147,576 research outputs found

    Educational Technology: The influence of theory

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    In this paper we explore the role of theories in current practice in educational technology. We review a range of writings from the past 30 years on the nature of learning technology research. We discuss influences on learning technologies from the related fields of Artificial Intelligence in Education (AIED) and Human-Computer Interaction (HCI). We identify two groups of theories which have been used. The first group are related to principled decisions about the design of learning materials. The second group influence the ways in which we frame our research on learning. Research in learning technologies in the future will need to draw on both groups of theories. In this paper, we draw on our own experiences as educational technologists and the purpose of the paper is to encourage other educational technologists to join with us in reflecting on their own use of theories

    Overview on agent-based social modelling and the use of formal languages

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    Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

    Man and Machine: Questions of Risk, Trust and Accountability in Today's AI Technology

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    Artificial Intelligence began as a field probing some of the most fundamental questions of science - the nature of intelligence and the design of intelligent artifacts. But it has grown into a discipline that is deeply entwined with commerce and society. Today's AI technology, such as expert systems and intelligent assistants, pose some difficult questions of risk, trust and accountability. In this paper, we present these concerns, examining them in the context of historical developments that have shaped the nature and direction of AI research. We also suggest the exploration and further development of two paradigms, human intelligence-machine cooperation, and a sociological view of intelligence, which might help address some of these concerns.Comment: Preprin

    CGAMES'2009

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