103,215 research outputs found

    USE OF LEARNING MANAGEMENT SYSTEM ILIAS IN TEACHING TECHNOLOGIES FOR INTENDING TEACHERS OF SECONDARY AND VOCATIONAL EDUCATION

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    The purpose of the article is to substantiate the features of e-learning technologies of materials for intending teachers of secondary and vocational education through the use of available learning management system ILIAS.The web-based learning management system ILIAS is used to develop e-learning materials, manage and disseminate multimedia materials in an online educational environment. The ILIAS system is available, free of charge and designed to manage learning resources as part of integrated systems and e-learning. The independence of the international project ILIAS and its support by many European universities as well as IT organizations are the basis for use and development in the training of intending teachers of secondary and vocational education.While researching the given issue, we have used theoretical and empirical research methods, i.e. analysis and synthesis to clarify the basic concepts and categories of computer-based education; conceptual and comparative analysis of curricula and programs, psychological and pedagogical, scientific and methodical literature as well as the materials of scientific and practical conferences on the problem of research and advanced pedagogical experience, comparing traditional and computer-oriented approaches in teaching technology. We have also used the methods of identifying patterns and drawing conclusions on the given issue.The use of web-based management system ILIAS in the teaching of construction materials technology contributes to the formation of professional competencies of intending teachers of secondary and vocational education, manifested in the ability to integrate knowledge of different technologies, make sound technical decisions and implement them in virtual reality; selection of technological processes, planning, forecasting and evaluation of technology efficiency; perception of computer models of technological processes.

    Forecasting the Spreading of Technologies in Research Communities

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    Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution

    Selected Instruments for Management of Technology Development

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    Polska dysponuje pewnymi możliwościami rozwijania nowoczesnych technologii, także tych, które aktualnie znajdują się w pierwszych fazach cyklu życia (np. nanotechnologii, spintroniki, fizykochemii zjawisk powierzchniowych, robotyki itd.), i mają wysoki potencjał generowania zysku przy relatywnie niskich (bo niezwiązanych z samymi kosztami produkcji) nakładach inwestycyjnych i niższych wymaganiach, jeśli chodzi o wcześniej zdobyte doświadczenie. Wykorzystanie tych możliwości wymaga rozszerzenia o nowe podejścia tradycyjnego instrumentarium zarządzania technologią, opartego głównie na dorobku teorii racjonalnych oczekiwań. Wśród tych nowych podejść na szczególną uwagę zasługuje foresight i towarzyszące mu: cykl życia technologii i mapowanie, które są przedmiotem niniejszego artykułu

    Managing stimulation of regional innovation subjects’ interaction in the digital economy

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    The reported study was funded by RFBR according to the research project No. 18-01000204_a, No. 16-07-00031_a, No. 18-07-00975_a.Purpose: The article is devoted to solving fundamental scientific problems in the scope of the development of forecasting modeling methods and evaluation of regional company’s innovative development parameters, synthesizing new methods of big data processing and intelligent analysis, as well as methods of knowledge eliciting and forecasting the dynamics of regional innovation developments through benchmarking. Design/Methodology/Approach: For regional economic development, it is required to identify the mechanisms that contribute to (or impede) the innovative economic development of the regions. The synergetic approach to management is based on the fact that there are multiple paths of IS development (scenarios with different probabilities), although it is necessary to reach the required attractor by meeting the management goals. Findings: The present research is focused on obtainment of new knowledge in creating a technique of multi-agent search, collection and processing of data on company’s innovative development indicators, models and methods of intelligent analysis of the collected data. Practical Implications: The author developed recommendations before starting the process of institutional changes in a specific regional innovation system. The article formulates recommendations on the implementation of institutional changes in the region taking into account the sociocultural characteristics of the region’s population. Originality/Value: It is the first time, when a complex of models and methods is based on the use of a convergent model of large data volumes processing is presented.peer-reviewe

    Forecasting transport mode use with support vector machines based approach

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    The paper explores potential to forecast what transport mode one will use for his/her next trip. The support vector machines based approach learns from individual's behavior (validated GPS tracks) to support smart city transport planning services. The overall success rate, in forecasting the transport mode, is 82 %, with lower confusion for private car, bike and walking
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