105,635 research outputs found

    A Collaborative Lecture in Information Retrieval for Students at Universities in Germany and Switzerland

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    K3, work in progress, is an acronym for Kollaboration (collaboration), Kommunikation (communication), and Kompetenz (competence). K3 provides a platform in the context of knowledge management to support collaborative knowledge production in learning environments. The underlying hypothesis states that collaborative discourse conciliates information as well as communication competence in learning contexts. The collaborative, communicative paradigm of K3 is implemented by asynchronous communication tools as a means of constructivist learning methodology. In this paper we will describe a K3 course. The lecture was organized and carried out at two places in two different countries (Germany and Switzerland) with students from different universities in the context of Library and Information Science. The paper informs about the management of the lecture and about the problems we had to run the lecture at two places. The circumstances in coordinating the presentations, the exercises, the examinations and evaluation, and the time schedule are presented. The conclusions of the lecturers and the results of a questionnaire for the students are explained in detail

    The relationship between IR and multimedia databases

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    Modern extensible database systems support multimedia data through ADTs. However, because of the problems with multimedia query formulation, this support is not sufficient.\ud \ud Multimedia querying requires an iterative search process involving many different representations of the objects in the database. The support that is needed is very similar to the processes in information retrieval.\ud \ud Based on this observation, we develop the miRRor architecture for multimedia query processing. We design a layered framework based on information retrieval techniques, to provide a usable query interface to the multimedia database.\ud \ud First, we introduce a concept layer to enable reasoning over low-level concepts in the database.\ud \ud Second, we add an evidential reasoning layer as an intermediate between the user and the concept layer.\ud \ud Third, we add the functionality to process the users' relevance feedback.\ud \ud We then adapt the inference network model from text retrieval to an evidential reasoning model for multimedia query processing.\ud \ud We conclude with an outline for implementation of miRRor on top of the Monet extensible database system

    Digital information support for concept design

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    This paper outlines the issues in effective utilisation of digital resources in conceptual design. Access to appropriate information acts as stimuli and can lead to better substantiated concepts. This paper addresses the issues of presenting such information in a digital form for effective use, exploring digital libraries and groupware as relevant literature areas, and argues that improved integration of these two technologies is necessary to better support the concept generation task. The development of the LauLima learning environment and digital library is consequently outlined. Despite its attempts to integrate the designers' working space and digital resources, continuing issues in library utilisation and migration of information to design concepts are highlighted through a class study. In light of this, new models of interaction to increase information use are explored

    Applying science of learning in education: Infusing psychological science into the curriculum

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    The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

    An inquiry-based learning approach to teaching information retrieval

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    The study of information retrieval (IR) has increased in interest and importance with the explosive growth of online information in recent years. Learning about IR within formal courses of study enables users of search engines to use them more knowledgeably and effectively, while providing the starting point for the explorations of new researchers into novel search technologies. Although IR can be taught in a traditional manner of formal classroom instruction with students being led through the details of the subject and expected to reproduce this in assessment, the nature of IR as a topic makes it an ideal subject for inquiry-based learning approaches to teaching. In an inquiry-based learning approach students are introduced to the principles of a subject and then encouraged to develop their understanding by solving structured or open problems. Working through solutions in subsequent class discussions enables students to appreciate the availability of alternative solutions as proposed by their classmates. Following this approach students not only learn the details of IR techniques, but significantly, naturally learn to apply them in solution of problems. In doing this they not only gain an appreciation of alternative solutions to a problem, but also how to assess their relative strengths and weaknesses. Developing confidence and skills in problem solving enables student assessment to be structured around solution of problems. Thus students can be assessed on the basis of their understanding and ability to apply techniques, rather simply their skill at reciting facts. This has the additional benefit of encouraging general problem solving skills which can be of benefit in other subjects. This approach to teaching IR was successfully implemented in an undergraduate module where students were assessed in a written examination exploring their knowledge and understanding of the principles of IR and their ability to apply them to solving problems, and a written assignment based on developing an individual research proposal

    Visualization of database structures for information retrieval

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    This paper describes the Book House system, which is designed to support children's information retrieval in libraries as part of their education. It is a shareware program available on CD‐ROM or floppy disks, and comprises functionality for database searching as well as for classifying and storing book information in the database. The system concept is based on an understanding of children's domain structures and their capabilities for categorization of information needs in connection with their activities in schools, in school libraries or in public libraries. These structures are visualized in the interface by using metaphors and multimedia technology. Through the use of text, images and animation, the Book House encourages children ‐ even at a very early age ‐ to learn by doing in an enjoyable way, which plays on their previous experiences with computer games. Both words and pictures can be used for searching; this makes the system suitable for all age groups. Even children who have not yet learned to read properly can, by selecting pictures, search for and find those books they would like to have read aloud. Thus, at the very beginning of their school life, they can learn to search for books on their own. For the library community, such a system will provide an extended service which will increase the number of children's own searches and also improve the relevance, quality and utilization of the book collections in the libraries. A market research report on the need for an annual indexing service for books in the Book House format is in preparation by the Danish Library Centre A/S

    Jurimetrics: The Methodology of Legal Inquiry

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