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Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact upon systematic reviews and mapping studies. Method: We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. Results: We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., ≈ 8%. For CS, 56% of retracted papers provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also some disparity between different publishers, a tendency for multiple versions of a retracted paper to be available beyond the Version of Record (VoR), and for new citations long after a paper is officially retracted (median = 3; maximum = 18). Systematic reviews are also impacted with ≈ 30% of the retracted papers having one or more citations from a review. Conclusions: Unfortunately, retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the differences between conference papers and journal papers in the field of computer science based on Bayesian network. This paper investigated the differences between conference papers and journal papers in the field of computer science based on Bayesian network, a knowledge-representative framework that can model relationships among all variables in the network. We defined the variables required for Bayesian networks modeling, calculated the values of each variable based Aminer dataset (a literature data set in the field of computer science), learned the Bayesian network and derived some findings based on network inference. The study found that conferences are more attractive to senior scholars, the academic impact of conference papers is slightly higher than journal papers, and it is uncertain whether conference papers are more innovative than journal papers. The study was limited to the field of computer science and employed Aminer dataset as the sample. Further studies involving more diverse datasets and different fields could provide a more complete picture of the matter. By demonstrating that Bayesian networks can effectively analyze issues in Scientometrics, the study offers valuable insights that may enhance researchers' understanding of the differences between journal and conference in computer science. Academic conferences play a crucial role in facilitating scholarly exchange and knowledge dissemination within the field of computer science. Several studies have been conducted to examine the distinctions between conference papers and journal papers in terms of various factors, such as authors, citations, h-index and others. Those studies were carried out from different (independent) perspectives, lacking a systematic examination of the connections and interactions between multiple perspectives. This paper supplements this deficiency based on Bayesian network modeling. [ABSTRACT FROM AUTHOR]

This small scale study aims to analyze the question papers of Board of Intermediate and Secondary Education in the subject of computer science with reference to item analysis and Bloom's taxonomy. Data were collected from 100 students of Grade 9th and 10th from the schools of Lahore city using convenient sampling technique. Data collected on the papers developed by Board of Intermediate and Secondary Education for the year of 2015 and 2016. Item analyses were performed using Conquest software. Findings of the study shows that in the question papers conducted by Board of Intermediate and Secondary Education the majority questions were measuring the student abilities of knowledge and comprehension and only few questions were given to measure the student abilities to analyze, synthesize and evaluate, and this can be very helpful for the policy makers. Result of item analysis shows that many questions were not in the acceptable range of item difficulty and item discrimination. Items in the question papers were either too easy or too difficult. Findings revealed that the papers conducted and administered by Board of Intermediate and Secondary Education were not up to the mark, with reference to Bloom's taxonomy. The researcher recommended to train the assessment committee/panel developing the items. [ABSTRACT FROM AUTHOR]

The paper-and-pencil programming strategy (PPS) is a way of representing an idea logically by any representation that can be created using paper and pencil. It was developed for non-computer majors to improve their understanding and use of computational thinking and increase interest in learning computer science. A total of 110 non-majors in their sophomore year were assigned to either a Logo or a PPS course with attendance being 2 hours per week for 15 weeks. To measure the effectiveness of PPS, the Group Assessment of Logical Thinking and a self-assessment survey pre- and post-test were used. Findings indicated that PPS not only improved students' overall logical thinking as much as did Logo programming learning, but also increased scores on one more subscale of logical thinking than did the Logo course. In addition, PPS significantly helped students understand the concept of computational thinking and increased their interest in learning computer science.

Driving research questions from the prevailing issues and interests and developing from them new theories, formulas, algorithms, methods, and designs, and linking them to the interests of the larger audience is a vital component of scientific research papers. The present article discusses outlining purposes or stating the nature of the present research, and listing research questions or hypotheses in the introduction of academic papers. This corpus-based genre study focuses particularly on Move 3 of the model "occupying the niche." The results indicating disciplinary variation show that the writers of Computer Science (CS) research articles, over the years have developed an increased use of outlining purpose/stating the nature of the present research, having the characteristics of purposive, descriptive, extension of the previous work, contrast to the existing work, brevity, complexity, and a description of methodology. It also shows that listing research questions or hypothesis may have distinctively different functions in developing genres as compared to the established ones such as physics.

In this article, we test the hypothesis that computer science papers asking questions (i.e., those with a question mark at the end of their title) are cited more frequently than those that do not have this property. To this end, we analyze a data set of almost two million records on computer science papers indexed in the Web of Science database and focus our investigation on the mean number of citations per paper of its specific subsets. The main finding is that the average number of citations per paper of the so-called “asking papers” is greater by almost 20% than that of other papers, and that this difference is statistically significant.

Purpose: The number of citations has been widely used to measure the significance of a paper. However, there is a need in introducing another index to determine superiority or inferiority of papers with the same number of citations. We determine superiority or inferiority of papers by using the ranking based on the number of citations and PageRank. Design/methodology/approach: We show the positive linear correlation between Citation Rank (the ranking of the number of citation) and PageRank. On this basis, we identify high-quality, prestige, emerging, and popular papers. Findings: We found that the high-quality papers belong to the subjects of biochemistry and molecular biology, chemistry, and multidisciplinary sciences. The prestige papers correspond to the subjects of computer science, engineering, and information science. The emerging papers are related to biochemistry and molecular biology, as well as those published in the journal "Cell." The popular papers belong to the subject of multidisciplinary sciences. Research limitations: We analyze the Science Citation Index Expanded (SCIE) from 1981 to 2015 to calculate Citation Rank and PageRank within a citation network consisting of 34,666,719 papers and 591,321,826 citations. Practical implications: Our method is applicable to forecast emerging fields of research subjects in science and helps policymakers to consider science policy. Originality/value: We calculated PageRank for a giant citation network which is extremely larger than the citation networks investigated by previous researchers. [ABSTRACT FROM AUTHOR]

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Lecture Notes in Computer Science (LNCS) is a globally recognised publication outlet for the field of Computer Science, including in South Africa. In this study, spanning from 1973 to 2022, we investigated the research participation of South African based authors in LNCS. The publication output and citation impact of these authors were compared to the global Computer Science and LNCS output. The authorship patterns and collaborative behaviour of South African LNCS papers were explored, and a keyword or topic analysis also conducted. Of the total of 518 662 LNCS papers published globally between 1973 and 2022, South African based researchers contributed 1150 papers (0.22%). The LNCS papers from South Africa exhibit a strong collaborative publication culture, with 1043 (91%) co-authored and 107 (9%) singleauthored works. Local LNCS researchers prefer institutional collaboration (43%), followed by international (37%) and national collaboration (11%). Europe emerged as the most significant collaboration partner for LNCS researchers in South Africa. Of the 1150 papers, 836 (73%) had received citations, while 314 (27%) had not. On average, papers published by South African based authors received 6.05 citations, compared to the global LNCS average of 9.49 citations per paper. A keyword analysis revealed that the majority of papers by South African authors focus on artificial intelligence. The results indicate that, although LNCS serves as a reputable dissemination platform for Computer Science research output both globally and locally, South African authors should consider publishing more journal articles to build and improve their researcher profiles. Significance: * The study shows that LNCS is the most frequent publication outlet for Computer Science researchers, globally and in South Africa. * The study offers insight into the publication output, authorship patterns, collaborative behaviour and citation impact of South African based Computer Science researchers. [ABSTRACT FROM AUTHOR]

In the November 2021 issue of Spectroscopy, we published a review paper titled 'H-Classic Papers in Atomic Spectroscopy: An Integrative Literature Review' (1). This paper caused quite a bit of […]