116,520 research outputs found

    Rich environments for active learning: a definition

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    Rich Environments for Active Learning, or REALs, are comprehensive instructional systems that evolve from and are consistent with constructivist philosophies and theories. To embody a constructivist view of learning, REALs: promote study and investigation within authentic contexts; encourage the growth of student responsibility, initiative, decision making, and intentional learning; cultivate collaboration among students and teachers; utilize dynamic, interdisciplinary, generative learning activities that promote higher-order thinking processes to help students develop rich and complex knowledge structures; and assess student progress in content and learning-to-learn within authentic contexts using realistic tasks and performances. REALs provide learning activities that engage students in a continuous collaborative process of building and reshaping understanding as a natural consequence of their experiences and interactions within learning environments that authentically reflect the world around them. In this way, REALs are a response to educational practices that promote the development of inert knowledge, such as conventional teacher-to-student knowledge-transfer activities. In this article, we describe and organize the shared elements of REALs, including the theoretical foundations and instructional strategies to provide a common ground for discussion. We compare existing assumptions underlying education with new assumptions that promote problem-solving and higher-level thinking. Next, we examine the theoretical foundation that supports these new assumptions. Finally, we describe how REALs promote these new assumptions within a constructivist framework, defining each REAL attribute and providing supporting examples of REAL strategies in action

    Thoughts about a General Theory of Influence in a DIME/PMESII/ASCOP/IRC2 Model

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    The leading question of this paper is: “How would influence warfare (“iWar”) work and how can we simulate it?” The paper discusses foundational aspects of a theory and model of influence warfare by discussing a framework built along the DIME/PMESII/ASCOP dimension forming a prism with three axes. The DIME concept groups the many instruments of power a nation state can muster into four categories: Diplomacy, Information, Military and Economy. PMESII describes the operational environment in six domains: Political, Military, Economic, Social, Information and Infrastructure. ASCOPE is used in counter insurgency (COIN) environments to analyze the cultural and human environment (aka the “human terrain”) and encompasses Areas, Structures, Capabilities, Organization, People and Events. In addition, the model reflects about aspects of information collection requirements (ICR) and information capabilities requirements (ICR) - hence DIME/PMESII/ASCOP/ICR2. This model was developed from an influence wargame that was conducted in October 2018. This paper introduces basic methodical questions around model building in general and puts a special focus on building a framework for the problem space of influence/information/hybrid warfare takes its shape in. The article tries to describe mechanisms and principles in the information/influence space using cross discipline terminology (e.g. physics, chemistry and literature). On a more advanced level this article contributes to the Human, Social, Culture, Behavior (HSCB) models and community. One goal is to establish an academic, multinational and whole of government influence wargamer community. This paper introduces the idea of the perception field understood as a molecule of a story or narrative that influences an observer. This molecule can be drawn as a selection of vectors that can be built inside the DIME/PMESII/ASCOP prism. Each vector can be influenced by a shielding or shaping action. These ideas were explored in this influence wargame

    The ergonomics of command and control

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    Since its inception, just after the Second World War, ergonomics research has paid special attention to the issues surrounding human control of systems. Command and Control environments continue to represent a challenging domain for Ergonomics research. We take a broad view of Command and Control research, to include C2 (Command and Control), C3 (Command, Control and Communication), and C4 (Command, Control, Communication and Computers) as well as human supervisory control paradigms. This special issue of ERGONOMICS aims to present state-of-the-art research into models of team performance, evaluation of novel interaction technologies, case studies, methodologies and theoretical review papers. We are pleased to present papers that detail research on these topics in domains as diverse as the emergency services (e.g., police, fire, and ambulance), civilian applications (e.g., air traffic control, rail networks, and nuclear power) and military applications (e.g., land, sea and air) of command and control. While the domains of application are very diverse, many of the challenges they face share interesting similarities

    An Agent-Based Simulation API for Speculative PDES Runtime Environments

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    Agent-Based Modeling and Simulation (ABMS) is an effective paradigm to model systems exhibiting complex interactions, also with the goal of studying the emergent behavior of these systems. While ABMS has been effectively used in many disciplines, many successful models are still run only sequentially. Relying on simple and easy-to-use languages such as NetLogo limits the possibility to benefit from more effective runtime paradigms, such as speculative Parallel Discrete Event Simulation (PDES). In this paper, we discuss a semantically-rich API allowing to implement Agent-Based Models in a simple and effective way. We also describe the critical points which should be taken into account to implement this API in a speculative PDES environment, to scale up simulations on distributed massively-parallel clusters. We present an experimental assessment showing how our proposal allows to implement complicated interactions with a reduced complexity, while delivering a non-negligible performance increase

    Lessons learned: structuring knowledge codification and abstraction to provide meaningful information for learning

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    Purpose – To increase the spread and reuse of lessons learned (LLs), the purpose of this paper is to develop a standardised information structure to facilitate concise capture of the critical elements needed to engage secondary learners and help them apply lessons to their contexts. Design/methodology/approach – Three workshops with industry practitioners, an analysis of over 60 actual lessons from private and public sector organisations and seven practitioner interviews provided evidence of actual practice. Design science was used to develop a repeatable/consistent information model of LL content/structure. Workshop analysis and theory provided the coding template. Situation theory and normative analysis were used to define the knowledge and rule logic to standardise fields. Findings – Comparing evidence from practice against theoretical prescriptions in the literature highlighted important enhancements to the standard LL model. These were a consistent/concise rule and context structure, appropriate emotional language, reuse and control criteria to ensure lessons were transferrable and reusable in new situations. Research limitations/implications – Findings are based on a limited sample. Long-term benefits of standardisation and use need further research. A larger sample/longitudinal usage study is planned. Practical implications – The implementation of the LL structure was well-received in one government user site and other industry user sites are pending. Practitioners validated the design logic for improving capture and reuse of lessons to render themeasily translatable to a new learner’s context. Originality/value – The new LL structure is uniquely grounded in user needs, developed from existing best practice and is an original application of normative and situation theory to provide consistent rule logic for context/content structure

    On perceptual expertise

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    Expertise is a cognitive achievement that clearly involves experience and learning, and often requires explicit, time-consuming training specific to the relevant domain. It is also intuitive that this kind of achievement is, in a rich sense, genuinely perceptual. Many experts—be they radiologists, bird watchers, or fingerprint examiners—are better perceivers in the domain(s) of their expertise. The goal of this paper is to motivate three related claims, by substantial appeal to recent empirical research on perceptual expertise: Perceptual expertise is genuinely perceptual and genuinely cognitive, and this phenomenon reveals how we can become epistemically better perceivers. These claims are defended against sceptical opponents that deny significant top-down or cognitive effects on perception, and opponents who maintain that any such effects on perception are epistemically pernicious

    An alternative Gospel of structure: order, composition, processes

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    We survey some basic mathematical structures, which arguably are more primitive than the structures taught at school. These structures are orders, with or without composition, and (symmetric) monoidal categories. We list several `real life' incarnations of each of these. This paper also serves as an introduction to these structures and their current and potentially future uses in linguistics, physics and knowledge representation.Comment: Introductory chapter to C. Heunen, M. Sadrzadeh, and E. Grefenstette. Quantum Physics and Linguistics: A Compositional, Diagrammatic Discourse. Oxford University Press, 201
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