ePortfolios: models and implementation

This paper explores the use of ePortfolio tools to support teaching, learning and the personal and professional development of postgraduate students at the Institute of Education, University of London (IOE). The needs of tutors and students are considered alongside the affordances and limitations of specific tools in relation to these needs. The study involved five areas of postgraduate study at the IOE, one at PhD level, two at Masters level (MA in ICT in Education and MTeach) and two PGCE courses (PGCE in ICT and Post-Compulsory PGCE). Preliminary discussions with IOE staff revealed five common themes relating to the perceived purpose of an ePortfolio: model, ownership, collaboration, accessibility and support. The first theme relates to the definition of the ePortfolio, whilst the remaining themes address questions relating to ownership, control, use and user needs/development. In this paper, each of the themes and the questions raised within those areas are addressed in detail and a cross-comparative table of responses across each of five teaching scenarios is provided with levels of importance measured on a scale of 1 (low) to 4 (high)

Translation and human-computer interaction

This paper seeks to characterise translation as a form of human-computer interaction. The evolution of translator-computer interaction is explored and the challenges and benefits are enunciated. The concept of cognitive ergonomics is drawn on to argue for a more caring and inclusive approach towards the translator by developers of translation technology. A case is also made for wider acceptance by the translation community of the benefits of the technology at their disposal and for more humanistic research on the impact of technology on the translator, the translation profession and the translation process

Towards Industrialized Conception and Production of Serious Games

Serious Games (SGs) have experienced a tremendous outburst these last years. Video game companies have been producing fun, user-friendly SGs, but their educational value has yet to be proven. Meanwhile, cognition research scientist have been developing SGs in such a way as to guarantee an educational gain, but the fun and attractive characteristics featured often would not meet the public's expectations. The ideal SG must combine these two aspects while still being economically viable. In this article, we propose a production chain model to efficiently conceive and produce SGs that are certified for their educational gain and fun qualities. Each step of this chain will be described along with the human actors, the tools and the documents that intervene

User-centered development of a Virtual Research Environment to support collaborative research events

This paper discusses the user-centred development process within the Collaborative Research Events on the Web (CREW) project, funded under the JISC Virtual Research Environments (VRE) programme. After presenting the project, its aims and the functionality of the CREW VRE, we focus on the user engagement approach, grounded in the method of co-realisation. We describe the different research settings and requirements of our three embedded user groups and the respective activities conducted so far. Finally we elaborate on the main challenges of our user engagement approach and end with the project’s next steps

Vision-Based Production of Personalized Video

In this paper we present a novel vision-based system for the automated production of personalised video souvenirs for visitors in leisure and cultural heritage venues. Visitors are visually identified and tracked through a camera network. The system produces a personalized DVD souvenir at the end of a visitor’s stay allowing visitors to relive their experiences. We analyze how we identify visitors by fusing facial and body features, how we track visitors, how the tracker recovers from failures due to occlusions, as well as how we annotate and compile the final product. Our experiments demonstrate the feasibility of the proposed approach

A Shared Task on Bandit Learning for Machine Translation

We introduce and describe the results of a novel shared task on bandit learning for machine translation. The task was organized jointly by Amazon and Heidelberg University for the first time at the Second Conference on Machine Translation (WMT 2017). The goal of the task is to encourage research on learning machine translation from weak user feedback instead of human references or post-edits. On each of a sequence of rounds, a machine translation system is required to propose a translation for an input, and receives a real-valued estimate of the quality of the proposed translation for learning. This paper describes the shared task's learning and evaluation setup, using services hosted on Amazon Web Services (AWS), the data and evaluation metrics, and the results of various machine translation architectures and learning protocols.Comment: Conference on Machine Translation (WMT) 201

Building capacity in climate change policy analysis and negotiation: methods and technologies

Capacity building is often cited as the reason “we cannot just pour money into developing countries” and why so many development projects fail because their design does not address local conditions. It is therefore a key technical and political concept in international development. Some of the poorest countries in the world are also some of the most vulnerable to the impacts of climate change. Their vulnerability is in part due to a lack of capacity to plan and anticipate the effects of climate change on crops, water resources, urban electricity demand etc. What capacities do these countries lack to deal with climate change? How will they cope? What steps can they take to reduce their vulnerability? This innovative and high-profile research project was part of a larger project (called C3D) and conducted with non-governmental organisations in Senegal, South Africa and Sri Lanka. The research involved several participatory workshops and a questionnaire to all three research centres

Taking statistical machine translation to the student translator

Despite the growth of statistical machine translation (SMT) research and development in recent years, it remains somewhat out of reach for the translation community where programming expertise and knowledge of statistics tend not to be commonplace. While the concept of SMT is relatively straightforward, its implementation in functioning systems remains difficult for most, regardless of expertise. More recently, however, developments such as SmartMATE have emerged which aim to assist users in creating their own customized SMT systems and thus reduce the learning curve associated with SMT. In addition to commercial uses, translator training stands to benefit from such increased levels of inclusion and access to state-of-the-art approaches to MT. In this paper we draw on experience in developing and evaluating a new syllabus in SMT for a cohort of post-graduate student translators: we identify several issues encountered in the introduction of student translators to SMT, and report on data derived from repeated measures questionnaires that aim to capture data on students’ self-efficacy in the use of SMT. Overall, results show that participants report significant increases in their levels of confidence and knowledge of MT in general, and of SMT in particular. Additional benefits – such as increased technical competence and confidence – and future refinements are also discussed