Search (7 results, page 1 of 1)

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Abstract

Educational standards are a central focus of the current educational system in the United States, underpinning educational practice, curriculum design, teacher professional development, and high-stakes testing and assessment. Digital library users have requested that this information be accessible in association with digital learning resources to support teaching and learning as well as accountability requirements. Providing this information is complex because of the variability and number of standards documents in use at the national, state, and local level. This article describes a cataloging tool that aids catalogers in the assignment of standards metadata to digital library resources, using natural language processing techniques. The research explores whether the standards suggestor service would suggest the same standards as a human, whether relevant standards are ranked appropriately in the result set, and whether the relevance of the suggested assignments improve when, in addition to resource content, metadata is included in the query to the cataloging tool. The article also discusses how this service might streamline the cataloging workflow.

Date

22. 1.2011 14:25:32

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Abstract

Along with significant opportunities, Massively Open Online Courses (MOOCs) provide major challenges to students (keeping track of course materials and effectively interacting with teachers and fellow students), teachers (managing thousands of students and supporting their learning progress), researchers (understanding how students interact with materials and each other), and MOOC platform developers (supporting effective course design and delivery in a scalable way). This article demonstrates the use of data analysis and visualization as a means to empower students, teachers, researchers, and platform developers by making large volumes of data easy to understand. First, we introduce the insight needs of different stakeholder groups. Second, we compare the wide variety of data provided by major MOOC platforms. Third, we present a novel framework that distinguishes visualizations by the type of questions they answer. We then review the state of the art MOOC visual analytics using a tabulation of stakeholder needs versus visual analytics workflow types. Finally, we present new data analysis and visualization workflows for statistical, geospatial, and topical insights. The workflows have been optimized and validated in the Information Visualization MOOC (IVMOOC) annually taught at Indiana University since 2013. All workflows, sample data, and visualizations are provided at http://cns.iu.edu/2016-MOOCVis.html.

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Source

Semantic web & linked data: Elemente zukünftiger Informationsinfrastrukturen ; 1. DGI-Konferenz ; 62. Jahrestagung der DGI ; Frankfurt am Main, 7. - 9. Oktober 2010 ; Proceedings / Deutsche Gesellschaft für Informationswissenschaft und Informationspraxis. Hrsg.: M. Ockenfeld

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Abstract

In this study, we design an innovative method for answering students' or scholars' academic questions (for a specific scientific publication) by automatically recommending e-learning resources in a cyber-infrastructure-enabled learning environment to enhance the learning experiences of students and scholars. By using information retrieval and metasearch methodologies, different types of referential metadata (related Wikipedia pages, data sets, source code, video lectures, presentation slides, and online tutorials) for an assortment of publications and scientific topics will be automatically retrieved, associated, and ranked (via the language model and the inference network model) to provide easily understandable cyberlearning resources to answer students' questions. We also designed an experimental system to automatically answer students' questions for a specific academic publication and then evaluated the quality of the answers (the recommended resources) using mean reciprocal rank and normalized discounted cumulative gain. After examining preliminary evaluation results and student feedback, we found that cyberlearning resources can provide high-quality and straightforward answers for students' and scholars' questions concerning the content of academic publications.

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Abstract

Motivated by the increasing popularity of computer-mediated communication (CMC) media in university students' learning, this study employs a four-stage novel approach for analyzing and developing a structured hierarchy framework for students' usage of CMC media in learning contexts. First, media characteristics and the Uses and Gratifications (U&G) approach were adopted to understand student-specific reasons for using media. Second, a set of relevant data concerning the university students' reasons for using CMC media was collected by the Repertory Grid Interview Technique (RGT) and analyzed qualitatively using content analysis. The Interpretive Structural Modeling (ISM) technique was then used to develop a six-level hierarchical structural model of media use reasons. Finally, the cross-impact matrix multiplication applied to classification (MICMAC) technique was used to analyze the driver and dependence power for each media use reason and identify the hidden and indirect relationships among all reasons. The reasons related to students' use of CMC were classified as independent variables, linkage variables, and dependent variables. The study provides a validated typology of different clusters of interrelated students' reasons for using CMC media in learning contexts. The findings of this study will have significant implications and will be helpful for researchers, university policy-makers, instructors, and organizations in framing CMC technology implementation and use strategies.

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Abstract

Distance Education professionals have been constantly coming up with methods and techniques to increase student participation in an environment where learning happens continuously and asynchronously. An online discussion forum (ODF) is one of these mechanisms, but it will only be successful if students are willing to participate. Stimulating students is a challenge many institutions currently face. The objective of this study was to analyze the social interaction among participants in ODFs using Social Network Analysis. Knowing the characteristics of these networks and its participants is important to design actions to improve the use of ODFs. As a case study, data were collected from ODF logs of the majors in Business Administration and Accounting in a Brazilian private university. This study found out that these interaction networks are sparse, which shows that students could be more engaged in interacting and collaborating with others. Students, in general, tend to interact more in the first semester and interaction diminishes as time passes. The number of active ODF participants has been around 45-50%, which shows that students currently do not participate very often in ODFs. Their main incentive seems to exist when they are graded. Popular ODFs were also analyzed.

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Source

Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly