Network mechanisms of intentional learning

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flex- ible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ven- tral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple dis- tinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.

Networked learning ten years on: the rise of the virtual graduate school

The aim of this paper is to reflect on how conceptions of networked learning have changed, particularly in relation to educational practices and uses of technology, that can nurture new ideas of networked learning to sustain multiple and diverse communities of practice in institutional settings. Our work is framed using two theoretical frameworks: Giddens's (1984) structuration theory and Callon & Latour's (1981) Actor Network Theory as critiqued by Fox (2005) in relation to networked learning. We use these frameworks to analyse and critique ideas of networked learning embodied in both cases. We investigate three questions: (a) the role of individual agency in the development of networked learning; (b) the impact of technological developments on approaches to supporting students within institutional infrastructures; and (c) designing networked learning to incorporate Web 2.0 practices that sustain multiple communities and foster engagement with knowledge in new ways. We use an interpretivist approach by drawing on experiential knowledge of the Masters programme in Networked Collaborative Learning and the decision making process of designing the virtual graduate schools. At this early stage, we have limited empirical data related to the student experience of networked learning in current and earlier projects. Our findings indicate that the use of two different theoretical frameworks provided an essential tool in illuminating, situating and informing the process of designing networked learning that involves supporting multiple and diverse communities of practice in institutional settings. These theoretical frameworks have also helped us to analyze our existing projects as case studies and to problematize and begin to understand the challenges we face in facilitating the participation of research students in networked learning communities of practice and the barriers to that participation. We have also found that this process of theorizing has given us a way of reconceptualizing communities of practice within research settings that have the potential to lead to new ideas of networked learning.