Scientific concepts are expressed through the strategic use of language and rhetorical devices. This study aims at identifying and investigating a basic English for science, which would cross the computer science and mathematics languages, facilitating the discursive learning process in academic and professional scientific fields. Language in science plays an important role because it is the vehicle, the tool through which scientific knowledge is conveyed in a clear, economical way. Scientific knowledge reflects the outside world as filtered through and influenced by culture, beliefs, interactions with others, stimulating pragmatic and cognitive processes. The receiver who acquires a scientific message/knoweldge is as active as the transmitter elaborating the content of the message. They both act and then react to the transmitting and understanding of the phenomena: “il est important de remarquer que la particularité (…) dans un code de sèmes dont les signifiés se trouvent en rapport logique d’inclusion ou d’intersection entre eux, consiste précisément non pas seulement dans la mise en contribution des circonstances pour “dire” ce que l’on « veut dire », mais dans la possibilité d’adapter la faon de le « dire » à l’apport que celles-ci sont susceptibles de faire » (Luis J. Prieto, Pertinence et pratique, essai de sémiologie, p.134). Studies have been done in the field of rhetoric of science analyzing different scientists’ discourses; they mostly report that scientists express their knowledge using persuasive processes, accepting or rejecting statements, through interactive rhetorical figures.To a better understanding of the computer science and mathematical discourses, the language of science will be explored; just like any other language, it has a basic alphabet, i.e., the natural numbers, and just like any language, its alphabet has an order. Since very ancient times numbers and letters have continually been related: numbers in mathematics or digits in computer science, they convey information just like words. According to Chomsky, all languages in the world must share certain structural properties despite their very different grammars. Mathematics and computer science both work according to the laws of logic: like any science they follow a coherent system of signs and rules: they are concerned with the study of number, quantity, shape and space using specialized notations. They are both indispensable technological and commercial tools, the bedrocks of all sciences. Aristotle’s laws of logical reasoning have considerably influenced the principles of these sciences and their respective languages. Mathematical connectives will be analyzed and associated to grammatical connectives, e.g.: “if…belongs to….”. Specific concepts of mathematics and computer science can be expressed through symbols, formulae, diagrams, images. These codes need to be verbalized for discursive purposes. Their specific vocabularies will be considered: the use of abbreviations, compound words, terms derived from Greek or Latin, the frequency and use of adjectives, phrasal verbs. It is a matter of experimentation and observation to determine precisely what abilities are innate and what properties are shared by both languages.
English in Computer Science and Mathematics - rhetorical devices and strategic vocabulary
Rudd L
;Bagnardi A.
2014-01-01
Abstract
Scientific concepts are expressed through the strategic use of language and rhetorical devices. This study aims at identifying and investigating a basic English for science, which would cross the computer science and mathematics languages, facilitating the discursive learning process in academic and professional scientific fields. Language in science plays an important role because it is the vehicle, the tool through which scientific knowledge is conveyed in a clear, economical way. Scientific knowledge reflects the outside world as filtered through and influenced by culture, beliefs, interactions with others, stimulating pragmatic and cognitive processes. The receiver who acquires a scientific message/knoweldge is as active as the transmitter elaborating the content of the message. They both act and then react to the transmitting and understanding of the phenomena: “il est important de remarquer que la particularité (…) dans un code de sèmes dont les signifiés se trouvent en rapport logique d’inclusion ou d’intersection entre eux, consiste précisément non pas seulement dans la mise en contribution des circonstances pour “dire” ce que l’on « veut dire », mais dans la possibilité d’adapter la faon de le « dire » à l’apport que celles-ci sont susceptibles de faire » (Luis J. Prieto, Pertinence et pratique, essai de sémiologie, p.134). Studies have been done in the field of rhetoric of science analyzing different scientists’ discourses; they mostly report that scientists express their knowledge using persuasive processes, accepting or rejecting statements, through interactive rhetorical figures.To a better understanding of the computer science and mathematical discourses, the language of science will be explored; just like any other language, it has a basic alphabet, i.e., the natural numbers, and just like any language, its alphabet has an order. Since very ancient times numbers and letters have continually been related: numbers in mathematics or digits in computer science, they convey information just like words. According to Chomsky, all languages in the world must share certain structural properties despite their very different grammars. Mathematics and computer science both work according to the laws of logic: like any science they follow a coherent system of signs and rules: they are concerned with the study of number, quantity, shape and space using specialized notations. They are both indispensable technological and commercial tools, the bedrocks of all sciences. Aristotle’s laws of logical reasoning have considerably influenced the principles of these sciences and their respective languages. Mathematical connectives will be analyzed and associated to grammatical connectives, e.g.: “if…belongs to….”. Specific concepts of mathematics and computer science can be expressed through symbols, formulae, diagrams, images. These codes need to be verbalized for discursive purposes. Their specific vocabularies will be considered: the use of abbreviations, compound words, terms derived from Greek or Latin, the frequency and use of adjectives, phrasal verbs. It is a matter of experimentation and observation to determine precisely what abilities are innate and what properties are shared by both languages.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.