Semantic Modeling for Group Formation

Group formation has always been a subject of interest in collaborative learning research. As it is concerned with assigning learners to the groups that maximize their benefits, computer-supported group formation can be viewed in this context as an active personalization for the individual as an entity within the group. While applying this personalization to all students in the class can cause conflicts due to the differences of needs and interests between the individuals, negotiating the allocations to groups to reach consensus can be a very challenging task. The automated process of grouping students while preserving the individual’s personalization needs to be supported by an appropriate learner model. In this paper, we propose a semantic learner model based on the Friend of Friend (FOAF) ontology, a vocabulary for mapping social networks. We discuss the model as we analyse the different types of groups and the learners’ features that need to be modeled for each of these types

Dark retweets: investigating non-conventional retweeting patterns

Retweets are an important mechanism for recognising propagation of information on the Twitter social media platform. However, many retweets do not use the official retweet mechanism, or even community established conventions, and these "dark retweets" are not accounted for in many existing analysis. In this paper, a comprehensive matrix of tweet propagation is presented to show the different nuances of retweeting, based on seven characteristics: whether it is proprietary, the mechanism used, whether it is directed to followers or non-followers, whether it mentions other users, if it is explicitly propagating another tweet, if it links to an original tweet, and what is the audience it is pushed to. Based on this matrix and two assumptions of retweetability, the degrees of a retweet's "darkness" can be determined. This matrix was evaluated over 2.3 million tweets and it was found that dark retweets amounted to 12.86% (for search results less than 1500 tweets per URL) and 24.7% (for search results including more than 1500 tweets per URL) respectively. By extrapolating these results with those found in existing studies, potentially thousands of retweets may be hidden from existing studies on retweets

The Chawton House Experience - Augmenting the Grounds of a Historic Manor House

Museum research is a burgeoning area of research where ubiquitous computing has already made an impact in enhancing user experiences. The goal of the Chawton House project is to extend this work by introducing ubicomp not to a museum as such, but a historic English manor house and its grounds. This presents a number of novel challenges relating to the kinds of visitors, the nature of visits, the specific character of the estate, the creation of a persistent and evolving system, and the process of developing it together with Chawton House staff

Teaching the Grid: Learning Distributed Computing with the M-grid Framework

A classic challenge within Computer Science is to distribute data and processes so as to take advantage of multiple computers tackling a single problem in a simultaneous and coordinated way. This situation arises in a number of different scenarios, including Grid computing which is a secure, service-based architecture for tackling massively parallel problems and creating virtual organizations. Although the Grid seems destined to be an important part of the future computing landscape, it is very difficult to learn how to use as real Grid software requires extensive setting up and complex security processes. M-grid mimics the core features of the Grid, in a much simpler way, enabling the rapid prototyping of distributed applications. We describe m-grid and explore how it may be used to teach foundation Grid computing skills at the Higher Education level and report some of our experiences of deploying it as an exercise within a programming course

Towards a semantic modeling of learners for social networks

The Friend of a Friend (FOAF) ontology is a vocabulary for mapping social networks. In this paper we propose an extension to FOAF in order to allow it to model learners and their social networks. We analyse FOAF alongside different learner modeling standards and specifications, and based on this analysis we introduce a taxonomy of the different features found in those models. We then compare the learner models and FOAF against the taxonomy to see how their characteristics have been shaped by their purpose. Based on this we propose extensions to FOAF in order to produce a learner model that is capable of forming the basis of a semantic social network.<br/

The horse before the cart: improving the accuracy of taxonomic directions when building tag hierarchies

Content on the Web is huge and constantly growing, and building taxonomies for such content can help with navigation and organisation, but building taxonomies manually is costly and time-consuming. An alternative is to allow users to construct folksonomies: collective social classifications. Yet, folksonomies are inconsistent and their use for searching and browsing is limited. Approaches have been suggested for acquiring implicit hierarchical structures from folksonomies, however, but these approaches suffer from the ‘popularity-generality’ problem, in that popularity is assumed to be a proxy for generality, i.e. high-level taxonomic terms will occur more often than low-level ones. To tackle this problem, we propose in this paper an improved approach. It is based on the Heymann–Benz algorithm, and works by checking the taxonomic directions against a corpus of text. Our results show that popularity works as a proxy for generality in at most 90.91% of cases, but this can be improved to 95.45% using our approach, which should translate to higher-quality tag hierarchy structure

How should we measure online learning activity?

The proliferation of Web-based learning objects makes finding and evaluating resources a considerable hurdle for learners to overcome. While established learning analytics methods provide feedback that can aid learner evaluation of learning resources, the adequacy and reliability of these methods is questioned. Because engagement with online learning is different from other Web activity, it is important to establish pedagogically relevant measures that can aid the development of distinct, automated analysis systems. Content analysis is often used to examine online discussion in educational settings, but these instruments are rarely compared with each other which leads to uncertainty regarding their validity and reliability. In this study, participation in Massive Open Online Course (MOOC) comment forums was evaluated using four different analytical approaches: the Digital Artefacts for Learning Engagement (DiAL-e) framework, Bloom's Taxonomy, Structure of Observed Learning Outcomes (SOLO) and Community of Inquiry (CoI). Results from this study indicate that different approaches to measuring cognitive activity are closely correlated and are distinct from typical interaction measures. This suggests that computational approaches to pedagogical analysis may provide useful insights into learning processes

Generating adaptive hypertext content from the semantic web

Accessing and extracting knowledge from online documents is crucial for therealisation of the Semantic Web and the provision of advanced knowledge services. The Artequakt project is an ongoing investigation tackling these issues to facilitate the creation of tailored biographies from information harvested from the web. In this paper we will present the methods we currently use to model, consolidate and store knowledge extracted from the web so that it can be re-purposed as adaptive content. We look at how Semantic Web technology could be used within this process and also how such techniques might be used to provide content to be published via the Semantic Web

Naming in OHP

Naming is a key issue in any distributed system. In particular, with the Open Hypermedia Systems Working Group's efforts towards openness and interoperability in Open Hypermedia Systems (OHS) resulting in the need for (globally) valid names for all types of resources the issue of naming has become increasingly important. In this position paper we examine the issues involved in naming and a naming proposal to be used within the Open Hypermedia Protocol (OHP)