Computer Science Text Research Articles

Author self-reference: A cross-linguistic/cultural and cross-disciplinary analysis

This study explored the use of author self-reference from cross-linguistic/cultural and cross-disciplinary perspectives in research articles (RAs). Based on a self-built corpus consisting of two disciplines (Computer Science and Linguistics) and two languages (Chinese and English), this study extracted the self-reference markers and compared their uses across the linguistic/cultural and disciplinary corpora. The cross-linguistic/cultural analysis showed that English RAs contain a higher frequency of first-person pronouns, while Chinese RAs tend to utilize more inanimate NPs in both disciplines. The cross-disciplinary comparison identified that English Computer Science texts are characterized by a more explicit authorial persona, while Chinese RAs display a mitigated authorial presence in the text construction. The findings contribute to our knowledge of how the specific disciplinary community and cultural conventions influence writers’ manifestation of their authorial presence.

Machine learning, meaning making: On reading computer science texts

Computer science tends to foreclose the reading of its texts by social science and humanities scholars – via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, when computer science papers are read in order to better understand what machine learning means for societies, a form of reading is brought to bear that is not primarily about excavating the hidden meaning of a text or exposing underlying truths about science. Not strictly reading to make sense or to discern definitive meaning of computer science texts, reading is an engagement with the sense-making and meaning-making that takes place. We propose a strategy for reading computer science that is attentive to the act of reading itself, that stays close to the difficulty involved in all forms of reading, and that works with the text as already properly belonging to the ethico-politics that this difficulty engenders. Addressing a series of three “reading problems” – genre, readability, and meaning – we discuss machine learning textbooks and papers as sites where today's algorithmic models are actively giving accounts of their paradigmatic worldview. Much more than matters of technical definition or proof of concept, texts are sites where concepts are forged and contested. In our times, when the political application of AI and machine learning is so commonly geared to settle or predict difficult societal problems in advance, a reading strategy must open the gaps and difficulties of that which cannot be settled or resolved.

Objective Type Question Generation using Natural Language Processing

Automatic Question Generation (AQG) is a research trend that enables teachers to create assessments with greater efficiency in right set of questions from the study material. Today's educational institutions require a powerful tool to correctly assess learner’s mastery of concepts learned through study materials. Objective type questions are an excellent method of assessing a learner's topic understanding in learning process, based on Information and Communication Technology (ICT) and Intelligent Tutoring Systems (ITS).Creating a set of questions for assessment can take a significant amount of time for teachers, and obtaining questions from external sources such as assessment books or question banks may not be relevant to the content covered by students during their studies. This proposed system involves to generate the familiar objective type questions like True or False, ‘Wh’, Fill up with double blank space, match the following type question have generated using Natural Language Processing(NLP) techniquesfrom the given study material. Different rules are created to generate T/F and ‘Wh’ type questions. Dependence parser method has involved in ‘Wh’ questions. Proposed system is tested with Grade V Computer Science text book as an input. Experimental result shows that the proposed system is quite promising to generate the amount of objective type assessment questions.

TOPIC SEGMENTATION METHODS COMPARISON ON COMPUTER SCIENCE TEXTS

The demand for the creation of information systems that simplifies and accelerates work has greatly increased in the context of the rapidinformatization of society and all its branches. It provokes the emergence of more and more companies involved in the development of softwareproducts and information systems in general. In order to ensure the systematization, processing and use of this knowledge, knowledge managementsystems are used. One of the main tasks of IT companies is continuous training of personnel. This requires export of the content from the company'sknowledge management system to the learning management system. The main goal of the research is to choose an algorithm that allows solving theproblem of marking up the text of articles close to those used in knowledge management systems of IT companies. To achieve this goal, it is necessaryto compare various topic segmentation methods on a dataset with a computer science texts. Inspec is one such dataset used for keyword extraction andin this research it has been adapted to the structure of the datasets used for the topic segmentation problem. The TextTiling and TextSeg methods wereused for comparison on some well-known data science metrics and specific metrics that relate to the topic segmentation problem. A new generalizedmetric was also introduced to compare the results for the topic segmentation problem. All software implementations of the algorithms were written inPython programming language and represent a set of interrelated functions. Results were obtained showing the advantages of the Text Seg method incomparison with TextTiling when compared using classical data science metrics and special metrics developed for the topic segmentation task. Fromall the metrics, including the introduced one it can be concluded that the TextSeg algorithm performs better than the TextTiling algorithm on theadapted Inspec test data set.

When a bug is not a bug: An introduction to the computer science academic vocabulary list

This article presents the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers. A 3.5-million-word corpus of academic computer science texts was developed in order to produce the CSAVL. The CSAVL draws from the improved methodologies used in the creation of recent lemma-based word lists such as the Academic Vocabulary List (AVL) (Gardner & Davies, 2014) and the Medical Academic Vocabulary List (MAVL) (Lei & Liu, 2016), which take into account the discipline-specific meanings of academic vocabulary. The CSAVL provides specific information for each entry, including part of speech and CS-specific meanings in order to provide users with clues as to how each item is used within the context of academic CS. Based on the analyses performed in this study, the CSAVL was found to be a more efficient tool for reaching an minimal level of academic CS reading comprehension than the Academic Word List (AWL) (Coxhead, 2000), or the combination of the AWL with the Computer Science Word List (CSWL) (Minshall, 2013).

Zinātniskais raksts dabaszinātņu nozarēs: kopīgais un atšķirīgais

Nowadays, the language of science is the subject of many linguistic studies. One of the research aspects in the language of science discourse is the various texts of science in written and oral communication. One of the most important types of written publications in the language of science is a scientific article. Publishers usually set certain formal and content requirements for scientific articles. There is a general belief that they are based on universal principles. Namely, in the publications of exact sciences, the prototype of a scientific article has a strictly defined structure or macrostructure, which is based on the traditional IMRaD structure of English language publications. In this article, a qualitative method is used to analyse scientific articles in the field of natural sciences and to characterize their macrostructure, paying attention to the common and different features of the structure of texts in individual sectors. The research was carried out in the framework of the project “Latvian Language of Science in the Intralingual Aspect” funded by the Latvian Council of Science. The research material consists of 114 scientific articles in natural sciences written in Latvian, which are freely available online and published from 2008 to 2018. The results of the analysis show that in natural sciences articles in Latvian, the authors mainly use the structure of IMRaD, supplementing it with other elements (for example, literature review, conclusions/conclusion). The linguistic evaluation reveals different variants of the wording used by the authors when naming the separate parts of the text macrostructure. The greatest differences in the text formation of the scientific article can be found in the scientific texts in computer science and informatics, where the authors use the classical IMRaD structure less often.

EFFECTIVENESS OF FLIPPED CLASSROOM LEARNING IN THE ACHIEVEMENT OF COMPUTER SCIENCE AMONG HIGHER SECONDARY SCHOOL STUDENTS

Modern Techniques are introduced in teaching and learning process frequently one such technique is Flipped Classroom learning. Where the pupils are asked to learn the contents given to them at their home from the available sources and they review the topics in their classroom. Since every student collect information from various sources like YouTube, Video lessons, different types of educational apps, Magazines and sources from elders etc. the collection will be excellent to review and collective ideas can help them to learn better than routine blackboard chalk and talk method by doing. So, they learn effectively and their doubts are cleared through discussion with peers in the presence of teacher. The teacher can conclude the teaching learning process by giving extra information left untouched by the students. The researcher is a computer science teacher so she took a lesson from Eleventh Standard Computer Science text book of State board in the 4th Chapter of Volume - I, "Theoretical Concepts of Operating System" and she prepared a video lesson, that video lesson is utilized by the students to learn the contents allotted to them. The Conclusion of her studying, she found that flipped classroom learning is effectively impact in the course content to the students.

EFFECTIVENESS OF BLENDED LEARNING CLASSROOM IN COMPUTER SCIENCE TEACHING AND LEARNING

In recent trends teaching and learning become very interesting due to the innovative methods of teaching using many technologies and practical tools. This study is dealing with new trends in education that can help one to become a modern teacher. Students like the teaching of modern teachers because they can actively participate in the learning process. E-content, Video Lessons and Online teaching and many other tools are used to present the subject innovatively and productively. Blended learning classroom is the latest educational technique that is being adapted in modern classrooms to enhance the learning experience of the students. The researcher is a Computer Science educator and she prepared a video lesson on "Working with Linux - Ubuntu" which is in Volume-I, Unit-I, Chapter 5 of XI Standard Computer Science text book in Tamil Nadu State Board Samacheer Kalvi new syllabus. The conclusion of her study reveals that blended learning classroom has positive impact on XI Std pupil's academic fulfilment of Computer Science.

Translating between models of concurrency

Hoare’s Communicating Sequential Processes (CSP) (Hoare in Communicating Sequential Processes, Prentice-Hall Inc, Upper Saddle River, 1985) admits a rich universe of semantic models closely related to the van Glabbeek spectrum. In this paper we study finite observational models, of which at least six have been studied for CSP, namely traces, stable failures, revivals, acceptances, refusal testing and finite linear observations (Roscoe in Understanding concurrent systems. Texts in computer science, Springer, Berlin, 2010). (Others are known.) We show how to use the relatively recently-introduced priority operator (Roscoe in Understanding concurrent systems. Texts in Computer Science, Springer, Berlin, 2010) to transform refinement questions in these models into trace refinement (language inclusion) tests. Furthermore, we are able to generalise this to any (rational) finite observational model. As well as being of theoretical interest, this is of practical significance since the state-of-the-art refinement checking tool FDR4 (Gibson-Robinson et al. in Int J Softw Tools Technol Transf 18(2):149–167, 2016) currently only supports two such models. In particular we study how it is possible to check refinement in a discrete version of the Timed Failures model that supports Timed CSP.

Reducing Complex CSP Models to Traces via Priority

Hoare's Communicating Sequential Processes (CSP) [C.A.R. Hoare. Communicating Sequential Processes. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1985] admits a rich universe of semantic models. In this paper we study finite observational models, of which at least six have been identified for CSP, namely traces, failures, revivals, acceptances, refusal testing and finite linear observations [A.W. Roscoe. Revivals, stuckness and the hierarchy of CSP models. The Journal of Logic and Algebraic Programming, 78(3):163–190, 2009]. We show how to use the recently-introduced priority operator ([A.W. Roscoe. Understanding Concurrent Systems. Texts in Computer Science. Springer, 2010], ch.20) to transform refinement questions in these models into trace refinement (language inclusion) tests. Furthermore, we are able to generalise this to any (rational) finite observational model. As well as being of theoretical interest, this is of practical significance since the state-of-the-art refinement checking tool FDR3 [Thomas Gibson-Robinson, Philip Armstrong, Alexandre Boulgakov, and A.W. Roscoe. FDR3 – a modern refinement checker for CSP. In Tools and Algorithms for the Construction and Analysis of Systems, pages 187–201. Springer, 2014] currently only supports two such models.

Exploring the effect of background knowledge and text cohesion on learning from texts in computer science

In this study, we examine the effect of background knowledge and local cohesion on learning from texts. The study is based on construction–integration model. Participants were 176 undergraduate students who read a Computer Science text. Half of the participants read a text of maximum local cohesion and the other a text of minimum local cohesion. Afterwards, they answered open-ended and multiple-choice versions of text-based, bridging-inference and elaborative-inference questions. The results showed that students with high background knowledge, reading the low-cohesion text, performed better in bridging-inference and in elaborative-inference questions, than those who read the high-cohesion text. Students with low background knowledge, reading the high-cohesion text, performed better in all types of questions than students reading the low-cohesion text only in elaborative-inference questions. The performance with open-ended and multiple-choice questions was similar, indicating that this type of question is more difficult to answer, regardless of the question format.

Neil Immerman. Descriptive complexity. Graduate texts in computer science. Springer, New York, Berlin, and Heidelberg, 1999, xvi + 268 pp.

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An interactive multimedia textbook for introductory computer science

A multimedia implementation of an introductory computer science text based on the LISP dialect Scheme, is described. The text, Exploring Computer Science with Scheme [4], is designed for beginning students who may have no prior experience using computers. The goal is to create an environment that facilitates learning of the material and concepts in the text. The multimedia system includes hypertext abilities to jump through the text, search, and mark positions in the text. A personal notebook facility is provided that allows the user to enter notes while using the system or to copy sections of the text or Scheme environment directly into the notebook. The tool provides an animation feature that illustrates how various list and applicative functions work by modeling their internal actions. A Scheme listener is built into the tool to foster testing ideas and experimentation. Since the intended audience of the text includes people with no prior computing experience, the user interface is intuitive and full help features are provided.

Historical content in computer science texts: a concern

Faculty teaching computer science courses-to majors and nonmajors alike-may have little chance to evaluate the historical material found in the texts assigned to their students. There are problems, however, in the presentations of the history of the field in many current texts, problems of which faculty are not always aware. Clarification of some of the problematic historical material found in current texts is presented, and some suggestions are offered for additional topics that should be included in the history component of the computer science curriculum. The examples are gleaned from several texts that have been otherwise valuable and effective in the presentation of computer science material; indeed, their continued presence and wide usage attest to the quality of their presentation. But the history of the field deserves the same careful treatment in these texts as do other aspects of computer science.

Essai de catégorisation sémantique des adjectifs composés (2)

Attempt at a semantic categorization of compound adjectives (2) This article follows the first part of the analysis of compound adjectives through a corpus of computer science texts. It deals with the ability of some linguistic units to combine with each other in order to generate three-and four-word compound adjectives. The study of this combinatory function has been carried out with the aim of clearing up the various generation mechanisms and the resulting semantic dynamics. From the pedagogic standpoint it allows isolating the main categories of compound adjectives to be integrated into the framework of an ESP course.

The present state of historical content in computer science texts

Writing texts in the early 1980's to fulfill the critical need in this burgeoning field, authors of computer science texts generally not mathematics or computer science historians relied upon readily available historical sources that do not stand up to critical analysis. These sources include Charles Babbage's memoirs [2], W. W. R. Ball's biased celebration of Cambridge University mathematics [3], and E. T. Bell's concise and colorful tributes to various mathematicians [6]. But these tributes and memoirs, cited in virtually every historical article, are no substitute for critical analysis of historical events.

The effect of syntactic simplification on reading EST texts as L1 and L2

ABSTRACTThere has been a considerable suggestion in the literature that syntactic adaptation of a text would simplify it. This empirical study determined that the complexity of the syntax does not significantly affect the level of reading comprehension. While a complete conceptual and lexical analysis may be necessary for reading comprehension, a thorough syntactic analysis is not. This should be true for both expert and novice readers in a particular professional field, herein computer science.Using American (L1 or E1, English as a native language) and Dutch (L2 or E2, English as a second, nonnative language) computer science and humanities majors reading in EST (English for Science and Technology), it was found that there were no significant differences between subgroups reading an authentic (in original, unadapted form) computer science text and those reading a syntactically adapted text either in comprehension or in time across the four groups of subjects. These results indicate that syntactic simplification of an EST text is not a real simplification. Hence, technical writers and EST teachers might give priority to other more conceptual ways of rewriting texts.

A content analysis of six introduction to computer science textbooks

A content analysis was conducted on three pairs of introduction to computer science textbooks to determine if there were any significant differences in their content. The results of the analysis seem to indicate that the content of major topics in earlier computer science texts is not signficantly different from more recent textbooks.

Information Representation and Manipulation in a Computer. 2nd Edition

Information Representation and Manipulation in a Computer (2nd edition). By E. S. Page and L. B. Wilson. Cambridge University Press, 1978. ix, 271 p. 22‐5 cm. £10 (hardbound). £3.95 (paperbound). (Cambridge Computer Science Texts, No. 2.)