This study evaluated the versatility of the MoJoXlab in conducting clinical movement analysis using inertial sensors from various manufacturers, including low-cost, non-proprietary, and open-protocol wearable options. Data were collected from 15 healthy participants who performed a range of clinically relevant activities and exercises using two sets of sensors. Dynamic time warping analysis of the sensor signals suggested that the collected dataset could be used for further algorithm development. The findings demonstrate that the current iteration of MoJoXlab can perform movement analysis using quaternions from sensors of any manufacturer. However, the accuracy of the resulting joint angles is not yet suitable for clinical applications across all sensor types, and only Xsens and NGIMU sensors are currently supported. This study also explored the potential for reducing the number of sensors required by MoJoXlab, which currently uses seven sensors to calculate joint angles for three joints (hip, knee and ankle) on both sides of the body. The creation of a comprehensive databank for lower limb movement analysis algorithms was an additional outcome of this work. Further research and development are necessary to expand MoJoXlab’s support for multiple sensor manufacturers and improve the accuracy of joint angle calculations for clinical applications.

Predictive learning analytics (PLA) dashboards have been used by teachers to identify students at risk of failing their studies and provide proactive support. Yet, very few of them have been deployed at a large scale or had their use studied at a mature level of implementation. In this study, we surveyed 366 distance learning university teachers across four faculties three years after PLA has been made available across university as business as usual. Informed by the Unified Theory of Acceptance and Use of Technology (UTAUT), we present a context-specific version of UTAUT that reflects teachers’ perceptions of PLA in distance learning higher education. The adoption and use of PLA was shown to be positively influenced by less experience in teaching, performance expectancy, self-efficacy, positive attitudes, and low anxiety, while negatively influenced by a lack of facilitating conditions and low effort expectancy, indicating that the type of technology and context within which it is used are significant factors determining our understanding of technology usage and adoption. This study provides significant insights as to how to design, apply and implement PLA with teachers in higher education.

Data integration is the dominant use case for RDF Knowledge Graphs. However, Web resources come in formats with weak semantics (for example, CSV and JSON), or formats specific to a given application (for example, BibTex, HTML, and Markdown). To solve this problem, Knowledge Graph Construction (KGC) is gaining momentum due to its focus on supporting users in transforming data into RDF. However, using existing KGC frameworks result in complex data processing pipelines, which mix structural and semantic mappings, whose development and maintenance constitute a significant bottleneck for KG engineers. Such frameworks force users to rely on different tools, sometimes based on heterogeneous languages, for inspecting sources, designing mappings, and generating triples, thus making the process unnecessarily complicated. We argue that it is possible and desirable to equip KG engineers with the ability of interacting with Web data formats by relying on their expertise in RDF and the well-established SPARQL query language [ 2 ]. In this article, we study a unified method for data access to heterogeneous data sources with Facade-X, a meta-model implemented in a new data integration system called SPARQL Anything. We demonstrate that our approach is theoretically sound, since it allows a single meta-model, based on RDF, to represent data from (a) any file format expressible in BNF syntax, as well as (b) any relational database. We compare our method to state-of-the-art approaches in terms of usability (cognitive complexity of the mappings) and general performance. Finally, we discuss the benefits and challenges of this novel approach by engaging with the reference user community.

Social media is a common place for people to post and share digital reflections of their life events, including major events such as getting married, having children, graduating, etc. Although the creation of such posts is straightforward, the identification of events on online media remains a challenge. Much research in recent years focused on extracting major events from Twitter, such as earthquakes, storms, and floods. This paper however, targets the automatic detection of personal life events, focusing on five events that psychologists found to be the most prominent in people lives. We define a variety of features (user, content, semantic and interaction) to capture the characteristics of those life events and present the results of several classification methods to automatically identify these events in Twitter. Our proposed classification methods obtain results between 0.84 and 0.92 F1-measure for the different types of life events. A novel contribution of this work also lies in a new corpus of tweets, which has been annotated by using crowdsourcing and that constitutes, to the best of our knowledge, the first publicly available dataset for the automatic identification of personal life events from Twitter.

Museum professionals create exhibitions that tell stories about museum objects. The exhibits are usually arranged to reveal the relationships between them and to highlight the story being told. But sometimes objects are in fixed places and cannot be re-positioned. This paper presents a solution to the problem of how to tell conceptually coherent stories across a set of fixed artworks within the grounds of a museum and to reveal relationships between them. A study was conducted in which QR codes were used to provide access, through mobile devices, to online information about artworks. A notion of conceptual coherence and coverage of artworks was used to construct online story trails linking artworks to each other based on overlap of key story features such as setting, people and themes. Visitors were free at all times to follow their own path through the museum grounds and choose which objects they wanted to stop and engage with. The QR code trail was evaluated on an outdoor art trail at the Irish Museum of Modern Art (IMMA). Analytics of page access were used to identify how often visitors scanned QR codes and to what extent, once they had visited the online information about an artwork, they were likely to follow the story links.

Most Knowledge Representation (KR) research follows a topdown approach: i) formalisms are designed on the basis of modelling needs and computational considerations, and ii) tools and applications based on these formalisms are realized and tested on application domains. As a result, there has traditionally been little attention in the KR research community to user issues, in particular to the usability of alternative modelling solutions. When statements about the intuitiveness of different solutions are found in the literature, these tend to reflect an author's epistemological standpoint, rather than any concrete user experience. In this paper we take a bottom-up, user-centric perspective and we report on an empirical study where subjects have been asked to represent temporal information and have been provided with alternative design patterns to do so. The study shows that, depending on their experience and level of expertise in KR, users tend to select different patterns for the given modelling problems. In particular, experts appear to choose on the basis of representation power, while naïve users appear to select on the basis of surface features and perceived user-friendliness. Interestingly, while some patterns are indeed perceived to be more intuitive than others, these considerations seem to apply primarily to less experienced users. Indeed, our findings appear to indicate that experts consider issues of 'intuitiveness' as secondary and, in contrast with naïve users, may be happy to apply patterns, which can be regarded as counter-intuitive, if they provide the right tool for the job.

Existing metadata schemes and content management systems used by museums focus on describing the heritage objects that the museum holds in its collection. These are used to manage and describe individual heritage objects according to properties such as artist, date and preservation requirements. Curatorial narratives, such as physical or online exhibitions tell a story that spans across heritage objects and have a meaning that does not necessarily reside in the individual heritage objects themselves. Here we present curate , an ontology for describing curatorial narratives. This draws on structuralist accounts that distinguish the narrative from the story and plot, and also a detailed analysis of two museum exhibitions and the curatorial processes that contributed to them. storyspace , our web based interface and API to the ontology, is being used by curatorial staff in two museums to model curatorial narratives and the processes through which they are constructed.

This paper proposes curation as an inquiry method for young learners who are learning history using web-based heritage resources and other online content. It introduces the QrAte tool, similar to many online social curation tools, but with added functionality for creating and supporting historical inquiry tasks. QrAte assists a learner in identifying key concepts related to an inquiry process, in asking inquiry questions and in locating and analyzing data sources, then extracting relevant information. QrAte helps the user to organize and visualize collected data and to curate an output that provides an answer to the question of the inquiry. The curated stories can be shared, whereby the content can be a 'seed' for future learners to use in their own inquiry and curation processes.

Book synopsis: Brand New Book. This publication covers papers presented at the Artificial Intelligence in Education conference 2009 (AIED). AIED2009 is part of an ongoing series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. The conference provides opportunities for the cross-fertilization of techniques from many fields that make up this interdisciplinary research area, including: artificial intelligence, computer science, cognitive and learning sciences, education, educational technology, psychology, philosophy, sociology, anthropology, linguistics and the many domain-specific areas for which AIED systems have been designed and evaluated. AIED2009 focuses on the theme 'Building learning systems that care: from knowledge representation to affective modelling'. The key research question is how to tackle the complex issues related to building learning systems that care, ranging from representing knowledge and context to modelling social, cognitive, metacognitive and affective dimensions.This requires multidisciplinary research that links theory and technology from artificial intelligence, cognitive science and computer science with theory and practice from education and the social sciences.

Inquiry learning involves the learner acquiring new concepts and skills by means of carrying out an investigation. Some previous studies have looked into how these learning activities can be carried out on source materials, such as web documents, and the provision of appropriate scaffolding to guide the learning process. Here we consider how intelligent support can be provided to guide the learner in analysing source materials and building knowledge from their interpretation. An important feature of our case study is that the source materials are images, potentially having greater variation in how they are interpreted and therefore increasing the need for intelligent support. Intelligent support provided by our system can identify patterns and inconsistencies in the learner's interpretation and knowledge building, and offer recommendations based on comparison with a reference model. The recommendations derived from a reference model aim to guide the learner in reviewing and revising their interpretation of the images and the implications of these for their inferences, rather than directly providing a “right” or “wrong” evaluation of their answer.

Scene-Driver is a software toolkit for the reuse of broadcast animation content to provide new engaging experiences for children. It has been developed and tested using content from the children's television series "Tiny Planets". Scene-Driver can be used to produce variations on a domino-like game. When playing, the child selects from a set of tiles that depict, for example, characters from the series. The child manipulates the direction of a story in the Tiny Planet world by their choice of tile. The successful selection of a tile will result in a scene from the show being played. A scene is defined as a section from an episode which has certain self-contained narrative elements such as conflict introduction, conflict resolution or comedic event. A scene-supervisor uses these descriptions to ensure that as well as having all the properties prescribed by the child's choice of tile, the scenes are presented in a coherent order according to certain plot and directorial principles. Inter-scene continuity is provided in the form of transition scenes which depict the departure and arrival of relevant characters between one scene and the next. Preliminary evaluations have demonstrated the potential of Scene-Driver to produce engaging and usable games based on broadcast content for young children.

Increasingly heritage institutions are making digital artifacts available to the general public and research groups to promote the active exploration of heritage and encourage visits to heritage sites. Stories, such as folklore and first person accounts form a useful and engaging heritage resource for this purpose. Story Fountain provides intelligent support for the exploration of digital stories. The suite of functions provided in Story Fountain together support the investigation of questions and topics that require the accumulation, association or induction of information across the story archive. Story Fountain provides specific support toward this end such as for comparing and contrasting story concepts, the presentation of story paths between concepts, and mapping stories and events according to properties such as who met whom and who lived where.

Integrating working and learning is seen as a desirable alternative to traditional training regimes. An integrated approach to working and learning is more gradual, contextual, problem oriented and cost effective. Knowledge technology aims to catalyze workplace learning, but requires the right organisational culture and brings additional costs regarding the articulation, representation and transmission of knowledge. Our approach reduces these costs by making articulation a natural part of collaborative working, designing for both informal and formal knowledge, and facilitating the transition of socially situated knowledge through enriched documents. To be successful, our approach has certain prequesites concerning organisational culture, and the nature of shared documents, organisational knowledge and work activities.

Engineering design is a complex activity, relying heavily on know-how gained from personal experience. Competitive pressures and new technology are making further demands on the skills and experience of designers, as effective knowledge reuse in design is seen as increasingly vital, and the work of design teams is often a collaborative and distributed activity. University students with a thorough knowledge of the engineering domain can be ill prepared for professional practice, with its increasing reliance on skills and know-how as well as knowledge of theory. Our approach aims to better prepare students for professional practice, through hands-on experience of design reuse, participation in distributed collaboration, and the development of presentation and documentation skills. Our case-study in the domain of modelling engineering systems, in which the course materials themselves are evolving and distributed, has ramifications for the publication model of educational materials, and the way students should be prepared for working life.