Computational Thinking - Учебное пособие

МОСКОВСКИЙ ГОСУДАРСТВЕННЫЙУНИВЕРСИТЕТимени М.В. ЛОМОНОСОВАФакультет вычислительной математики и кибернетикиCOMPUTATIONAL THINKING____________________________________КОМПЬЮТЕРНОЕ МЫШЛЕНИЕдля студентов старших курсов и аспирантовАвторы составители:Кашелкина О.А., Круглова М.А., Макарова А.А.,Саратовская Л.Б.Под редакцией Кругловой М.А.

и Саратовской Л.Б.Учебное пособиеМОСКВА - 2014Авторы-составители: Кашелкина О.А., Круглова М.А.,Макарова А.А., Саратовская Л.Б.Под редакцией Кругловой М.А. и Саратовской Л.Б.Рецензенты: к.ф.н. Краснова Л.Н., к.к.н. Беликова Е.К.Computational Thinking: Учебное пособие на английскомязыке/ Авт.-сост.: Кашелкина О.А., Круглова М.А., МакароваА.А., Саратовская Л.Б. Под ред.

Кругловой М.А. ИСаратовской Л.Б. - М.: АРГАМАК-МЕДИА, 2014. - 120 с.Данное учебное пособие предназначено для студентов направлений«Прикладная информатика» и «Информационные технологии»факультета ВМК МГУ имени М.В. Ломоносова, аспирантов иучащихся магистратуры.Учебно-методическое изданиеКОМПЬЮТЕРНОЕ МЫШЛЕНИЕдля студентов старших курсов и аспирантовФакультет ВМК МГУимени М.В. Ломоносова, 2014Кашелкина О.А., Круглова М.А.,Макарова А.А., Саратовская Л.Б.,составление,2014Круглова М.А., Саратовская Л.Б.,редакция, 2014ПредисловиеОвладение языковой и коммуникативной компетенциямиявляется неотделимой составляющей профессиональнойподготовкиспециалистовнафакультетеВМКвМосковском Государственном университете им.

М.В.Ломоносова. В настоящее время в связи с сильнорасширившимися международными контактами в областикомпьютерной науки успешное решение вопросовкадрового роста выпускников во многом зависит откачества их языковой подготовки.Данное учебное пособие предназначено для студентовстарших курсов, специалистов в области вычислительнойтехники, учащихся магистратуры и аспирантов. Оносостоит из 8 разделов, посвященных последним проблемами достижениям в области искусственного интеллекта,нанотехнологий,экологичныхвычисленийидр.Аутентичные материалы взяты из специализированныхисточников: Journal of Online Education, IEEE ControlSystems Magazine,American Control Conference,Communications of the ACM, Natural Computing journal,русских и англоязычных СМИ, и имеют целью дополнитьучебники по английскому языку.Послетекстовые задания, в основном, носят проблемныйхарактер и ставят целью развитие логического мышленияучащихся, их умения аргументировать, переводить нетолько с английского на русский язык, но и с русского наанглийский, помогают овладеть навыками реферированияи написания эссе по прочитанным материалам.К пособию прилагается справочный материал в разделеAppendix,призванныйпомочьучащимсяовладетьнавыками грамотного написания эссе, докладов, иподготовке к устным презентациям.Авторы выражают надежду, что включенные в сборникстатьипомогутболееэффективноорганизоватьсамостоятельную работу студентов и подготовить их кпрактической деятельности по своей специальности.От редактораComputational ThinkingWords and phrases:Computational thinkingTo draw onTangible deviceA rule of thumbBrainstormingSheer bulldozing powerEmbellishmentUnifying themeIntrinsic purposes- компьютерное,вычислительное мышление- выявлять,- реальное устройство- практический метод,эвристическое правило- групповой метод решениясложных задач- исключительно за счетвычислительной мощности- преувеличение- объединяющая тема- присущий, свойственныйComputers are incredibly fast, accurate, and stupid.Human beings are incredibly slow, inaccurate, and brilliant.Togethertheyarepowerfulbeyondimagination.Albert EinsteinComputer scientists see the value of thinking abstractly,thinking at multiple levels of abstraction, abstracting tomanage complexity, abstracting to deal with scale, etc.

Whatdo we mean by computational thinking and what are thebenefits of being able to think computationally?The statement quoted above captures the essence ofcomputational thinking. The term Computational Thinking(CT) was coined by Jannette Wing while she was head of theComputer Science Department at Carnegie Mellon.Computational thinking involves using the capabilities of one's(human) brain and the capabilities of computer (brains) torepresent and solve problems and accomplish tasks by aninformation-processing agent, or more generally, bycombinations of humans and machines. Education for4computational thinking involves learning to make effective useof these two types of brains.Here is a more recent description of computational thinking:Computational thinking is a way of solving problems,designing systems, and understanding human behavior thatdraws on concepts fundamental to computer science.Computational thinking is thinking in terms of abstractions,invariably multiple layers of abstraction at once.Computational thinking is about the automation of theseabstractions.

The automaton could be an algorithm, a Turingmachine, a tangible device, a software system or the humanbrain.Human brains get better through informal and formaleducation and through regular use. Computer brains get betterthrough the combined research and development of manythousands of people at a rapid pace. Thus, it is essential tolearn about the capabilities and limitations of the combinationof human and computer brains. Each type of brain has uniquecapabilities and limitations. Together they are incrediblypowerful.Many adjectives describe modes of thinking: abstract,analytic, conceptual, concrete, convergent, creative, critical,deductive, divergent, strategic, synthetic, tactical, and alsocomputational and procedural. Computational thinking isused in the design and analysis of problems and solutions,broadly interpreted.

The most important and high-levelthought process in computational thinking is the abstractionprocess. Abstraction is used in defining patterns, generalizingfrom instances, and parametrization. It is used to let oneobject stand for many, to capture essential properties commonto a set of objects while hiding irrelevant distinctions amongthem.

For example, an algorithm is an abstraction of aprocess that takes inputs, executes a sequence of steps, andproduces outputs to satisfy a desired goal. An abstract datatype defines an abstract set of values and operations formanipulating those values, hiding the actual representation of5the values from the user of the abstract data type. Designingefficient algorithms inherently involves designing abstractdata types.

Abstraction gives us the power to scale and dealwith complexity. Recursively applying abstraction gives us theability to build larger and larger systems, with the base case,at least for computer science being bits (0’s and 1’s).Computational thinking draws on both mathematical thinkingand engineering thinking. Unlike other engineeringdisciplines, because of software computing that makes possiblebuilding virtual worlds that are unconstrained by physicalreality.Computational and procedural thinking are fundamental ideasin the discipline of computer and information science. Acomputer is a machine that automatically, rapidly, andaccurately carries out the steps in certain types of procedures.Computer programmers think in terms of solving problemsand accomplishing tasks through the use of procedures.

Theprocedures may be algorithmic or heuristic, or a combinationof these two approaches. An algorithm is a step-by-step set ofdirections guaranteed to achieve a task, which may be to solvea particular problem in a finite number of steps.A heuristic is like an algorithm except that theaccomplishment of a specific task or solution of a specificproblem is not guaranteed. Many heuristics are called “rulesof thumb,” simple-sounding guides that often concealcomplexities.

For example, one heuristic for solving acomplex problem is to break the problem into smaller, moremanageable problems. Solve each of the smaller problems, putthe results together, and the larger problem is solved. But,there is no guarantee that one will be able to solve all of thesmaller problems, and there is no guarantee that one canfigure out how to break the large problem into appropriatepieces.Brainstorming is a group process heuristic for addressing acomplex problem. In brainstorming, people suggest ideas andthese are collected without comment by the person facilitating6the brainstorming.

Later, the group analyzes the brainstormedideas, deciding on which ones are worthy of further study.Brainstorming is often a useful process (heuristic), but there isno guarantee that it will lead to a good solution to theproblem under consideration. Developing algorithms andheuristics can be very mentally challenging.Computational thinking is the new literacy of the 21st century.It enables a person to bend computation to his or her needs.Computational thinking for everyone means being able to:• Understand what aspects of a problem are amenablefor computation• Evaluate the match between computational tools andtechniques and the problem• Understand the limitations and the power ofcomputational tools and techniques• Apply or adapt a computational tool or technique to anew use• Recognize opportunity to use computation in a newway• Apply computational strategies such as “ divide andconquer” in any domain.Computational thinking for scientists and engineers, andother professionals means being able to:• Apply new computational methods to their problems• Reformulateproblemstobeamenabletocomputational strategies• Discover new science through analysis of large data.Computers are too important to overrate or underrate.

Thereis no real point in sensationalizing or exaggerating activitieswhich are striking enough without embellishment. There is nopoint in belittling, either. It is hardly an insult to existingcomputers that they fall considerably short of the humanbrain and are not creative. The difference simply emphasizeswith new force the complexity and capabilities of the nervoussystem, and challenges us to study it as well as our machines7more deeply. The more we learn about computers, the betterwe shall understand and appreciate the nature of thought and the better we shall use our brains.

Notice that the firstparagraph mentions the idea of machine learning. Machinelearning has grown to be an important component of the fieldof Artificial Intelligence. Machine learning is defined as a“Field of study that gives computers the ability to learnwithout being explicitly programmed”.The history of electronic digital computers includes thedevelopment of three important ideas:• Computers could process both numeric and nonnumeric symbols, and thus could be used for manytasks other than just arithmetic computation.Computer Science (CS) or Computer and InformationScience (CIS)is an academic discipline and asignificant area of study, research, and development.• Information and Communication Technology (ICT)provides powerful aids to solving problems in everydiscipline.