Social behaviors and learning in smart communities

Abstract : Smart communities are at the heart of social innovation. Based on networks of people and knowledge, these communities are able to foster social knowledge building. Moreover, this social knowledge building process may produce through interaction more adequate and improved decision-making processes; focusing on work, learning, or policy definition. Smart communities’ analysis and benchmarking is of paramount importance for investigating the evolution of each community, and for producing models of social interaction, knowledge building and learning that concurrently create the basis of collective intelligence.Against this background, this special issue of the IxD&A journal brings together four educational technology studies covering different facets of smart communities, with an emphasis on their underlying technologies. The authors discuss the phenomenon as follows. In first article in this issue, “Designing Smart Knowledge Building Communities”, Ambar Murillo Montes de Oca, Nicolae Nistor (Ludwig-Maximilians-Universität München, Germany), Mihai Dascalu and Ștefan Trausan-Matu (University Politehnica of Bucharest, Romania) take a larger perspective on knowledge building communities (KBC). KBCs represent environments where participants are engaged in collaborative discourse, along with the development and the use of conceptual artifacts, while the collective knowledge base is gradually being expanded upon. Automatic tools are suggested for such communities in order to foster and monitor the development and use of collaborative discourse and conceptual artifacts. Finally, recommendations for the design of smart KBCs are provided. In keeping with the previous definition of KBC, in the article “Newcomer Integration in Online Knowledge Building Communities: Automated Dialogue Analysis in Integrative vs. Non-Integrative Blogger Communities” the authors Nicolae Nistor (Ludwig-Maximilians-Universität München, Germany), Costin-Gabriel Chiru (University Politehnica of Bucharest, Romania) and Nicolas Bresser (Universität der Bundeswehr, München, Germany) search for predictors of newcomer integration in existing KBCs by employing an automated analysis tool for comparing two dialogues in terms of lexical chain occurrences and inter-animation moments. Further on, Zinayida Petrushyna, Ralf Klamma and Matthias Jarke (Rheinisch-Westfälische Technische Hochschule Aachen, Germany) in their article “The Impact of Culture On Smart Community Technology: The Case of 13 Wikipedia Instances” perceive smart communities as being capable of providing themselves with technologies for monitoring social behaviors inside communities. Nevertheless, the underlying technologies that support knowledge building should consider the cultural background of community members. Since users with different cultural backgrounds build knowledge in different ways, social network analysis can be employed to define the different requirements for the technologies used in smart communities across different cultures. Taking a different perspective, Thomas Köhler, Sander Münster and Lars Schlenker (Technische Universität Dresden, Germany), attempt in their paper “Smart communities in virtual reality. A comparison of design approaches for academic education” to define smart communities by adopting „virtual reality” (VR) for a wide variety of purposes, among which potential educational scenarios are of particular interest. Overall, VR offers the possibility to create complex learning and working environments in terms of social interaction in communication and collaboration processes. Subsequently, smart communities should also establish a VR ecosystem while providing support for a variety of educational communities that make use of ICT for teaching and learning. Beyond the widespread adoption of ICT, smart communities can especially profit from the use of VR technologies in order to bridge spatial and time gaps in members’ collaborations. All in all, natural language processing techniques, discourse analysis, social networks analysis, virtual reality and other analytics tools concur to outline a comprehensive toolkit aimed at capturing the multiple facets of social interaction and of learning processes that take place in smart communities.
Type de document :
Direction d'ouvrage, Proceedings, Dossier
Liste complète des métadonnées

http://hal.univ-grenoble-alpes.fr/hal-01226347
Contributeur : Philippe Dessus <>
Soumis le : lundi 9 novembre 2015 - 12:48:45
Dernière modification le : jeudi 21 juin 2018 - 15:28:05

Identifiants

  • HAL Id : hal-01226347, version 1

Collections

UGA | TICE | LSE

Citation

Mihai Dascălu, Philippe Dessus, Nicolae Nistor, Ștefan Trăușan-Matu. Social behaviors and learning in smart communities. Roma, Italy. 22, 68 p., 2014, IxD&A, 1826-9745. 〈http://www.mifav.uniroma2.it/inevent/events/idea2010/index.php?s=9#〉. 〈hal-01226347〉

Partager

Métriques

Consultations de la notice

282