Building an effective school-university partnership : a cluster approach

Deakin University has introduced a new Master of Teaching course incorporating a new form school-university partnership that we refer to as the ‘cluster approach’. In addition to responding to recent state and National reports on teacher education (e.g. House of Representatives Standing Committee on Education and Vocational Training, 2007; Kruger et al., 2009; Parliament of Victoria Education and Training Committee, 2005), this cluster approach aims to respond directly to recommendations from the Australian Teaching and Learning Council funded project into practicum partnerships (Ure, 2009), and focuses specifically on one of the reform agendas of the National Partnership Agreement on Improving Teacher Quality, that of ‘improving the quality and consistency of teacher training in partnership with universities’ (see http://smarterschools.gov.au/nationalpartnerships/Pages/ImprovingTeacherQuality.aspx)
Learning to teach is a continuum whereby teachers create new understandings and build professional knowledge and practice in collaboration with colleagues during their pre-service teacher education and then during their careers as teachers (Fieman-Nemser 2001). Learning to teach is not a sole learning activity; rather teachers learn in communities and in collaboration with colleagues. Moreover, teachers are always balancing ‘being the teacher’ while at the same time ‘becoming a teacher’ (e.g. Britzman, 2003). Thus, they balance the notion of ‘doing teaching’ while at the same time ‘learning teaching’, and this is nowhere more evident than during the professional experience component of teacher education. This cluster approach is based on these premises.
The work of Le Cornu (2004), Le Cornu and Ewing (2008) and Little (2001) also informed aspects of the approach, which is predicated on ‘reciprocal relationships’ amongst pre-service teachers, and between pre-service teachers and experienced teachers both in schools and in universities. It frames teachers as cultural producers of knowledge, pre-service teachers as new resources bringing different ideas and practices into schools and schools as knowledge building communities (Little 2001, Nias 1998, Retallick et al 1999, Veugelers & O’Hair 2005).

A microfluidic system for testing the responses of head and neck squamous cell carcinoma tissue biopsies to treatment with chemotherapy drugs

Tumors are heterogeneous masses of cells characterized pathologically by their size and spread. Their chaotic biology makes treatment of malignancies hard to generalize. We present a robust and reproducible glass microfluidic system, for the maintenance and “interrogation” of head and neck squamous cell carcinoma (HNSCC) tumor biopsies, which enables continuous media perfusion and waste removal, recreating in vivo laminar flow and diffusion-driven conditions. Primary HNSCC or metastatic lymph samples were subsequently treated with 5-fluorouracil and cisplatin, alone and in combination, and were monitored for viability and apoptotic biomarker release ‘off-chip’ over 7 days. The concentration of lactate dehydrogenase was initially high but rapidly dropped to minimally detectable levels in all tumor samples; conversely, effluent concentration of WST-1 (cell proliferation) increased over 7 days: both factors demonstrating cell viability. Addition of cell lysis reagent resulted in increased cell death and reduction in cell proliferation. An apoptotic biomarker, cytochrome c, was analyzed and all the treated samples showed higher levels than the control, with the combination therapy showing the greatest effect. Hematoxylin- and Eosin-stained sections from the biopsy, before and after maintenance, demonstrated the preservation of tissue architecture. This device offers a novel method of studying the tumor environment, and offers a pre-clinical model for creating personalized treatment regimens.

Cluster identification and separation in the growing self-organizing map: application in protein sequence classification

Growing self-organizing map (GSOM) has been introduced as an improvement to the self-organizing map (SOM) algorithm in clustering and knowledge discovery. Unlike the traditional SOM, GSOM has a dynamic structure which allows nodes to grow reflecting the knowledge discovered from the input data as learning progresses. The spread factor parameter (SF) in GSOM can be utilized to control the spread of the map, thus giving an analyst a flexibility to examine the clusters at different granularities. Although GSOM has been applied in various areas and has been proven effective in knowledge discovery tasks, no comprehensive study has been done on the effect of the spread factor parameter value to the cluster formation and separation. Therefore, the aim of this paper is to investigate the effect of the spread factor value towards cluster separation in the GSOM. We used simple k-means algorithm as a method to identify clusters in the GSOM. By using Davies–Bouldin index, clusters formed by different values of spread factor are obtained and the resulting clusters are analyzed. In this work, we show that clusters can be more separated when the spread factor value is increased. Hierarchical clusters can then be constructed by mapping the GSOM clusters at different spread factor values.