Computational Thinking Across the Curriculum:
A Conceptual Framework
Ljubomir Perkovi´c and Amber Settle
College of Computing and Digital Media
张九龄 望月怀远DePaul University
December18,2009
1Introduction
The development of computer technologies and computer science has been largely motivated by a desire to support,extend and amplify the human intellect.Thefirst general purpo computer,ENIAC,was built in1946to calculate artilleryfiring tables to support the task of artillery crews.At SRI in the mid-1960s,Doug Engelbart,in a project aptly entitled “Augmenting Human Intellect:A Conceptual Framework”[7],invented the mou,the GUI (Graphic Ur Interface),HTML),networked computers,and collaborative software tools such as tele-and
video-conferencing.Today,the Internet,the WWW,a myriad of computer applications,and computational concepts and techniques are available for the purpo of augmenting a person’s productivity,and more,in practically all human endeavors. In order to make an effective u of computer applications and techniques in his/herfield,a person needs to have certain skills.One skill is the ability to u basic computer applications such as an editor and a web orfile-system browr;this skill is often described as computer literacy.Another skill is a high level understanding of the workings of a computer system, often defined as computerfluency.While computer literacy andfluency are certainly necessary, neither is sufficient for fully realizing the potential that computing can have in augmenting a person’s productivity in theirfield.The third,critical,skill t is the intellectual and reasoning skills that a professional needs to master in order to apply computational techniques or computer applications to the problems and projects in theirfield,whether thefield is in the arts,sciences,humanities,or social sciences.
This third skill was given the name computational thinking in a recent2006CACM article by Jeannette Wing[16].Computational thinking is not new,however.Many of its elements are as old as mathematics Euclid’s500B.C Greatest Common Divisor algorithm).故弄玄虚英语
Computational thinking has beenfleshed out and ud by computer scientists in the con-text of comp
uter application development for decades.Computational thinking has also been applied tofields other than computer science for years.For example,computer scientists, psychologists,sociologists,anthropologists,and biologists have all contributed to applying computational concepts and process to thefield of cognitive science[9].The application of computational thinking within computer science and relatedfields has been implicit,becau it is the natural approach to problem solving in thefield.The application of computa-tional thinking to otherfields has also usually been implicit,sometimes without an explicit recognition of the reasoning skills involved.What is different about the recent attention on computational thinking is the emphasis on explicitly defining what it is and explicitly using it to gain new insights into problems infields outside of computer science.As Wing argues in her minal article,“the ideas of abstraction,layering of abstractions,and automation, to name a few,are fundamental computer science concepts that have already yielded new insights in the natural sciences and hard social sciences such as economics”[16].She argues that computational thinking is an emerging basic skill that should become an integral part of education:
“Computational thinking is a fundamental skill for everyone,not just for computer
scientists.To reading,writing,and arithmetic,we should add computational
thinking to every child’s analytical ability.”
conquently造句In this project we are developing a framework for implementing Wing’s vision in the context of undergraduate education.More specifically,we focus on using liberal studies cours–part of the education of the vast majority of undergraduates–as a vehicle for the teaching of computational thinking.In order to achieve this,a broad connsus among faculty from diver areas must be reached.In this project we worked toward achieving this connsus by developing a framework that faculty without formal training in information technology can u to understand and integrate computational thinking into their liberal studies cours.
2A practical definition of computational thinking
Since Wing’s article many,including Wing,have attempted to pin down a definition of com-putational thinking.Wing us many examples from computer science and“hard sciences”to define the term in her article.Unfortunately,she does not give examples of computational thinking outside the“hard sciences”.Wing’s article is also not ideal for explaining computa-tional thinking to professionals outside of computing.Part of the contribution of our project is to uncover examples of computational thinking more broadly and to explain computational thinking to faculty in all academic disciplines.
iyingOne way to decide whether some analytical process is computational thinking is if it is–or can be–described using computational thinking keywords and whether it can be categorized
as employing a fundamental“computing principle”.Using terminology defined in Appendix 8.1.2,we define the computing principles and keywords we will u.
2.1Principles of computing and keywords
Computation is a broad term that encompass different tasks,concepts and techniques.Sim-ilarly,computational thinking involves a broad t of approaches and skills.In this project wefind it uful to define different categories of computational thinking.Using the cat-egories we can understand computational thinking by distinguishing differences andfinding similarities between specific examples in differentfields.
In order to understand and organize computational thinking,we will u the categories de-fined by Denning in his“Great Principles of Computing”project[5].The goal of Denning’s project is to articulate the fundamental principles of computing.Of particular interest to us is one of Denning’s motivations:“To establish a new relationship with people from otherfields by offering computing principles in a language that shows them how to map the principles into their ownfields.”He claims th
at the“principles of computing can be organized into ven categories,each emphasizing a unique perspective on computation.”The Great Prin-ciples of Computing,according to Denning,are:computation,communication,coordination, recollection,automation,evaluation,and design.
The ven“principles”form a foundation that is uful to recognize,organize,and categorize instances of computational thinking and build a framework that can translate computational thinking to contexts outside of computer science.The categories should be en as a starting point,subject to modification as necessary.For example,abstraction is viewed by Denning as belonging to the design principle,when it could be argued that abstraction is a principle on its own.Below is our definition of each principle.Note that the definitions are somewhat different from Denning’s becau we are defining them in a context larger than computer science.For each principle,we also define a list of keywords typically ud when expressing concepts or process that the principle embodies.
•Computation is the execution of an algorithm,a process that starts from an initial state containing the algorithm and input data,and goes through a quence of intermediate states until afinal,goal state is reached.
Keywords:state and state transitions,algorithm,program,exhaustive arch,backtrack-ing,recursion and iteration,decision tree,randomization,problem complexity,com-putability.
•Communication is the transmission of information from one process or object to an-other.
Keywords:information and its reprentations,messages,nder/receiver,communica-tion protocol,message compression,message encryption,error correction,communica-tion channel,encoder/decoder,noi,authentication.
•Coordination is control(through communication,for example)of the timing of com-putation at participating process in order to achieve a certain goal.
Keywords:interacting process/agents,inter-process protocols including communica-tion protocols,synchronization,events and event handling,flow and sharing dependen-cies,concurrency.
•Recollection is the encoding and organization of data in ways to make it efficient to arch and perform other operations.
Keywords:storage media,data hierarchy and organization,data manipulations including data inrtion/query/removal and their efficiencies,data locality and caching,virtual reprentations,namin
g system,relative and absolute references.•Automation is the mapping of computation to physical systems that perform them.i potato you为什么是我喜欢你的意思
Keywords:mapping of algorithm to physical computing object,mechanization,applies to repetitive process and provides error-free,consistent,fast,cost-efficient executions.•Evaluation is the statistical,numerical,or experimental analysis of data.
Keywords:visualization,data analysis,statistics,data mining,simulation,recommender system,computational experiment.
•Design is the organization(using abstraction,modularization,aggregation,decompo-sition)of a system,process,object,etc.
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Keywords:abstraction,layers of abstraction,modeling,modularity,information hiding, class,architecture,aggregation,pattern,underlying structure.
2.2What benefits does computational thinking bring?
When reaching out to people who do not work in the area of computing,it is important to emphasize the possible benefits of applying computational thinking.There is a tendency to be(justifiably)skeptica
l of applying new approaches,particularly when existing approaches have yielded satisfactory results and when the new approaches come from an area outside of one’s experti.
The impact of computing in the sciences has been recognized for a while now.Physics Nobel Laureate Ken Wilson recognized the role of computing in his work in Nobel lecture[15]he gave in1982.Computing and computational thinking have been at the core of recent advances in molecular biology.Today complex physical process,such as the behavior of aflock of birds[2],are often best understood as computational process that are then amenable to analysis using algorithm and computational complexity tools.
Computational thinking has permeated thefield of economics from computationalfinance to electronic trading.With more and more archival documents moving into databas,it is
changing how social scientists rearch.Musicians and many artists have embraced computing as a way to enhance their creativity and productivity.
Overall,computational thinking:
1.Offers new ways of eing physical,social,or other phenomena.
2.Prents new ways to solve problems[14].
google英文3.Emphasizes creating knowledge rather than using information[14].
4.Enhances creativity and innovation.
We illustrate the benefits of computational thinking through veral examples.
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2.2.1New views of physical,social,or other phenomenamba英语
The Human Genome Project:Interpreting DNA strands as data or code is the classic example of computational thinking that led to a revolution in molecular biology.Abstracting the complexity of organic chemistry to linear strings of4characters allowed rearchers to view DNA as the encoding of information.DNA strands encode instructions to be ud in the development of the organism and this encoding is an example of data organization(or recollection).Genetic mutations can be viewed as randomized computation and the cellular growth and interactions between cells may be viewed using the ideas of coordination and communication.By taking this new view of DNA,rearchers have been able make dramatic advances in the area of molecular biology,such as the completion of the Human Genome Project in which the all the genes in human DNA were identified,the quences
making up human DNA were determined,and tools for analyzing the information were developed[10]. The evolution of the theory of evolution:Few people outside of the sciences understand that scientific discovery is often a distinctly non-linear process,where early ideas may be dis-carded or revid when new information is examined,understood,and integrated.Conveying this process to people who are not involved in scientific discovery can be difficult at best,yet it is one of the things that makes science appealing and interesting as afield.One of the most fascinating examples of this process can be en in“On The Origin of Species”by Charles Darwin.Over the cour of his lifetime,Darwin wrote six versions of the book,adding40,000 words between thefirst and sixth editions.A project by Fry[8]examines the differences between the editions,tracking the changes in text in a visual way enabling a viewer to watch the revision and expansion of Darwin’s minal work.This is a clever u of visualization that produces new understanding about the development of an important scientific theory.
2.2.2New approaches to problem solving
Origami structure:Origami,the Japane art of paper folding,is something that has
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