By Joao Bento, Jose Duarte, Manuel V. Heitor, William Mitchell
In ultra-modern knowledge-driven economic climate, the power to proportion perception and knowledge is vital for riding innovation and development. during this groundbreaking quantity, students from all over the world display how conversation and data applied sciences are allowing dynamic undertaking layout and administration practices that problem conventional strategies of time, house and behaviour. Showcasing experiments in structure, engineering, and development design—employing technological infrastructures that hyperlink humans and their principles throughout actual, highbrow, and cultural boundaries—the authors ponder such matters because the hyperlinks among competence and innovation and among person and collective wisdom. on the center in their research is the belief that technological innovation is mainly a social task. the consequences are profound for the sensible administration of advanced layout tasks, experiments in distance studying and digital groups, and rising theoretical thoughts of collaborative studying and innovation.
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Additional info for Collaborative Design and Learning: Competence Building for Innovation (International Series on Technology Policy and Innovation)
Our vision is that of a new milieu of discovery, learning, and sharing, in which people learn-by-doing, interacting and consulting widely, being able to readily access vast storehouses of knowledge, anytime and anyplace. Engineered learning systems should be promoted to achieve this Learning through Interaction 35 vision. Such systems must emphasize active learning experiences, such as simulation, creation, and collaboration, in a learning environment enhanced by technologies for accessing global resources, real-time and asynchronous distance interaction, self-directed exploration, self-assessment, and authoring.
These two kinds of knowledge differ in the way they are used, diffused, and produced. However, they are strongly interdependent Learning through Interaction 25 in the learning processes that lead to the accumulation of knowledge, the basis for our proposed model in which learning is the main driver for economic development. We explore in a later subsection the differences between software and wetware identified in the introductory chapter of this book, and then we propose a unifying model of economic development, centered on the interactions between software and wetware.
We explore in a later subsection the differences between software and wetware identified in the introductory chapter of this book, and then we propose a unifying model of economic development, centered on the interactions between software and wetware. These interactions lead to the accumulation of knowledge through learning. 4 Further differences are explored toward the end of this subsection. , ideas and skills) lies in the level of codification. Although ideas correspond to knowledge that can be articulated in words, symbols, or other means of expression, skills cannot be formalized, but always remain in tacit form.