Differentiated Instruction at Work. Reinforcing the art of classroom observation through the creation of a checklist for beginning and pre-service teachers

Professional experience is viewed as integral to shaping philosophy and acquiring skills in the area of classroom teaching. Classrooms are complex places, with educators implementing differentiated strategies to cater for student diversity. Pre-service teachers who observe these lessons often miss the intuitive practices, as there is much to absorb during a typical observation session. Equipping them with a checklist enhances this experience, giving them intentional guidelines with regard to observation. The current study, utilized a qualitative approach, to gain an understanding of specific dynamics that impact on a pre-service teacher’s professional experience. The intersection of data and the literature led to the creation of a checklist for use by beginning and pre-service teachers. The checklist may be used by teacher educators as an instrument to assist with the preparation of teachers, as it could help with honing in on key elements of observation of classroom practice and differentiated strategies

Gaussian Belief with dynamic data and in dynamic network

In this paper we analyse Belief Propagation over a Gaussian model in a dynamic environment. Recently, this has been proposed as a method to average local measurement values by a distributed protocol ("Consensus Propagation", Moallemi & Van Roy, 2006), where the average is available for read-out at every single node. In the case that the underlying network is constant but the values to be averaged fluctuate ("dynamic data"), convergence and accuracy are determined by the spectral properties of an associated Ruelle-Perron-Frobenius operator. For Gaussian models on Erdos-Renyi graphs, numerical computation points to a spectral gap remaining in the large-size limit, implying exceptionally good scalability. In a model where the underlying network also fluctuates ("dynamic network"), averaging is more effective than in the dynamic data case. Altogether, this implies very good performance of these methods in very large systems, and opens a new field of statistical physics of large (and dynamic) information systems.Comment: 5 pages, 7 figure

“Bringing Our Small, Imperfect Stones to the Pile”: The Everyday Work of Building a More Just World

In this conversation between Brittany Pearl Battle and Tamara K. Nopper (facilitated by Antonia Randolph), two sociologists who have been involved in a variety of social justice struggles (e.g. prison abolition, worker’s rights, Asian American rights), describe the everyday practices that make up struggles for social justice. They identify a spectrum of practices that individuals can do to bring about a more just world, while arguing that all practices towards justice do not constitute organizing or activism. Moreover, they describe the salience of their status as workers and women of color as structuring the ways they have pursued social change at different points in their lives. In so doing, they identify academia as a workplace rather than being an academic as a status as the salient force that shapes how they work to build a more just world. Ultimately, the article questions the usefulness of the designation scholar-activist, opting to recognize the unique role of activists in social change while affirming that we all bring what we can to struggles for justice

'Big data' approaches for novel anti-cancer drug discovery

Introduction: The development of improved cancer therapies is frequently cited as an urgent unmet medical need. Here we review how recent advances in platform technologies and the increasing availability of biological ‘big data’ are providing an unparalleled opportunity to systematically identify the key genes and pathways involved in tumorigenesis. We then discuss how these discoveries may be amenable to therapeutic interventions. Areas covered: We discuss the current approaches that use ‘big data’ to identify cancer drivers. These approaches include genomic sequencing, pathway data, multi-platform data, identifying genetic interactions such as synthetic lethality and using cell line data. We review how big data is being used to assess the tractability of potential drug targets and how systems biology is being utilised to identify novel drug targets. We finish the review with an overview of available data repositories and tools being used at the forefront of cancer drug discovery. Expert opinion: Targeted therapies based on the genomic events driving the tumour will eventually inform treatment protocols. However, using a tailored approach to treat all tumour patients may require developing a large repertoire of targeted drugs

Causal connectivity of evolved neural networks during behavior

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics

A Documentation Review of Yoruba Indigenous Architectural Morphology

The indigenous architecture of the Yoruba which is the summation of the traditional, the vernacular and the contemporary ethno-acculturation of contemporary styles has not received a robust level of reporting from recent publications. This study was carried out with the sole aim of organizing the various lines of thought into a continuum for defining the evolution of the Yoruba architecture in the simplest way. A search was conducted in the Social Science Citations Index and Google Scholar to sift out the publications with “Yoruba Architecture” and “Southwest Nigeria Architecture” as search words. Thirty relevant publications of the sixty-seven publications that related to the topic among others were selected for further scrutiny. It was discovered that most of the publications were descriptive and eclectic in their analysis. They sought to explain the architecture basically as a spatial product of the socio-cultural demands of the society. The traditional and vernacular styles are well documented and easily explained by this approach. There was however very little attempt to decipher the current threshold of the indigenous architecture in the face of the overwhelming influence of the postmodern and contemporary building styles that are common in Yoruba towns of recent. Keywords: International style, post vernacular architecture, postmodern architecture, traditional architecture, vernacular architecture, thresholds. DOI: 10.7176/JAAS/66-05 Publication date:July 31st 202

Equilibration through local information exchange in networks

We study the equilibrium states of energy functions involving a large set of real variables, defined on the links of sparsely connected networks, and interacting at the network nodes, using the cavity and replica methods. When applied to the representative problem of network resource allocation, an efficient distributed algorithm is devised, with simulations showing full agreement with theory. Scaling properties with the network connectivity and the resource availability are found.Comment: v1: 7 pages, 1 figure, v2: 4 pages, 2 figures, simplified analysis and more organized results, v3: minor change