133,746 research outputs found

    Designing the EMBeRS summer school: Connecting stakeholders in learning, teaching and research

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    © 2017 Asia-Pacific Society for Computers in Education. All rights reserved. In this paper, we describe our research investigating design, teaching and learning aspects of the EMBeRS Summer School. In 2016, thirteen graduate Environmental Science students participated in a ten-day Summer School to learn about interdisciplinary approaches to researching socio-environmental systems. Using the Employing Model-Based Reasoning in Socio-Environmental Synthesis (EMBeRS) approach, students learned about wicked problems, team composition, systems thinking and modelling, stakeholder management, and communication. They applied this approach to their own research, as well as to a case study, in order to, ultimately, further the EMBeRS approach in their own institutions. Learning sciences researchers, environmental science instructors and learners collaborated in design, teaching, and learning during the 2016 Summer School in order to co-create and co-configure the tasks, social arrangements, and tools for learning, teaching and design. This paper identifies four examples of connections between the stakeholders (researchers, instructors and learners), the tools that facilitated the connection, and the implications for learning, teaching and design

    Harmonised Principles for Public Participation in Quality Assurance of Integrated Water Resources Modelling

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    The main purpose of public participation in integrated water resources modelling is to improve decision-making by ensuring that decisions are soundly based on shared knowledge, experience and scientific evidence. The present paper describes stakeholder involvement in the modelling process. The point of departure is the guidelines for quality assurance for `scientific` water resources modelling developed under the EU research project HarmoniQuA, which has developed a computer based Modelling Support Tool (MoST) to provide a user-friendly guidance and a quality assurance framework that aim for enhancing the credibility of river basin modelling. MoST prescribes interaction, which is a form of participation above consultation but below engagement of stakeholders and the public in the early phases of the modelling cycle and under review tasks throughout the process. MoST is a flexible tool which supports different types of users and facilitates interaction between modeller, manager and stakeholders. The perspective of using MoST for engagement of stakeholders e.g. higher level participation throughout the modelling process as part of integrated water resource management is evaluate

    On the role of pre and post-processing in environmental data mining

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    The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed

    How do school leaders successfully lead learning?

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    Systematic evaluation of design choices for software development tools

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    [Abstract]: Most design and evaluation of software tools is based on the intuition and experience of the designers. Software tool designers consider themselves typical users of the tools that they build and tend to subjectively evaluate their products rather than objectively evaluate them using established usability methods. This subjective approach is inadequate if the quality of software tools is to improve and the use of more systematic methods is advocated. This paper summarises a sequence of studies that show how user interface design choices for software development tools can be evaluated using established usability engineering techniques. The techniques used included guideline review, predictive modelling and experimental studies with users

    Big data analytics:Computational intelligence techniques and application areas

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    Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment
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