Fostering the reduction of assortative mixing or homophily into the class

Human societies from the outset have been associated according to race, beliefs, religion, social level, and the like. These behaviors continue even today in the classroom at primary, middle, and superior levels. However, the growth of ICT offers educational researchers new ways to explore methods of team formation that have been proven to be efficient in the field of serious games through the use of computer networks. The selection process of team members in serious games through the use of computer networks is carried out according to their performance in the area of the game without distinction of social variables. The use of serious games in education has been discussed in multiple research studies which state that its application in teaching and learning processes are changing the way of teaching. This article presents an exploratory analysis of the team formation process based on collaboration through the use of ICT tools of collective intelligence called TBT (The best team). The process and its ICT tool combine the paradigms of creativity in swarming, collective intelligence, serious games, and social computing in order to capture the participants’ emotions and evaluate contributions. Based on the results, we consider that the use of new forms of teaching and learning based on the emerging paradigms is necessary. Therefore, TBT is a tool that could become an effective way to encourage the formation of work groups by evaluating objective variable of performance of its members in collaborative works.Postprint (published version

Measuring the collective intelligence education index

War games and sports games always seek glory and excellence in an environment where participants enjoy what they do. Success is guaranteed in the degree of effective collaboration and coordination within the team members, as well as the strategy used by teams, such games or war strategies are generated since the birth of humanity. In this sense, the following questions emerge in the field of education: Is it possible to design learning activities that use this principle applied to collaborative work in the classroom? Which are the conditions of application of team competition strategy using ICT tools and how to measure it? This research explores the application of a web tool called Choose the Best (CTB). CTB implements a strategy that fosters competitiveness among the teams of a class, as well as the coordination and collaboration within the same, these types of strategies contribute to the development of Collective Intelligence levels. It's measured through a group of implemented metrics. Based on the results, we consider that the use of new forms of teaching and learning based on the emerging paradigms is necessary. Therefore, CTB is a tool that could become an effective way to measuring the group's performance according to Collective Intelligence paradigms.Postprint (author's final draft

Human Computation and Convergence

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added references to page 1 and 3, and corrected typ

Compassion on University Degree Programmes at a UK University: The Neuroscience of Effective Group work

This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/ licences/by/4.0/legalcodePurpose The purpose of this paper is to explore the neuroscience that underpins the psychology of compassion as a competency. We explain why this cognitive competency is now taught and assessed on modules of different degree subjects in a UK university. Design/methodology/approach The paper is divided into first, an exploration of recent psychology and neuroscience literature that illuminates the differences, and relationship, between empathy and compassion for safeness building in teams. Within that, the role of oxytocin in achieving social and intellectual rewards though the exercise of cognitive flexibility, working memory and impulsive inhibitory control (Zelazo, et al, 2016) is also identified. The literature findings are compared against relevant qualitative data from the above university’s, so far, nine years of mixed methods action research on compassion-focused pedagogy (CfP). Findings These are that the concept and practice of embedding compassion as a cognitive competency into assessed university group work is illuminated and rationalised by research findings in neuroscience. Research limitations/implications The limitations of the study are that, so far, fMRI research methods have not been used to investigate student subjects involved in the compassion-focused pedagogy now in use. Practical implications The paper has implications for theory, policy and practice in relation to managing the increasing amount of group work that accompanies widening participation in Higher Education. Originality/value A review of this kind specifically for student assessed group and its implications for student academic achievement and mental health has not, apparently, been publishedPeer reviewe

Human behaviour modelling in complex socio-technical systems : an agent based approach

For many years we have been striving to understand human behaviour and our interactions with our socio-technological environment. By advancing our knowledge in this area, we have helped the design of new or improved work processes and technologies. Historically, much of the work in analysing social interactions has been conducted within the social sciences. However, computer simulation has brought an extra tool in trying to understand and model human behaviours. Using an agent based approach this presentation describes my work in constructing computational models of human behaviour for informing design through simulation. With examples from projects in two main application areas of crisis and emergency management, and energy management I describe how my work addresses some main issues in agent based social simulation. The first concerns the process by which we develop these models. The second lies in the nature of socio-technical systems. Human societies are a perfect example of a complex system exhibiting characteristics of self-organisation, adaptability and showing emergent phenomena such as cooperation and robustness. I describe how complex systems theory may be applied to improve our understanding of socio-technical systems, and how our micro level interactions lead to emergent mutual awareness for problem-solving. From agent based simulation systems I show how context awareness may be modelled. Looking forward to the future, I discuss how the increasing prevalence of artificial agents in our society will cause us to re-examine the new types of interactions and cooperative behaviours that will emerge.Depuis de nombreuses années, nous nous sommes efforcés de comprendre le comportement humain et nos interactions avec l'environnement sociotechnique. Grâce à l'avancée de nos connaissances dans ce domaine, nous avons contribué à la conception de technologies et de processus de travail nouveaux ou améliorés. Historiquement, une part importante du travail d'analyse des interactions sociales fut entreprise au sein des sciences sociales. Cependant, la simulation informatique a apporté un nouvel outil pour tenter de comprendre et de modéliser les comportements humains. En utilisant une approche à base d'agents, cette présentation décrit mon travail sur la construction de modèles informatiques du comportement humain pour guider la conception par la simulation. A l'aide d'exemples issus de projets des deux domaines d'application que sont la gestion des crises et de l'urgence et la gestion de l'énergie, je décris comment mon travail aborde certains problèmes centraux à la simulation sociale à base d'agents. Le premier concerne le processus par lequel nous développons ces modèles. Le second problème provient de la nature des systèmes sociotechniques. Les sociétés humaines constituent un exemple parfait de système complexe possédant des caractéristiques d'auto-organisation et d'adaptabilité, et affichant des phénomènes émergents tels que la coopération et la robustesse. Je décris comment la théorie des systèmes complexes peut être appliquée pour améliorer notre compréhension des systèmes sociotechniques, et comment nos interactions au niveau microscopique mènent à l'émergence d'une conscience mutuelle pour la résolution de problèmes. A partir de systèmes de simulation à base d'agents, je montre comment la conscience du contexte peut être modélisée. En terme de perspectives, j'expliquerai comment la hausse de la prévalence des agents artificiels dans notre société nous forcera à considérer de nouveaux types d'interactions et de comportements coopératifs

Global board games project:a cross-border entrepreneurship experiential learning initiative

Entrepreneurship training and development in the context of higher education has grown tremendously over the past four decades. What began as offerings of a handful of courses aimed primarily at business planning and small business management has evolved into over 3.000 higher education institutions around the world offering degree programs and concentrations in entrepreneurship on both undergraduate and graduate levels (Morris, Kuratko and Cornwall, 2013). Universities – particularly in the USA, UK and EU – have invested into developing entrepreneurship curricula but also extra-curricular programs and infrastructure aimed at supporting enterprise development. It is consensus among educators that entrepreneurship can be taught (Kuratko, 2005). Indeed, entrepreneurship education research has become a field in its own right (Fayolle, Gailly and Lassas‐Clerc, 2006; Pittaway and Cope, 2007; Penaluna, Penaluna and Jones, 2012; Fayolle, 2013; Fayolle and Gailly, 2015; Pittaway et al., 2015; Nabi et al., 2017). As literature indicates, entrepreneurship education can have an important impact on a variety of outcomes, including entrepreneurial intentions and behaviours. Intentions are a motivation to engage in certain behaviour that is geared towards venture creation (Gibb, 2008, 2011) as well as recognition and exploitation of opportunities (Shane and Venkataraman, 2000). Moreover, research has also identified the impact of entrepreneurship education on more subjective indicators such as attitudes (Boukamcha, 2015), perceived feasibility (Rauch and Hulsink, 2015), and skills and knowledge (Greene and Saridakis, 2008). Recently, the literature on the best practices in entrepreneurship education has centred on the importance of experiential learning allowing students to create knowledge from their interactions with the environment (Kolb, 1984). The key to effective experiential learning is engaging students individually and socially in a situation that enables them to interact with elements of the entrepreneurial context thus moving them away from text-driven to action-driven learning mode (Morris, Kuratko and Cornwall, 2013). Increasingly, digital technologies have been leveraged to create a learning environment that provides opportunities for experiential learning (Onyema and Daniil, 2017). This chapter provides findings of a study related to the development and implementation of a collaborative, digitally supported simulation project aimed at enhancing entrepreneurial social skills in an international context

Mascaret: Pedagogical multi-agents system for virtual environment for training.

International audienceThis study concerns virtual environments for training in operational conditions. The principal developed idea is that these environments are heterogeneous and open multi-agent systems. The MASCARET model is proposed to organize the interactions between agents and to provide them reactive, cognitive and social abilities to simulate the physical and social environment. The physical environment represents, in a realistic way, the phenomena that learners and teachers have to take into account. The social environment is simulated by agents executing collaborative and adaptive tasks. These agents realize, in team, procedures that they have to adapt to the environment. The users participate to the training environment through their avatar. In this article, we explain how we integrated, in MASCARET, models necessary to the creation of Intelligent Tutoring System. We notably incorporate pedagogical strategies and pedagogical actions. We present pedagogical agents. To validate our model, the SÉCURÉVI application for fire-fighters training is developed

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains