A structured model metametadata technique to enhance semantic searching in metadata repository

This paper discusses on a novel technique for semantic searching and retrieval of information about learning materials. A novel structured metametadata model has been created to provide the foundation for a semantic search engine to extract, match and map queries to retrieve relevant results. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. The use of ontological views assists the pedagogical content of metadata extracted from learning objects by using the control vocabularies as identified from the metametadata taxonomy. The use of metametadata (based on the metametadata taxonomy) supported by the ontologies have contributed towards a novel semantic searching mechanism. This research has presented a metametadata model for identifying semantics and describing learning objects in finer-grain detail that allows for intelligent and smart retrieval by automated search and retrieval software

Generating collaborative systems for digital libraries: A model-driven approach

This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework

A digital library of language learning exercises

Recent years have seen widespread adoption of the Internet for language teaching and learning. Interactive systems on the World-Wide Web provide useful alternatives to face-to-face tuition, and both teachers and learners can benefit from the exercises available. However, although there is a wealth of suitable material, it is hard to find because it is scattered around the web. Moreover, teachers are restricted by the material that is available, and cannot provide their own. To tackle these problems we have constructed a digital library of language learning exercises that presents students with different kinds of exercise, and also lets teachers contribute new material. We first reviewed existing language learning systems on the web in order to develop a taxonomy of exercise types used for language activity. A prototype, ELLE, based on this taxonomy, provides various kinds of interactive exercises using material that teachers submit. The system has been evaluated by practicing language teachers

Learning roadmap studio : new approaches and strategies for efficient learning and training processes

Learning systems have emerged in a set of different information systems, oriented for different kinds of organizations and institutions, such as learning management systems, knowledge management systems and learning content management systems, which can be integrated or merged with others. From past experience, it has been denoted that strategies and pedagogical processes are tasks that can be created, enriched and boosted by actors who participate in learning and training processes: course managers, teachers and students. The challenge posed to the different actors involved also accelerates the changes that have been happening in education and training, empowering a society based on knowledge. Initiatives such as eLearning (EU Comission 2000), eLearningEurope, eTwinning and Education Observatories are an evidence of this challenge. Platforms, applications, tools and systems must respond to challenges that those actors face nowadays: heterogeneous target audiences, in terms of student profiles, number of participants, differentiated contents and schedules to achieve knowledge, outcomes and competences. Thus, a prototype application, named Learning Roadmap Studio (LRMS), has been developed and deployed at Aveiro Norte Polytechnic School of the University of Aveiro, in order to suppress gaps in learning processes and to power better learning and training. It represents a new challenge for the University of Aveiro for higher education and is already being tested. At its core is the concept of “learning roadmaps” that act upon two fundamental axes: education and learning. For the teachers, it aims at becoming a self-supporting tool that stimulates the organization and management of the course materials (lectures, presentations, multimedia content, and evaluation materials, amongst others). For the students, the learning roadmap aims at promoting self-study and supervised study, endowing the pupil with the capabilities to find the relevant information and to capture the concepts in the study materials. The outcome will be a stimulating learning process together with an organized management of those materials. It is not intended to create new learning management systems. Instead, it is presented as an application that enables the edition and creation of learning processes and strategies, giving primary relevance to teachers, instead of focusing on tools, features and contents

trackr: A Framework for Enhancing Discoverability and Reproducibility of Data Visualizations and Other Artifacts in R

Research is an incremental, iterative process, with new results relying and building upon previous ones. Scientists need to find, retrieve, understand, and verify results in order to confidently extend them, even when the results are their own. We present the trackr framework for organizing, automatically annotating, discovering, and retrieving results. We identify sources of automatically extractable metadata for computational results, and we define an extensible system for organizing, annotating, and searching for results based on these and other metadata. We present an open-source implementation of these concepts for plots, computational artifacts, and woven dynamic reports generated in the R statistical computing language

Library Cataloguing and Role and Reference Grammar for Natural Language processing Applications

Several potential application of natural language processing have proven to be intractable. In this paper, we provide and overview of methods from library cataloguing and linguistics that have not yet been adopted by the natural language processing community and which could be used to help solve some of these problems

An explicit model for learning to structure and analyze decisions by judges

Legal practitioners and legal scientists need to have knowledge of the general rules that apply in the legal system. This involves both knowledge of the legislation and knowledge of the decisions by judges that function as general rules of law. Law students preparing themselves for the legal profession need to acquire these kinds of knowledge. A student has to have knowledge about where to look for decisions, understand the structure of decisions and learn to determine what makes a decision relevant to the body of applicable rules in the legal system. Legal education primarily aims at acquiring insight in the legal sources, their history and background. This basic knowledge is of great importance; legal problem solving is hardly possible without an understanding of the legal knowledge. To illustrate the use of this knowledge in practice, teachers work through decisions as examples. However, it is difficult, if not impossible, to learn by explanation or by imitation alone. A more effective way to obtain expertise is by actually performing the task, i.e. students should do the exercises, while the teacher provides feedback on their solutions. For effective learning, also the solution process should be monitored and provided with feedback. Furthermore it is desirable for students to be able to ask for help at any time during the process. They should also be able to practice over and over again. An ideal situation would have a teacher available for every student, monitoring the student while practicing and providing support where and whenever necessary. However, this being not practically feasible, the second best option is to offer the student electronic support. CASE (Case Analysis and Structuring Environment) is an environment where a law student can practice with finding decisions, with structuring its text and with analysing the decision in order to be able to determine in what way it adds to the body of applicable rules in the legal system. CASE is developed using a principled and structured design approach. A short description of this approach is followed by an analysis of the learning task, the difficulties law students experience and the remedies proposed on the basis of both the task analysis and the stated difficulties. This is followed by a description of architecture, functionality, platform and implementation of CASE and a description of a session with CASE and future work