Tom Crick

Restart: The Resurgence of Computer Science in UK Schools

Computer science in UK schools is undergoing a remarkable transformation. While the changes are not consistent across each of the four devolved nations of the UK (England, Scotland, Wales and Northern Ireland), there are developments in each that are moving the subject to become mandatory for all pupils from age 5 onwards. In this article, we detail how computer science declined in the UK, and the developments that led to its revitalisation: a mixture of industry and interest group lobbying, with a particular focus on the value of the subject to all school pupils, not just those who would study it at degree level. This rapid growth in the subject is not without issues, however: there remain significant forthcoming challenges with its delivery, especially surrounding the issue of training sufficient numbers of teachers. We describe a national network of teaching excellence which is being set up to combat this problem, and look at the other challenges that lie ahead.

Bringing computer science back into schools: lessons from the UK

Computer science in UK schools is a subject in decline: the ratio of Computing to Maths A-Level students (i.e. ages 16--18) has fallen from 1:2 in 2003 to 1:20 in 2011 and in 2012. In 2011 and again in 2012, the ratio for female students was 1:100, with less than 300 female students taking Computing A-Level in the whole of the UK each year. Similar problems have been observed in the USA and other countries, despite the increased need for computer science skills caused by IT growth in industry and society. In the UK, the Computing At School (CAS) group was formed to try to improve the state of computer science in schools. Using a combination of grassroots teacher activities and policy lobbying at a national level, CAS has been able to rapidly gain traction in the fight for computer science in schools. We examine the reasons for this success, the challenges and dangers that lie ahead, and suggest how the experience of CAS in the UK can benefit other similar organisations, such as the CSTA in the USA.

TOAST: applying answer set programming to superoptimisation

Answer set programming (ASP) is a form of declarative programming particularly suited to difficult combinatorial search problems. However, it has yet to be used for more than a handful of large-scale applications, which are needed to demonstrate the strengths of ASP and to motivate the development of tools and methodology. This paper describes such a large-scale application, the TOAST (Total Optimisation using Answer Set Technology) system, which seeks to generate optimal machine code for simple, acyclic functions using a technique known as superoptimisation. ASP is used as a scalable computational engine to handle searching over complex, non-regular search spaces, with the experimental results suggesting that this is a viable approach to the optimisation problem and demonstrates the scalability of a variety of solvers.

Computing at school: stimulating computing education in the UK

In this paper, we present the development of Computing at School (CAS), a UK membership association established in 2008 to promote and support the teaching of Computing and related disciplines in UK schools. Its membership is broad and includes teachers, parents, examiners, university faculty, professional societies and industry. CAS was born out of a serious concern that many students in the UK are disengaging from Computing as a discipline. The goal of CAS is to put the excitement back into Computing at school, as well as to influence Computing education policy in the UK, especially improving the wider perception of the discipline and its position within the STEM subject area.

LAIMA: a multi-agent platform using ordered choice logic programming

Multi-agent systems (MAS) can take many forms depending on the characteristics of the agents populating them. Amongst the more demanding properties with respect to the design and implementation of multi-agent system is how these agents may individually reason and communicate about their knowledge and beliefs, with a view to cooperation and collaboration. In this paper, we present a deductive reasoning multi-agent platform using an extension of answer set programming (ASP). We show that it is capable of dealing with the specification and implementation of the systems architecture, communication and the individual agents reasoning capacities. Agents are represented as Ordered Choice Logic Programs (OCLP) as a way of modelling their knowledge and reasoning capacities, with communication between the agents regulated by uni-directional channels transporting information based on their answer sets. In the implementation of our system we combine the extensibility of the JADE framework with the flexibility of the OCT front-end to the Smodels answer set solver. The power of this approach is demonstrated by a multi-agent system reasoning about equilibria of extensive games with perfect information.

A multi-disciplinary perspective on emergent and future innovations in peer review

Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.

Engineering design optimization using services and workflows

Multi-disciplinary design optimization (MDO) is the process whereby the often conflicting requirements of the different disciplines to the engineering design process attempts to converge upon a description that represents an acceptable compromise in the design space. We present a simple demonstrator of a flexible workflow framework for engineering design optimization using an e-Science tool. This paper provides a concise introduction to MDO, complemented by a summary of the related tools and techniques developed under the umbrella of the UK e-Science programme that we have explored in support of the engineering process. The main contributions of this paper are: (i) a description of the optimization workflow that has been developed in the Taverna workbench, (ii) a demonstrator of a structural optimization process with a range of tool options using common benchmark problems, (iii) some reflections on the experience of software engineering meeting mechanical engineering, and (iv) an indicative discussion on the feasibility of a ‘plug-and-play’ engineering environment for analysis and design.

R U :-) or :-( ? Character- vs. Word-Gram Feature Selection for Sentiment Classification of OSN Corpora

Binary sentiment classification, or sentiment analysis, is the task of computing the sentiment of a document, i.e. whether it contains broadly positive or negative opinions. The topic is well-studied, and the intuitive approach of using words as classification features is the basis of most techniques documented in the literature. The alternative character n-gram language model has been applied successfully to a range of NLP tasks, but its effectiveness at sentiment classification seems to be under-investigated, and results are mixed. We present an investigation of the application of the character n-gram model to text classification of corpora from online social networks, the first such documented study, where text is known to be rich in so-called unnatural language, also introducing a novel corpus of Facebook photo comments. Despite hoping that the flexibility of the character n-gram approach would be well-suited to unnatural language phenomenon, we find little improvement over the baseline algorithms employing the word n-gram language model.

"Share and Enjoy"""": Publishing Useful and Usable Scientific Models

The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural problem that pervades the scientific community. Sharing code, data and models often requires extra effort, this is currently seen as a significant overhead that may not be worth the time investment. Automated systems, which allow easy reproduction of results, offer the potential to incentives a culture change and drive the adoption of new techniques to improve the efficiency of scientific exploration. In this paper, we discuss the value of improved access and sharing of the two key types of results arising from work done in the computational sciences: models and algorithms. We propose the development of an integrated cloud-based system underpinning computational science, linking together software and data repositories, tool chains, workflows and outputs, providing a seamless automated infrastructure for the verification and validation of scientific models and in particular, performance benchmarks.

The Smart City from a Public Value Perspective

This paper explores whether it is useful to view the fundamental ideas behind the smart city concept through the lens of the ‘Public Value Management’ (PVM) paradigm. It investigates how appropriate ICT investment in cities might be articulated and valued through the concept of PVM. In order to achieve this, it explores the core concepts found in the PVM literature, and draws key connections to the smart city