121,738 research outputs found
Learning Design: reflections on a snapshot of the current landscape
The mounting wealth of open and readily available information and the swift evolution of social, mobile and creative technologies warrant a re-conceptualisation of the role of educators: from providers of knowledge to designers of learning. This need is being addressed by a growing trend of research in Learning Design. Responding to this trend, the Art and Science of Learning Design workshop brought together leading voices in the field and provided a forum for discussing its key issues. It focused on three thematic axes: practices and methods, tools and resources, and theoretical frameworks. This paper reviews some definitions of Learning Design and then summarises the main contributions to the workshop. Drawing upon these, we identify three key challenges for Learning Design that suggest directions for future research
Design thinking support: information systems versus reasoning
Numerous attempts have been made to conceive and implement appropriate information systems to support architectural designers in their creative design thinking processes. These information systems aim at providing support in very diverse ways: enabling designers to make diverse kinds of visual representations of a design, enabling them to make complex calculations and simulations which take into account numerous relevant parameters in the design context, providing them with loads of information and knowledge from all over the world, and so forth. Notwithstanding the continued efforts to develop these information systems, they still fail to provide essential support in the core creative activities of architectural designers. In order to understand why an appropriately effective support from information systems is so hard to realize, we started to look into the nature of design thinking and on how reasoning processes are at play in this design thinking. This investigation suggests that creative designing rests on a cyclic combination of abductive, deductive and inductive reasoning processes. Because traditional information systems typically target only one of these reasoning processes at a time, this could explain the limited applicability and usefulness of these systems. As research in information technology is increasingly targeting the combination of these reasoning modes, improvements may be within reach for design thinking support by information systems
Both Generic Design and Different Forms of Designing
This paper defends an augmented cognitively oriented "generic-design
hypothesis": There are both significant similarities between the design
activities implemented in different situations and crucial differences between
these and other cognitive activities; yet, characteristics of a design
situation (i.e., related to the designers, the artefact, and other task
variables influencing these two) introduce specificities in the corresponding
design activities and cognitive structures that are used. We thus combine the
generic-design hypothesis with that of different "forms" of designing. In this
paper, outlining a number of directions that need further elaboration, we
propose a series of candidate dimensions underlying such forms of design
Design: One, but in different forms
This overview paper defends an augmented cognitively oriented generic-design
hypothesis: there are both significant similarities between the design
activities implemented in different situations and crucial differences between
these and other cognitive activities; yet, characteristics of a design
situation (related to the design process, the designers, and the artefact)
introduce specificities in the corresponding cognitive activities and
structures that are used, and in the resulting designs. We thus augment the
classical generic-design hypothesis with that of different forms of designing.
We review the data available in the cognitive design research literature and
propose a series of candidates underlying such forms of design, outlining a
number of directions requiring further elaboration
Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks
Biological plastic neural networks are systems of extraordinary computational
capabilities shaped by evolution, development, and lifetime learning. The
interplay of these elements leads to the emergence of adaptive behavior and
intelligence. Inspired by such intricate natural phenomena, Evolved Plastic
Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed
plastic neural networks with a large variety of dynamics, architectures, and
plasticity rules: these artificial systems are composed of inputs, outputs, and
plastic components that change in response to experiences in an environment.
These systems may autonomously discover novel adaptive algorithms, and lead to
hypotheses on the emergence of biological adaptation. EPANNs have seen
considerable progress over the last two decades. Current scientific and
technological advances in artificial neural networks are now setting the
conditions for radically new approaches and results. In particular, the
limitations of hand-designed networks could be overcome by more flexible and
innovative solutions. This paper brings together a variety of inspiring ideas
that define the field of EPANNs. The main methods and results are reviewed.
Finally, new opportunities and developments are presented
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Learning design – making practice explicit
New technologies have immense potential for learning, but the sheer variety possible also creates challenges for learners in terms of navigating through an increasingly complex digital landscape and for teachers in terms of how to design and support learning interventions. How can learners and teachers make informed decisions about what technologies to use in the design and support of learning activities? This presentation will consider this question and present a new methodology for design – 'learning design', which aims to shift the creation and support of learning from what has traditionally been an implicit, belief-based practice to one that is explicit and design based. Learning design research at the Open University, UK has included the development of a set of conceptual design views, a tool for visualising designs (CompendiumLD) and a social networking site, for sharing and discussing learning and teaching ideas and designs (Cloudworks). An overview of this work will be provided, along with a discussion of the perceived benefits of this new approach to educational design
Creativity as Cognitive design \ud The case of mesoscopic variables in Meta-Structures\ud
Creativity is an open problem which has been differently approached by several disciplines since a long time. In this contribution we consider as creative the constructivist design an observer does on the description levels of complex phenomena, such as the self-organized and emergent ones ( e.g., Bènard rollers, Belousov-Zhabotinsky reactions, flocks, swarms, and more radical cognitive and social emergences). We consider this design as related to the Gestaltian creation of a language fit for representing natural processes and the observer in an integrated way. Organised systems, both artificial and most of the natural ones are designed/ modelled according to a logical closed model which masters all the inter-relation between their constitutive elements, and which can be described by an algorithm or a single formal model. We will show there that logical openness and DYSAM (Dynamical Usage of Models) are the proper tools for those phenomena which cannot be described by algorithms or by a single formal model. The strong correlation between emergence and creativity suggests that an open model is the best way to provide a formal definition of creativity. A specific application relates to the possibility to shape the emergence of Collective Behaviours. Different modelling approaches have been introduced, based on symbolic as well as sub-symbolic rules of interaction to simulate collective phenomena by means of computational emergence. Another approach is based on modelling collective phenomena as sequences of Multiple Systems established by percentages of conceptually interchangeable agents taking on the same roles at different times and different roles at the same time. In the Meta-Structures project we propose to use mesoscopic variables as creative design, invention, good continuity and imitation of the description level. In the project we propose to define the coherence of sequences of Multiple Systems by using the values taken on by the dynamic mesoscopic clusters of its constitutive elements, such as the instantaneous number of elements having, in a flock, the same speed, distance from their nearest neighbours, direction and altitude. In Meta-Structures the collective behaviour’s coherence corresponds, for instance, to the scalar values taken by speed, distance, direction and altitude along time, through statistical strategies of interpolation, quasi-periodicity, levels of ergodicity and their reciprocal relationship. In this case the constructivist role of the observer is considered creative as it relates to neither non-linear replication nor transposition of levels of description and models used for artificial systems, like reductionism. Creativity rather lies in inventing new mesoscopic variables able to identify coherent patterns in complex systems. As it is known, mesoscopic variables represent partial macroscopic properties of a system by using some of the microscopic degrees of freedom possessed by composing elements. Such partial usage of microscopic as well as macroscopic properties allows a kind of Gestaltian continuity and imitation between levels of descriptions for mesoscopic modelling. \ud
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