Gaia is a cornerstone mission in the science programme of the European Space Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page.

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues -a realisation of the Tycho-Gaia Astrometric Solution (TGAS) -and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr −1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr −1 . For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.

This article reviews the research and evidence about multi-touch tables to provide an analysis of their key design features and capabilities and how these might relate to their use in educational settings to support collaborative learning. A typology of design features is proposed as a synthesis of the hardware and physical characteristics of the tables so that the longevity of these factors and the associated analysis can be better preserved, particularly in relation to the range of ways in which they may be used collaboratively in classrooms. The variability of features relating to software is also analysed and key pedagogic issues identified. The aim that underpins this review is to relate the design of the technical features with key pedagogic issues concerning the use of digital technologies in classrooms, so as to provide a more robust basis for their integration in classrooms in terms of their potential to support or to improve learning.

The development of multi-touch tables, an emerging technology for classroom learning, offers valuable opportunities to explore how its features can be designed to support effective collaboration in schools. In this study, small groups of 10-to 11-year-old children undertook a history task where they had to connect various pieces of information about a mining accident to reach a consensus about who had been responsible. Their interaction using traditional resources was compared with their interaction when using a multi-touch table. Analysis suggests that the design and capabilities of the multi-touch technology offers some key features that supported the collaboration and interaction of the participants, particularly in the early stages of the task. Some of these features appear to provide new opportunities for collaboration and interaction, which were different from the interactions observed in the paper-based groups. These features of the multi-touch surface therefore appear to support effective interaction between the pupils. IntroductionLarge multi-touch surfaces offer opportunities to explore how they can support collaboration and learning. The technology enables several people to control and interact with the information on the same screen, simultaneously (Shen et al, 2009). This opportunity for joint control, rather than the single point of control provided by a mouse or single touch screen, is clearly suited to collaboration around the table surface (see Higgins, Mercier, Burd & Hatch, 2011). It provides new opportunities to explore how learners collaborate during educational tasks in a digital environment. In this paper, we explore differences in interactions between groups working on a multi-touch table and groups working on a paper-based version of the same task. This was intentionally an attempt to "computerise a hitherto pencil-and-paper activity" (Noss, Healy & Hoyles, 1997) and an explicit stage in our programme of research. We particularly wanted to explore how the multi-touch compared with similar paper-based activities as a starting point to develop more pedagogically effective activities with more complex resources and interactions. However, as a new educational technology, understanding how learners use the multi-touch environment was limited, so it was important to establish a baseline with activities comparable with those in traditional classrooms. This is to enable successful integration of these technologies

Gender differences in the pursuit of technology careers are a current issue of concern. We report on two studies that use surveys, drawings and interviews to examine sixth-and eighthgrade students' perceptions of knowledgeable computer users and their self-perception as a computer-type person. In Study 1, participants were asked to generate representations of computer users in pictures or words. The results indicate that the majority of representations were of male users and they frequently wore glasses. Students of both genders were more likely to draw males. Eighth-grade students' representations included more stereotypical features than those of sixth-grade students. In Study 2, students were asked whether they believed that there was such a thing as a computer-type person and whether they perceived themselves to be one. Eighty per cent of students rejected this characterization. They differed from students who accepted it in their levels of past experience, their confidence, and the probability that they shared their knowledge with others. The results of both studies suggest that while there is a male image of computer science in general, it is not overly negative and students' self-perception is not governed by their own gender as much as by other variables.