Readers' corner: The role of experiments in computer science

Fletcher, Peter

doi:10.1016/0164-1212(95)00050-b

Cited by 12 publications

(14 citation statements)

References 10 publications

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“…But there are a number of other arguments against the scientific nature of computing. For instance, Peter Fletcher (1995) opposed an undue emphasis of the hypothetico-deductive model in computing fields and noted that without the theoretical principle of Turing equivalence of all computers (i.e. particular characteristics of computers are, in principle, irrelevant) there would be no academic discipline of computing, but just eclectic knowledge about particular machines.…”

Section: Objections To the Scientific Viewmentioning

confidence: 97%

“…He continued to argue that instead of seeking the best solutions to previously specified problems, often researchers in computing work with problems that are poorly understood and where one major goal is to find and understand problems, delimit them precisely, and convince others that those problems are worth solving (Fletcher, 1995). In other words, exploration and description seem to be valuable aims in computing.…”

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confidence: 96%

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Three traditions of computing: what educators should know

Tedre

Sutinen

2008

Computer Science Education

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Educators in the computing fields are often familiar with the characterization of computing as a combination of theoretical, scientific, and engineering traditions. That distinction is often used to guide the work and disciplinary self-identity of computing professionals. But the distinction is, by no means, an easy one. The three traditions of computing are based on different principles, they have different aims, they employ different methods, and their products are very different. Educators in the field of computing should be aware of the fundamental differences between the traditions of computing so that they can offer their students a truthful and balanced view about computing branches. In this article the three traditions of computing are presented and some of their underlying assumptions, principles, application areas, restrictions, and weaknesses are portrayed. Also, some of the landmark arguments in the debates about the identity of computing disciplines are discussed.

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Section: Objections To the Scientific Viewmentioning

confidence: 97%

mentioning

confidence: 96%

Three traditions of computing: what educators should know

Tedre

Sutinen

2008

Computer Science Education

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“…Data collection through social networks is notoriously problematic for traditional sampling terms. Laboratory and field testing of computer systems often lack proper description and justification of the setup, parameter choices, measured outputs and variables, and choice of competing systems [2,7,8].…”

Section: Selection Of Information Sourcesmentioning

confidence: 99%

“…In computing experimentation terminology is used differently from many other fields [28]. Others have argued that precautions against bias are often not taken [7,8]. Yet others have argued that computing researchers just act like scientists but do not really do science [17].…”

Section: Introductionmentioning

confidence: 99%

Towards identification and classification of core and threshold concepts in methodology education in computing

Tedre¹,

Brash²,

Männikkö-Barbutiu³

et al. 2014

Proceedings of the 2014 Conference on Innovation &Amp; Technology in Computer Science Education - ITiCSE '14

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Research methodology is a quintessential component of science, but methods differ greatly between sciences. In computing, methods are borrowed from many fields, which causes difficulties to methodology education in computing. In our methodology courses in computing, we have observed a number of core and threshold concepts that affect students' success. This essay describes a work in progress towards understanding those core and threshold concepts in methodology education in computing, classified along two dimensions. We classify methodological concepts in terms of standard elements of research design in students' projects in computing, and in terms of their centrality and difficulty. We present examples of three types of troublesome knowledge concerning methodology: the strangeness and complexity of methodological concepts, misimpressions from everyday experience, and reasonable but mistaken expectations.

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“…For instance, they are presented with the view that theories in computer science do not explain fundamental phenomena (cf. Hartmanis, 1993) and the view that much of computer science resembles exploration of uncharted territory rather than seeking solutions to clearly specified problems (Fletcher, 1995). A note is made that the observations about algorithm behavior, the usability of machinery and software, or information retrieval, are observations of things that computer scientists have constructed.…”

Section: Theme 3: Mathematics Engineering and Sciencementioning

confidence: 99%

Know Your Discipline: Teaching the Philosophy of Computer Science

Tedre

2007

Proceedings of the 2007 InSITE Conference

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The diversity and interdisciplinarity of computer science and the multiplicity of its uses in other sciences make it hard to define computer science and to prescribe how computer science should be carried out. The diversity of computer science also causes friction between computer scientists from different branches. Computer science curricula, as they stand, have been criticized for being unable to offer computer scientists proper methodological training or a deep understanding of different research traditions. At the Department of Computer Science and Statistics at the University of Joensuu we decided to include in our curriculum a course that offers our students an awareness of epistemological and methodological issues in computer science, and we wanted to design the course to be meaningful for practicing computer scientists. In this article the needs and aims of our course on the philosophy of computer science are discussed, and the structure and arrangements—the whys, whats, and hows—of that course are explained. The course, which is given entirely on-line, was designed for advanced graduate or postgraduate computer science students from two Finnish universities: the University of Joensuu and the University of Kuopio. The course has four relatively broad themes, and all those themes are tied to the students’ everyday work or their own research topics. I have prepared course readings about each of those four themes. The course readings describe, in a compact and simple form, the cruces of the topics that are discussed in the course. The electronic version of the course readings includes hyperlinks to a large number of articles that are available on-line. The course readings are publicly available on the course home page, and they are licensed under the creative commons license.

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Readers' corner: The role of experiments in computer science

Abstract: Abstract

Cited by 12 publications

References 10 publications

Three traditions of computing: what educators should know

Three traditions of computing: what educators should know

Towards identification and classification of core and threshold concepts in methodology education in computing

Know Your Discipline: Teaching the Philosophy of Computer Science

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