STELLAR (Semantic Technologies Enhancing the Lifecycle of Learning Resources): Jisc Final Report

[Project Summary] As one of the earliest distance learning providers The Open University (OU) has a rich heritage of archived learning materials. An ever increasing amount of that is in digital form and is being deposited with the University Archive. This growth has been driven by digitisation activity from projects such as AVA (Access to Video Assets) and the Fedora-based Open University Digital Library ‘a place to discover digital and digitised archival content from the OU Library, from videos and images to digitised documents’. Other digital content is being captured from web archiving activities, such as work to preserve Moodle Virtual Learning Environment course websites. An evidence based understanding is required to inform digital preservation policies, curation strategy and investment in digital library development. Following the Pre-enhancement, Enhancement and Post-enhancement methodology set out by Jisc, STELLAR adopted the model of a balanced scorecard to ascertain the value ascribed to the non-current learning materials. Four aspects were considered: Personal and professional perspectives of value; Value to the Higher Educational and academic communities; Value to internal processes and cultures; Financial perspectives of value. The outcomes of the survey indicated that stakeholders place a high value on the materials, and that they perceived them to have value in all areas evaluated. Three OU courses were chosen from the digital library for the transformation stage. These materials were enhanced and transformed into RDF, a process that required more extensive metadata expertise and effort than was expected. Following enhancement the RDF was accessed through a tool called DiscOU, created by a member of the project team from the OU’s Knowledge Media Institute. DiscOU uses both linked data and a semantic meaning engine to analyse the meaning of the text in a search query. This is matched against the meaning of the content derived from an index of the full-text of the digital library content. In the final stage stakeholders were asked through a survey and series of workshops to use the DiscOU proof-of-concept tool to assess their perception of the value of this transformation. This has revealed that overall, academics and other stakeholders in the university do believe that the value of the selected materials was positively impacted by the application of semantic technologies

Library resources, student success and the distance-learning university

Purpose - Research at the Open University Library Services has been investigating the relationshipbetween access to online library resources and student success to help to understand whether there is asimilar relationship at a distance-learning university to that found in other institutions. Design/methodology/approach - A small library data project was established to investigate this area.The study analysed online library resource data from access logs from the EZproxy and OpenAthens systems. A data set of 1.7 million online resource accesses was combined with student success data for around 90,000 undergraduate students and a series of analyses undertaken.Findings The study found a pattern where students who are more successful are accessing more library resources. A chi-square test indicated a statistically significant association between library resource accesses and module result, while an ANOVA test suggests a medium sized effect. The study also found that 152 (76%) of 199 modules had a small, medium or large positive correlation between student success, measured by the overall assessment score, and online library resource accesses.Originality/value - This study builds on evidence that there is a relationship between library use and student success by showing that this relationship extends to the setting of a non-traditional, innovative library service supporting part-time distance learners

Can an excellent distance learning library service support student retention and how can we find out?

Higher Education libraries have traditionally sought to be able to demonstrate the impact their services have on student attainment. This is particularly important in the current economic climate where libraries frequently have to defend their budgets in the face of financial constraints, whilst needing to demonstrate better value for money to students who are now paying more for higher education. A number of studies around the world have been successful in harnessing data around library usage to begin to show strong correlation with student retention and final results. But most of these studies rely on data from book loans and engagement with a physical library, and where students follow a traditional three or four year degree course. This is challenging for a distance education institution, like the UK’s Open University (OU), where most students rarely or never visit the physical Open University Library and where study and assessment patterns can differ from those of traditional universities. This paper outlines the efforts of staff at The Open University Library to embed their services and resources into the learning experience of their distance learners, and to aspire to find ways of demonstrating their contribution to student retention and achievement. While there is huge potential in the amount and range of data available, the challenge is to identify an appropriate model that allows The Open University Library to demonstrate how Library Services impacts on student retention, attainment and achievement

Boom for a load handling machine

A boom (12) for a load handling machine (10), the boom (12) has a mounting (20) by which the boom (12) is mounted on a body (11) of the machine (10), and first and second telescoped sections (24), the boom (12) carrying in use, at or towards its outermost end, a load handling implement (27), the second boom (24) section being telescoped within the first section and being extendible and retractable relative to the first boom sections (22) by actuating means, characterised in that at least one of the boom sections (22, 25) includes a plurality of walls (25a, 25b, 25c, 25d) each being a web made at least predominantly of a composite material, and where adjacent walls meet there being bearing members (30/35; 30a) which extend along a substantial length of the boom section (22, 25) to provide bearing surfaces (31) during sliding of the second boom section (25) relative to the first boom section (22)

A Framework for Effective Corporate Communication after Cyber Security Incidents

A major cyber security incident can represent a cyber crisis for an organisation, in particular because of the associated risk of substantial reputational damage. As the likelihood of falling victim to a cyberattack has increased over time, so too has the need to understand exactly what is effective corporate communication after an attack, and how best to engage the concerns of customers, partners and other stakeholders. This research seeks to tackle this problem through a critical, multi-faceted investigation into the efficacy of crisis communication and public relations following a data breach. It does so by drawing on academic literature, obtained through a systematic literature review, and real-world case studies. Qualitative data analysis is used to interpret and structure the results, allowing for the development of a new, comprehensive framework for corporate communication to support companies in their preparation and response to such events. The validity of this framework is demonstrated by its evaluation through interviews with senior industry professionals, as well as a critical assessment against relevant practice and research. The framework is further refined based on these evaluations, and an updated version defined. This research represents the first grounded, comprehensive and evaluated proposal for characterising effective corporate communication after cyber security incidents

Boom for a load handling machine

A boom for a load handling machine, the boom has a mounting by which the boom is mounted on a body of the machine, and at least first and second telescoped sections. In use, the boom carries a load handling implement at or towards its outermost end. The first boom section is telescoped within the second section and is extendible and retractable relative to the second boom section by an actuator. At least the first boom section includes walls made at least predominantly of a composite material. A bearing member is located where adjacent walls meet to extend along a substantial length of the first boom section to provide bearing surfaces during sliding of the first boom section relative to the second boom section. Bearings also may be provided on the interior of the second boom section to further protect the first boom section

The Anatomy of Online Deception: What Makes Automated Text Convincing?

Technology is rapidly evolving, and with it comes increasingly sophisticated bots (i.e. software robots) which automatically produce content to inform, influence, and deceive genuine users. This is particularly a problem for social media networks where content tends to be extremely short, informally written, and full of inconsistencies. Motivated by the rise of bots on these networks, we investigate the ease with which a bot can deceive a human. In particular, we focus on deceiving a human into believing that an automatically generated sample of text was written by a human, as well as analysing which factors affect how convincing the text is. To accomplish this, we train a set of models to write text about several distinct topics, to simulate a bot's behaviour, which are then evaluated by a panel of judges. We find that: (1) typical Internet users are twice as likely to be deceived by automated content than security researchers; (2) text that disagrees with the crowd's opinion is more believably human; (3) light-hearted topics such as Entertainment are significantly easier to deceive with than factual topics such as Science; and (4) automated text on Adult content is the most deceptive regardless of a user's background