"Is music something 'out there', a kind of structure or artefact, that can be dealt with in a static way? Or does it rely on processes which call forth interactions with the sounds? Should we conceive of music users besides the music, and think about music as something which is perceived, conceptualised and enacted upon in order to be meaningful? Is music an ontological category, or a sounding phenomenon that calls forth epistemic interactions with the sounds? And can music be considered as a sonic environment and the music user as an organism that generates music knowledge as a tool for adaptation to the sonic world?
These questions revolve around the ecological concept of coping with the (sonic) world (Reybrouck, 2001a, 2005a, b). Musical sense–making, in this view, can be addressed in terms of interactions with the sounds, both at the level of perception, action and mental processing. It is a position that broadens the scope of music research, encompassing all kinds of music and sounds, and going beyond any kind of cultural and historical constraints. Music, in this broadened view, is to be defined as a collection of sound/time phenomena which have the potential of being structured, with the process of structuring being as important as the structure of the music. As such, it is possible to transcend a merely structural description of the music in favour of a process–like description of the ongoing process of maintaining epistemic contact with the music as a sounding environment. A central focus, in this approach, is on the role of musical experience and the way how listeners make sense of music as it sounds (see Blacking, 1955; Määttänen, 1993; Reybrouck, 2004; Westerlund, 2002)."
(Mark Reybrouck, 2012)
Reybrouck, M. (2012). "Musical sense–making and the concept of affordance: an ecosemiotic and experiential approach". Biosemiotics, 5 (3), 391–409.
"Despite their important implications for interpersonal behaviors and relations, cognitive abilities have been largely ignored as explanations of prejudice. We proposed and tested mediation models in which lower cognitive ability predicts greater prejudice, an effect mediated through the endorsement of right–wing ideologies (social conservatism, right–wing authoritarianism) and low levels of contact with out–groups. In an analysis of two large–scale, nationally representative United Kingdom data sets (N = 15,874), we found that lower general intelligence (g) in childhood predicts greater racism in adulthood, and this effect was largely mediated via conservative ideology. A secondary analysis of a U.S. data set confirmed a predictive effect of poor abstract–reasoning skills on antihomosexual prejudice, a relation partially mediated by both authoritarianism and low levels of intergroup contact. All analyses controlled for education and socioeconomic status. Our results suggest that cognitive abilities play a critical, albeit underappreciated, role in prejudice. Consequently, we recommend a heightened focus on cognitive ability in research on prejudice and a better integration of cognitive ability into prejudice models."
(Gordon Hodson and Michael A. Busseri, 2012)
Hodson, G. and M. Busseri (2012). "Bright Minds and Dark Attitudes: Lower Cognitive Ability Predicts Greater Prejudice Through Right–Wing Ideology and Low Intergroup Contact." Psychological Science 23(2): 187–195.
"A central tenet of most learning theories is that learning occurs inside a person. Even social constructivist views, which hold that learning is a socially enacted process, promotes the principality of the individual (and her/his physical presence–i.e. brain–based) in learning. These theories do not address learning that occurs outside of people (i.e. learning that is stored and manipulated by technology)... In a networked world, the very manner of information that we acquire is worth exploring. The need to evaluate the worthiness of learning something is a meta–skill that is applied before learning itself begins. When knowledge is subject to paucity, the process of assessing worthiness is assumed to be intrinsic to learning. When knowledge is abundant, the rapid evaluation of knowledge is important. The ability to synthesize and recognize connections and patterns is a valuable skill. Including technology and connection making as learning activities begins to move learning theories into a digital age. We can no longer personally experience and acquire learning that we need to act. We derive our competence from forming connections. Karen Stephenson states: 'Experience has long been considered the best teacher of knowledge. Since we cannot experience everything, other people's experiences, and hence other people, become the surrogate for knowledge. 'I store my knowledge in my friends' is an axiom for collecting knowledge through collecting people.
Connectivism is the integration of principles explored by chaos, network, and complexity and self–organization theories"
(George Siemens, P2P Foundation)
"The resource covers basic logic and faulty arguments, developing student's critical thinking skills. Suitable for year 8–10, focused on science issues, the module can be adapted to suit classroom plans."
"TechNyou was established to meet a growing community need for balanced and factual information on emerging technologies. We are funded by the Australian Government Department of Industry, Innovation, Science, Research and Tertiary Education (DIISRTE). We operate in partnership with the University of Melbourne, where our office is based."
"Big data smacks of the centralization fads we've seen in each computing era. The thought that 'hey there's more data than we can process!' (something which is no doubt always true year–on–year since computing began) is dressed up as the latest trend with associated technology must–haves.
Meanwhile we risk overlooking the much more important story here, the real revolution, which is the mass democratisation of the means of access, storage and processing of data. This story isn't about large organisations running parallel software on tens of thousand of servers, but about more people than ever being able to collaborate effectively around a distributed ecosystem of information, an ecosystem of small data. ...
And when we want to scale up the way to do that is through componentized small data: by creating and integrating small data "packages" not building big data monoliths, by partitioning problems in a way that works across people and organizations, not through creating massive centralized silos.
This next decade belongs to distributed models not centralized ones, to collaboration not control, and to small data not big data."
(Rufus Pollock, 25 April 2013)