Modelling collective learning in design

In this paper, a model of collective learning in design is developed in the context of team design. It explains that a team design activity uses input knowledge, environmental information, and design goals to produce output knowledge. A collective learning activity uses input knowledge from different agents and produces learned knowledge with the process of knowledge acquisition and transformation between different agents, which may be triggered by learning goals and rationale triggers. Different forms of collective learning were observed with respect to agent interactions, goal(s) of learning, and involvement of an agent. Three types of links between team design and collective learning were identified, namely teleological, rationale, and epistemic. Hypotheses of collective learning are made based upon existing theories and models in design and learning, which were tested using a protocol analysis approach. The model of collective learning in design is derived from the test results. The proposed model can be used as a basis to develop agent-based learning systems in design. In the future, collective learning between design teams, the links between collective learning and creativity, and computational support for collective learning can be investigated

Fundamental activity constraints lead to specific interpretations of the connectome

The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to experimental observations. Nevertheless, structurally realistic network models of spiking neurons are necessarily underconstrained even if experimental data on brain connectivity are incorporated to the best of our knowledge. Guided by physiological observations, any model must therefore explore the parameter ranges within the uncertainty of the data. Based on simulation results alone, however, the mechanisms underlying stable and physiologically realistic activity often remain obscure. We here employ a mean-field reduction of the dynamics, which allows us to include activity constraints into the process of model construction. We shape the phase space of a multi-scale network model of the vision-related areas of macaque cortex by systematically refining its connectivity. Fundamental constraints on the activity, i.e., prohibiting quiescence and requiring global stability, prove sufficient to obtain realistic layer- and area-specific activity. Only small adaptations of the structure are required, showing that the network operates close to an instability. The procedure identifies components of the network critical to its collective dynamics and creates hypotheses for structural data and future experiments. The method can be applied to networks involving any neuron model with a known gain function.Comment: J. Schuecker and M. Schmidt contributed equally to this wor

Cognitive modeling of social behaviors

To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual mind as ways of carrying out activities. This requires for the psychologist a shift from only modeling goals and tasks —why people do what they do—to modeling behavioral patterns—what people do—as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). To illustrate these ideas, this article presents an extract from a Brahms simulation of the Flashline Mars Arctic Research Station (FMARS), in which a crew of six people are living and working for a week, physically simulating a Mars surface mission. The example focuses on the simulation of a planning meeting, showing how physiological constraints (e.g., hunger, fatigue), facilities (e.g., the habitat’s layout) and group decision making interact. Methods are described for constructing such a model of practice, from video and first-hand observation, and how this modeling approach changes how one relates goals, knowledge, and cognitive architecture. The resulting simulation model is a powerful complement to task analysis and knowledge-based simulations of reasoning, with many practical applications for work system design, operations management, and training

Uncovering everyday learning and teaching within the quilting community of Aotearoa New Zealand : a thesis presented in fulfilment of the requirements for the degree of Doctor of Philosophy in Arts at Massey University, Palmerston North, New Zealand

This thesis explores the social and cultural phenomenon of everyday learning and teaching within the communal activity of quiltmaking. Home-sewn quilts are rarely associated with the needleworkers’ high level of knowledge and skill; yet, the quilters’ act of knowing is practical, inherently social, and intentional. This research study examines the collaborative processes of “quilting together” to understand cultural patterns of participation; and investigates the participants’ meaning-making experiences to facilitate an analysis of collective knowledge practices. Using an ethnographic methodology, this research investigated the lived experiences of quilters within the situated context of two quilting groups, located in Aotearoa New Zealand. Observations were made of participants’ engagement in quilting activities as they interacted with each other, material artefacts and quilting tools. These observations took place during regular quilting sessions and special events. Interviews were conducted with founding members to gain an understanding of cultural-historical processes, as well as a purposively selected sample of ten participants who shared their personal quilting experiences. Observation notes, conversation commentaries and interview transcripts were analysed in relation to the research question and two guiding questions. Key findings are related to a variety of contextual issues surrounding the process of informal learning and teaching as it materialised through the quilters’ engagement in idiosyncratic community practices: the practices of which are generative of quilting knowledge and vice-versa. Firstly, through social integration quilters developed a sense of belonging and responsibility. Secondly, cultural patterns of social interaction consisted of multi-directional learning with quilters having complementary roles. Thirdly, due to the tacit nature of quilting knowledge, embodied experiences and material mediations were essential for thinking and communicating with others. Fourthly, a constellation of knowledge practices co-existed in the quilting community. Finally, the quilters’ informal learning was organised and supported within the community. The study contributes to a body of locally-based and international research concerned with informal learning and teaching theory, situated in a quilting community-based setting. The emerging conceptual framework, “Apprenticeship Model of Craft Community Learning”, develops and extends participation-based approaches to learning. In addition, the quilters’ collaborative designing process of inquiry advances understanding of knowledge creation within craft maker cultures

The role of competences on patenting activities of learning regions : an empirical study on French data

In a learning region interactions between agents strongly determine the territorial capacities to create, develop and diffuse knowledge, and finally to innovate.. More precisely, the interactive model of innovation suggests that several different pieces of knowledge have to be mixed and shared between actors in order to win the innovative race. Indeed, in our current knowledge based economies a maximum of research inputs is not a guarantee of a high level of innovation any more. On the contrary, the entities (whatever their size) which succeed to combine efficiently different and sometimes complementary or conflicting "small" pieces of knowledge inside their borders, might reach unexpected and higher level of invention and innovation. But, because of the multiple facets of knowledge (tacit, explicit, individual, collective..) and of the potential barriers generated by geographic and/or cognitive distances, these knowledge combinations or re-combinations require specific abilities or competences. First of all, firms have to develop abilities to organise internally and efficiently around innovation (we call theses competences organisational and technical ones). Besides, firms try to benefit from external innovative ideas by developing critical interfaces (Pavitt, 1998). In other words, they try and acquire competences in collaborating with customers, suppliers, but also competitors, financers and public institutions so as to reduce their mutual cognitive misunderstandings.. So, we assume that thanks to a large range of complementary competences, firms try to cope with knowledge transmission problems and to keep as innovative as possible (exploiting every external innovative ideas). Using an original (quantitative and qualitative) data base on competences for innovation (Sessi, 1997), we precisely aim at testing this hypothesis. Concretely we run an econometric model evaluating the impact of competences mastered by firms of a region, on the innovative activity (proxied by the ratio patents/GDP) of the same region. We purposely choose to run the analysis at the regional level so as to minimize the geographic distance impact. Indeed, lots of existing articles already analyse the impact of geographic proximity on innovation. We rather aim at analysing the influence of cognitive proximity. Our results allow us to highlight the core competences of innovative regions. We then build a typology of regions coupling the nature of competences a region has to master and its industrial specificities. Based on this typology we suggest some guidelines for policy makers: As regions differ in terms of industrial specificities, they also differ in the competences they have to develop and therefore differentiated innovative policies have to be run.

Realizing the Power of Extelligence: A New Business Model for Academic Publishing

The limitations of traditional academic knowledge exchange systems such as conferences and peer-reviewed journals result in discipline-based scholarship that is feudal in nature and can only dissipate as cross-disciplinary research expands. The next evolutionary step is democratic online knowledge exchange, run by the academic many rather than the publishing-oligarchic few. Using sociotechnical tools it is possible to implement an academic publishing business model that maximizes the power of “extelligence”, or knowledge realized through the collective gifting of information. Such a model would change the roles of journal editors and peer reviewers from knowledge gatekeepers to knowledge guides, and change the competitive yet conforming behaviors of academic researchers seeking publication to behaviors that reward collaborative activity that engages research communities in the act of knowledge exchange. We argue that socio-technical systems, social systems sitting on a technical base such as the Internet, can provide effective ways to motivate people to increase knowledge that research communities can share. By employing a hybrid of wiki, e-journal, electronic repository, micro-commenting and reputation systems for readers and writers, along with other socio-technical functions common to social computing such as social book-marking and reader recommendation, we can move from our traditional print publishing model in which prestige is established through publication in slowly produced, expensive and virtually unread journals to a vibrant, online knowledge exchange community built upon the foundations of legitimacy, transparency and freedom

Bifurcate

Bifurcating means: reconstituting a political economy that reconnects local knowledge and practices with macroeconomic circulation and rethinks territoriality at its different scales of locality; developing an economy of contribution on the basis of a contributory income no longer tied to employment and once again valuing work as a knowledge activity; overhauling law, and government and corporate accounting, via economic and social experiments, including in laboratory territories, and in relation to cooperative, local market economies formed into networks and linked to international trade; revaluing research from a long-term perspective, independent of the short-term interests of political and economic powers; reorienting digital technology in the service of territories and territorial cooperation. The collective work that produced this book is based on the claim that today’s destructive development model is reaching its ultimate limits, and that its toxicity, which is increasingly massive, manifest and multidimensional (medical, environmental, mental, epistemological, economic – accumulating pockets of insolvency, which become veritable oceans), is generated above all by the fact that the current industrial economy is based in every sector on an obsolete physical model – a mechanism that ignores the constraints of locality in biology and the entropic tendency in reticulated computational information. In these gravely perilous times, we must bifurcate: there is no alternative