computer science

computer science

The Evolution and Impact of Computer Science

1. Introduction to Computer Science

Computer science is the scientific and practical approach to computation and its applications. Computer science is the systematic study of the feasibility, structure, expression, and mechanization of the methodical procedures (or algorithms) that underlie the acquisition, representation, processing, storage, communication of, and access to information. The inextricable connection between computer science and the study of algorithms provides a unifying intellectual framework for computer science. Indeed, in many modern computer science curricula, algorithms are studied as part of mathematics, in courses that include mathematics foundation topics such as discrete mathematics, linear algebra, probability theory, and combinatorics as well as courses in other areas of computer science. Computer scientists may even become experts at creating and analyzing different algorithms using sophisticated mathematical tools. Computer science is not applied mathematics and is not material science. However, computer science exhibits strong relations with other sciences. The foundational scientific concept of universality is central to the idea of a general-purpose computer that can perform any computation that can be specified by an algorithm. Another foundational concept, that of specification, enables the definition of computer systems, the specification of computing and communication services, and the determination of the hardware and software components necessary to provide these services. Computer science and engineering studies the development of computing systems and the use of computers as control systems for other equipment, operating in parallel or interacting with physical equipment, creating effective methods or procedures for solving various problems in the real world. Computer science imparts essential knowledge and skills for solving problems in the real world.

With the advent of electronic digital computers in the 1940s, computer science emerged as a distinct academic discipline and as a driving force for technological progress. The computer has revolutionized the way we live, how we learn, and how we perceive the world. More recently, the wide-ranging impact of computers has led to a re-examination of the definition of computer science and the manner in which its concepts and methods are introduced and applied. This chapter begins with a discussion of the scientific foundations of computer science, then presents a model for K–12 computer science education. Programming and algorithms are used to illustrate the concepts in the model.

2. Key Theories and Concepts in Computer Science

2.72. The basics of Computer Science The first theoretical model we are going to consider is that of the finite automata around nineteen forty, the mathematician John has come up with a fundamental question. The first theoretical model we are going to consider is that of the finite automata around nineteen forty, the mathematician John has come up with a fundamental question.

2.71. Introduction This chapter is essentially expository. It looks at some of the key theoretical models underlying modern computer science and goes on to explore the ways in which such disciplines operate across disciplines at the very heart of the subject. In terms of computer characteristics, as with mechanical engineering, the computer science field is well understood. We can talk confidently about constants, such as constants for time, space, manufacturability, cost, and ultimately performance. Similarly with respect to the design space, it includes software, commands, utilities, tools, extended systems, and interfaces. Interconnection networks and operating systems are other concepts, as are distributed and shared memory and parallelism. Major categories of computers are reviewed.

3. Applications and Innovations in Computer Science

However, while much of the initial work on game playing was predicated on the potential that playing games could be used to define and compare intelligent behavior, the applications of game-playing research to other areas are mainly attributable to its historical precedent, rather than to a connection between games and these areas. In contrast to board games with simple, uniform rules of nature, complex systems in the natural and imagined worlds that scientists and engineers study have structure, order, and complexity at many levels. In the following sections, we review several principal areas and questions on the impact of computer science with the intention of discussing our perspectives on instances of consensus and contention in the principles of “Societal”.

As winning strategies have been found for larger and larger instances of traditional games like chess and checkers—as well as entirely new video games like Ms. Pac-Man and Dota—these successes have generated lively commentary, and the related research has contributed a number of algorithmic improvements that are relevant far beyond the domains of game playing. Specific applications of traditional game-playing algorithms to problems in robotics have been demonstrated. Competition and tournament organization has played a major role in the assembly and dissemination of invigorating test sets and benchmarks for algorithms of all sorts; chess and checkers competition led to the LINPACK and TOP500 lists, which spur innovation in solution techniques for large systems of linear equations and scientific computing more generally. Game playing has also resulted in the development, popularization, and improvement of important forms of interactive experiences that are valued more for entertainment and intellectual enjoyment than for practical goals.

4. Ethical Considerations in Computer Science

Finally, we would be remiss if we did not acknowledge the ethical considerations with which computer scientists must grapple, particularly as they create the Internet and apps, and store, analyze, and present the data of the world. Neal Postman’s question in Technopoly is central and prescient: what is the problem to which the technology is the solution? Postman further offers a way forward by quoting the technology critic Jerry Mander: “You are free to do as we tell you.” Thus, as instructors prepare project-based offerings in learning communities or math, social science, or even computer science classes, this ethical consideration of the software we solicit or buy or create is crucial. You want to know the problem, or the type of problem, and then seek out the best options that respect the user, the user’s capability to learn from and with the user interface, and the right of the user to own, control, and grow from the software and use. By considering who is served best and who may be left out or left behind, we raise the discussion to an ethical plane. It is our continuing privilege to engage students with appropriate software, ask students to critique software and develop their own understanding of what is appropriate, and model ethical curriculum development by transposing our concerns into finding software and curricular models that serve the educational goals and well-being of the students in our charge.