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Computer science has been a discipline for some years, and its position in the school curriculum has been contested differently in several countries. This paper looks at its role in three countries to illustrate these differences. A reconsideration of computer science as a separate subject both in primary and secondary education is suggested. At EDUsummIT 2015 it was argued that the major rationales for including computer science as a subject in the K-12 curriculum are economic, social and cultural. The paper explores these three rationales and also a beneficence matrix to assist curriculum designers. It also argues computer science is rapidly becoming critical for generating new knowledge, and should be taught as a distinct subject or content area, especially in secondary schools. The paper concludes by looking at some of the key questions to be considered when implementing computer science in the school curriculum, and at ways its role might change in the future.

Automatic grading is not a new approach but the need to adapt the latest technology to automatic grading has become very important. As the technology has rapidly became more powerful on scoring exams and essays, especially from the 1990s onwards, partially or wholly automated grading systems using computational methods have evolved and have become a major area of research. In particular, the demand of scoring of natural language responses has created a need for tools that can be applied to automatically grade these responses. In this paper, we focus on the concept of automatic grading of short answer questions such as are typical in the UK GCSE system, and providing useful feedback on their answers to students. We present experimental results on a dataset provided from the introductory computer science class in the University of North Texas. We first apply standard data mining techniques to the corpus of student answers for the purpose of measuring similarity between the student answers and the model answer. This is based on the number of common words. We then evaluate the relation between these similarities and marks awarded by scorers. We consider an approach that groups student answers into clusters. Each cluster would be awarded the same mark, and the same feedback given to each answer in a cluster. In this manner, we demonstrate that clusters indicate the groups of students who are awarded the same or the similar scores. Words in each cluster are compared to show that clusters are constructed based on how many and which words of the model answer have been used. The main novelty in this paper is that we design a model to predict marks based on the similarities between the student answers and the model answer. We argue that computational methods be used to enhance the reliability of human scoring, and not replace it. Humans are required to calibrate the system, and to deal with situations that are challenging. Computational methods can provide insight into which student answers will be found challenging and thus be a place human judgement is required. [ABSTRACT FROM AUTHOR]

Research has shown that e-learning games do not have the same level of appeal to girls, as they do to boys; particularly in the crucial 11-14 age group. In the United Kingdom, this is typically when they start to make subject choices that impact their future studies and careers. Given the shortage of females who choose computer science as a career, this study explores how e-learning games can be designed to be motivationally appealing to young learners. It further explores the role of game representations and its appeal to this age group. This empirical study addresses the research question: "Can we develop e-learning games which appeal and motivate girls of age 11-14 to study computer science concepts?" Two e-learning games were developed: one included game representations such as game colour, graphics, character, age appropriateness, storyline, number of players, violence, identified as appealing to young females and the other game included antithetical or neutral representations. The two developed prototypes were used to explore key e-learning game representations as used to teach computer science concepts. A total of 304 participants, comprising of 152 girls and 152 boys from a combination of same sex and mixed secondary schools in Southeast England, engaged with both experimental games. The experiment also elicited information on how learners interact with these games and the resulting game appeal, motivation and learning. The insight gained from the analysis of data captured during the experiments, provide the evidence to demonstrate that inclusive e-learning games which motivate and appeal to girls of age 11-14 can be developed. This can have a positive influence on their willingness to use such games to learn computer science concepts. This implies that the study found positive outcomes related to e-learning game appeal, motivation and the learning of girls of this age group. A follow-up longitudinal study could investigate the impact of significant e-learning game representations that appeal to the target group. This could provide additional evidence on the changes in the appeal of the investigated significant game representations over time, due to the influence of other factors such as socio-economic and socio-cultural differences. This understanding can further enhance inclusive e-learning strategies to improve diversity in computer science education and consequently the career pipeline. [ABSTRACT FROM AUTHOR]

Background: Virtual reality (VR) and augmented reality (AR) have recently become popular research themes. However, there are no published bibliometric reports that have analyzed the corresponding scientific literature in relation to the application of these technologies in medicine.Objective: We used a bibliometric approach to identify and analyze the scientific literature on VR and AR research in medicine, revealing the popular research topics, key authors, scientific institutions, countries, and journals. We further aimed to capture and describe the themes and medical conditions most commonly investigated by VR and AR research.Methods: The Web of Science electronic database was searched to identify relevant papers on VR research in medicine. Basic publication and citation data were acquired using the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer and Bibliometrix, dedicated bibliometric software packages, for further analyses. Visualization maps were generated to illustrate the recurring keywords and words mentioned in the titles and abstracts.Results: The analysis was based on data from 8399 papers. Major research themes were diagnostic and surgical procedures, as well as rehabilitation. Commonly studied medical conditions were pain, stroke, anxiety, depression, fear, cancer, and neurodegenerative disorders. Overall, contributions to the literature were globally distributed with heaviest contributions from the United States and United Kingdom. Studies from more clinically related research areas such as surgery, psychology, neurosciences, and rehabilitation had higher average numbers of citations than studies from computer sciences and engineering.Conclusions: The conducted bibliometric analysis unequivocally reveals the versatile emerging applications of VR and AR in medicine. With the further maturation of the technology and improved accessibility in countries where VR and AR research is strong, we expect it to have a marked impact on clinical practice and in the life of patients. [ABSTRACT FROM AUTHOR]

The article focuses on the exposure and effectiveness of the Leg Club model in the healthcare system in Great Britain. Topics discussed include an overview of the Leg Club model, the significance of informatics, the wound care of the National Health Service, and the plan of Finland to set its first Leg Club.