Public leaders and managers today are being challenged by unprecedented, complex problems. Tackling "wicked problems" requires a new way of thinking, and new methods and tools for building models that realis...
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Public leaders and managers today are being challenged by unprecedented, complex problems. Tackling "wicked problems" requires a new way of thinking, and new methods and tools for building models that realistically account for social and natural phenomena, gather and structure convincing evidence, and predict policy outcomes accurately. To prepare future and current public decision makers for a rapidly changing, complex world, we suggest a multidimensional framework of complexity in public policy settings that encompasses both analytic and socially constructed complexity, and introduce a simulation-based learning environment (SBLE) in which the power of traditional learningenvironments is augmented by a computer simulation model. In this study, we report on our experimental attempt to teach students in the MPA classroom about complexity by creating and implementing a SBLE with a U.S. Gulf Coast disaster preparedness case.
Artificial General Intelligence (AGI) refers to machine intelligence that can effectively conduct variety of human tasks. Therefore AGI research requires multivariate and realistic learningenvironments. In recent yea...
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ISBN:
(数字)9783319466873
ISBN:
(纸本)9783319466873;9783319466866
Artificial General Intelligence (AGI) refers to machine intelligence that can effectively conduct variety of human tasks. Therefore AGI research requires multivariate and realistic learningenvironments. In recent years, game engines capable of constructing highly realistic 3D virtual worlds have also become available at low cost. In accordance with these changes, we developed the "Life in Silico" (LIS) framework, which provides virtual agents with learning algorithms and their learningenvironments with game engine. This should in turn allow for easier and more flexible AGI research. Furthermore, non-experts will be able to play with the framework, which would enable them to research as their hobby. If AGI research becomes popular in this manner, we may see a sudden acceleration towards the "Democratization of AGI".
based on cognitive load theory, the effect of different levels of instructional detail and expertise in a simulation-basedenvironment on learning about concepts of correlation was investigated. Separate versions of t...
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based on cognitive load theory, the effect of different levels of instructional detail and expertise in a simulation-basedenvironment on learning about concepts of correlation was investigated. Separate versions of the learningenvironment were designed for the four experimental conditions which differed only with regard to the levels of written instructional detail. One hundred and forty Grade 10 (lower-expertise) and Grade 11 (higher-expertise) students participated in this experiment. In accord with the expertise reversal effect, the results supported the hypothesis that higher levels of instructional detail benefited learning for lower-expertise learners, whereas lower levels of detail facilitated learning for higher-expertise learners. It was concluded that the level of instructional guidance needed to match learners' levels of expertise.
Background. simulation-based learning environments are used extensively to support learning in complex business systems. Nevertheless, studies have identified problems and limitations due to cognitive processing diffi...
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Background. simulation-based learning environments are used extensively to support learning in complex business systems. Nevertheless, studies have identified problems and limitations due to cognitive processing difficulties. In particular, previous research has addressed some aspects of model transparency and instructional strategy and produced inconclusive results. Aim. This study investigates the learning effects of using transparent simulations (that is, showing users the internal structure of models) and exploratory guidance (that is, guiding learners so they are able to explore the simulation by themselves, supported by specific cognitive aids) from a mental models perspective. Method. A test based on a simulation experiment with a system dynamics model, representing a supply chain system, was performed. Participants are required to use the simulator to investigate some issues related to the bullwhip effect and other supply chain coordination concepts. Results. Participants provided with the more transparent strategy and offered the more exploratory guidance demonstrated better understanding of the structure and behaviour of the underlying model. However, our results suggest that while exploratory guidance is a beneficial method for understanding both model structure and behaviour, making only the model transparent is more limited in its effect.
Error-basedsimulation (EBS) is a framework for assisting a learner to become aware of his errors. It makes a simulationbased on his erroneous hypothesis to show what unreasonable phenomena would occur if his hypothe...
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ISBN:
(纸本)9783540891963
Error-basedsimulation (EBS) is a framework for assisting a learner to become aware of his errors. It makes a simulationbased on his erroneous hypothesis to show what unreasonable phenomena would occur if his hypothesis were correct, which has been proved effective as counterexamples to cause cognitive conflict. In making EBS, it is necessary (1) to make a simulation by dealing with a set of inconsistent constraints because erroneous hypotheses often contradict the correct knowledge, and (2) to estimate the 'unreasonableness' of phenomena in a simulation because it must be recognized as 'unreasonable.' We previously proposed a technique (called 'Partial Constraint Analysis (PCA)') for making EBS based on any inconsistent simultaneous equations, and a set of domain-independent heuristics to estimate the 'unreasonableness' of physical phenomena. In this paper, we describe a prototype EBS-system implemented by using these, and show the results of preliminary test which verified the usefulness of our method.
In 2014, NASPAA (Network of Schools of Public Policy, Affairs, and Administration) partnered with the Rippel Foundation to hold the first NASPAA Student simulation Competition, built on the ReThink Health simulation p...
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In 2014, NASPAA (Network of Schools of Public Policy, Affairs, and Administration) partnered with the Rippel Foundation to hold the first NASPAA Student simulation Competition, built on the ReThink Health simulation platform. The competition took place at five sites and involved 181 graduate students from 93 institutions. Students used the simulator in small teams to craft longterm policy solutions to problems facing the U.S. health care system. This article describes how the competition came to be, identifies key stakeholders, describes the environment that made the competition a reality, explains the simulation model, details the planning and logistics for each competition site, lists the materials that turned the simulation into a learning experience, and speculates about implications of this competition and the role for simulation- based exercises in public management and public policy education.
Collaborative skills are crucial in knowledge-rich domains, such as medical diagnosing. The Collaborative Diagnostic Reasoning (CDR) model emphasizes the importance of high-quality collaborative diagnostic activities ...
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Collaborative skills are crucial in knowledge-rich domains, such as medical diagnosing. The Collaborative Diagnostic Reasoning (CDR) model emphasizes the importance of high-quality collaborative diagnostic activities (CDAs;e.g., evidence elicitation and sharing), influenced by content and collaboration knowledge as well as more general social skills, to achieve accurate, justified, and efficient diagnostic outcomes (Radkowitsch et al., 2022). However, it has not yet been empirically tested, and the relationships between individual characteristics, CDAs, and diagnostic outcomes remain largely unexplored. The aim of this study was to test the CDR model by analyzing data from three studies in a simulation-basedenvironment and to better understand the construct and the processes involved (N = 504 intermediate medical students) using a structural equation model including indirect effects. We found various stable relationships between individual characteristics and CDAs, and between CDAs and diagnostic outcome, highlighting the multidimensional nature of CDR. While both content and collaboration knowledge were important for CDAs, none of the individual characteristics directly related to diagnostic outcome. The study suggests that CDAs are important factors in achieving successful diagnoses in collaborative contexts, particularly in simulation-based settings. CDAs are influenced by content and collaboration knowledge, highlighting the importance of understanding collaboration partners' knowledge. We propose revising the CDR model by assigning higher priority to collaboration knowledge compared with social skills, and dividing the CDAs into information elicitation and sharing, with sharing being more transactive. Training should focus on the development of CDAs to improve CDR skills.
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