Education in the Knowledge Society (Feb 2013)
Looking at learning communities with the appropriate glasses: hints and ideas from network sciences
Abstract
/* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-ansi-language:ES; mso-fareast-language:EN-US;} The level of network thinking within education – intended as the capacity to look at learning systems and communities by focussing on the relations among the involved actors (primarily teachers and learners) and not only on the actors characteristics – is growing, with different speeds depending on the educational sector, but not at the pace needed to keep up with the increasingly network nature of our societies. We claim that educational research and practices should increase their capacity to look at learning communities through appropriate “networking-sensitive” glasses, and get equipped with tools and methods – such as Social network Analysis - to properly understand and support these networks. The application of Social Network Analysis to education, especially in the case of distance learning, can allow understanding the patterns of interactions between teachers and learners, and can facilitate the consolidation of new approaches to understand collaboration mechanisms. The paper presents and discusses - from a learning viewpoint - a brief overview of the main theoretical and practical contributions coming from Social Network Analysis – such as the “random graphs”, the “small-worlds” or the “weak-ties” theories – together with some general properties and dynamics of networks, believing that mastering these dynamics is extremely important for educational researchers and practitioners, when it comes to understanding and supporting meaningful collaborative learning.
