thinking at NSF,[object Object]
40,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],CDI: Cyber-Enabled Discovery and Innovation,[object Object],Paradigm shift,[object Object],Not just computing’s metal tools (transistors and wires) but also our mental tools (abstractions and methods),[object Object],It’s about partnerships and transformative research.,[object Object],To innovate in/innovatively use computational thinking; and,[object Object],To advance more than one science/engineering discipline.,[object Object],Investments by all directorates and offices,[object Object],FY08: $48M, 1800 Letters of Intent, 1300 Preliminary Proposals, 200 Full Proposals, 36 Awards,[object Object],FY09: $63M+, 830 Prelimary Proposals, 283 Full Proposals, 53+ Awards,[object Object],Computational Thinking for Science and Engineering,[object Object]
41,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Range of Disciplines in CDI Awards,[object Object],Aerospace engineering,[object Object],Astrophysics and cosmology,[object Object],Atmospheric sciences,[object Object],Biochemistry,[object Object],Biomaterials,[object Object],Biophysics,[object Object],Chemical engineering,[object Object],Civil engineering,[object Object],Communications science and engineering,[object Object],Computer science,[object Object],Cosmology,[object Object],Ecosystems,[object Object],Genomics,[object Object],Geosciences,[object Object],Linguistics,[object Object],Materials engineering,[object Object],Mathematics,[object Object],Mechanical engineering,[object Object],Molecular biology,[object Object],Nanocomputing,[object Object],Neuroscience,[object Object],Proteomics,[object Object],Robotics,[object Object],Social sciences,[object Object],Statistics,[object Object],Statistical physics,[object Object],Sustainability,[object Object],…,[object Object],… advances via Computational Thinking,[object Object]
42,[object Object],Computational Thinking,[object Object],Jeannette M. Wing,[object Object],Range of Societal Issues Addressed,[object Object],Cancer therapy,[object Object],Climate change,[object Object],Environment,[object Object],Sustainability,[object Object],Visually impaired,[object Object],Water,[object Object]
ACM-Ed,[object Object],CRA-E,[object Object],CSTA,[object Object],NSF,[object Object],College Board,[object Object],Rebooting,[object Object],National Academies,[object Object],workshops,[object Object],K-12,[object Object],CPATH,[object Object],BPC,[object Object],AP,[object Object],C.T. in Education: National Efforts,[object Object],ComputingCommunity,[object Object],Computational     Thinking,[object Object],CSTB “CT for Everyone” Steering Committee,[object Object],[object Object]
 Al Aho, Columbia
 Brian Blake, Georgetown
 Bob Constable, Cornell
 Yasmin Kafai, U Penn
 Janet Kolodner, Georgia Tech
 Larry Snyder, U Washington
 Uri Wilensky, Northwestern43,[object Object],CT & TC,[object Object],Jeannette M. Wing,[object Object]

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  • 44. Al Aho, Columbia
  • 45. Brian Blake, Georgetown
  • 48. Janet Kolodner, Georgia Tech
  • 49. Larry Snyder, U Washington
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  • 58. Except where otherwise indicated, permission is granted to copy, distribute, and/or modify all images in this document under the terms of the GNU Free Documentation license, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled “GNU Free Documentation license” (http://commons.wikimedia.org/wiki/Commons:GNU_Free_Documentation_License)
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