27,592 research outputs found
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Web-based writing support: making it useable for distance teachers
This paper considers the issues that distance teachers in higher education who are not writing specialists face in supporting their studentsā academic writing development. We discuss the usefulness of open web-based writing support resources, and propose the need for a system that serves as an interface with these resources. Such a system should help teachers to make quick selections of materials that can be offered to students to address specific problems in the studentsā assignments. We consider principles for the design of such a system, based on the experience of building and testing a small prototype for tutors on an Open University Masters in Education course
The OU Linked Open Data: production and consumption
The aim of this paper is to introduce the current efforts toward the release and exploitation of The Open University's (OU) Linked Open Data (LOD). We introduce the work that has been done within the LUCERO project in order to select, extract and structure subsets of information contained within the OU data sources and migrate and expose this information as part of the LOD cloud. To show the potential of such exposure we also introduce three different prototypes that exploit this new educational resource: (1) the OU expert search system, a tool focused on fnding the best experts for a certain topic within the OU staff; (2) the Buddy Study system, a tool that relies on Facebook information to identify common interest among friends and recommend potential courses within the OU that `buddies' can study together, and; (3) Linked OpenLearn, an application that enables exploring linked courses, Podcasts and tags to OpenLearn units. Its aim is to enhance the browsing experience for students, by detecting relevant educational resources on fly while reading an OpenLearn unit
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Capturing and Exploiting Citation Knowledge for the Recommendation of Scientific Publications
With the continuous growth of scientific literature, it is becoming increasingly challenging to discover relevant scientific publications from the plethora of available academic digital libraries. Despite the current scale, important efforts have been achieved towards the research and development of academic search engines, reference management tools, review management platforms, scientometrics systems, and recommender systems that help finding a variety of relevant scientific items, such as publications, books, researchers, grants and events, among others.
This thesis focuses on recommender systems for scientific publications. Existing systems do not always provide the most relevant scientific publications to users, despite they are present in the recommendation space. A common limitation is the lack of access to the full content of the publications when designing the recommendation methods. Solutions are largely based on the exploitation of metadata (e.g., titles, abstracts, lists of references, etc.), but rarely with the text of the publications. Another important limitation is the lack of time awareness. Existing works have not addressed the important scenario of recommending the most recent publications to users, due to the challenge of recommending items for which no ratings (i.e., user preferences) have been yet provided. The lack of evaluation benchmarks also limits the evolution and progress of the field.
This thesis investigates the use of fine-grained forms of citation knowledge, extracted from the full textual content of scientific publications, to enhance recommendations: citation proximity, citation context, citation section, citation graph and citation intention. We design and develop new recommendation methods that incorporate such knowledge, individually and in combination.
By conducting offline evaluations, as well as user studies, we show how the use of citation knowledge does help enhancing the performance of existing recommendation methods when addressing two key tasks: (i) recommending scientific publications for a given work, and (ii) recommending recent scientific publications to a user. Two novel evaluation benchmarks have also been generated and made available for the scientific community
Young people and the evaluation of information on the World Wide Web: Principles, practice and beliefs
A recurrent theme in LIS literature is the tendency of young people not to evaluate rigorously the information with which they come into contact. Although many information literacy models stress the need to take a critical approach, the reality of behaviour is often very different. Recent research conducted in an English high school has explored the importance that teenagers attach to ten particular evaluative criteria. 149 youngsters contributed data via an online questionnaire. Participants felt that information on the Web should be current/topical, free from spelling and grammatical errors and easily verifiable elsewhere but authorship was much less of a priority to them. The findings are likely to be of special relevance to information literacy teachers who are defining priorities for their own programmes
Discovery Is Never By Chance: Designing for (Un)Serendipity
Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by āassociation-huntingā agents. We propose considering not only the inventorās role in perceiving serendipity, but also how that inventorās perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately
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