Shared Education in contested spaces: How collaborative networks improve communities and schools

Societies which suffer from ethnic and political divisions are often characterised by patterns of social and institutional separation, and sometimes these divisions remain even after political conflict has ended. This has occurred in Northern Ireland where there is, and remains, a long-standing pattern of parallel institutions and services for the different communities. A socially significant example lies in the education system where a parallel system of Catholic and Protestant schools has been in place since the establishment of a national school system in the 1830s. During the years of political violence in Northern Ireland a variety of educational interventions were implemented to promote reconciliation, but most of them failed to create any systemic change. This paper describes a post-conflict educational initiative known as Shared Education which aims to promote social cohesion and school improvement by encouraging sustained and regular shared learning between students and broader collaboration between teachers and school leaders from different schools. The paper examines the background to work on Shared Education, describes a ‘sharing continuum’ which emerged as an evaluation and policy tool from this work and considers evidence from a case study of a Shared Education school partnership in a divided city in Northern Ireland. The paper will conclude by highlighting some of the significant social and policy impact of the Shared Education work.

A case study of teaching and learning practice in a Chinese adult institution

Résumé: Cette recherche s'est réalisée dans une institution chinoise de formation des adultes. Il existe très peu d'études présentant la pratique de l'enseignement et de l'apprentissage en Chine. Aussi, il semble que cette étude de cas puisse être utile. Elle porte sur le personnel de formation en administration économique dans un centre de formation de Tianjin. Le but premier de cette recherche est de décrire ce qui se fait à cet institut de formation des adultes. Les aspects couverts vont de la sélection du contenu de formation et des modalités d'enseignement jusqu'à la compréhension de l'enseignement et de l'apprentissage. À partir de l'expérience des professeurs de ce centre de Tianjin, cette étude cherche précisément à décrire leurs perceptions et leurs attitudes en regard d'un enseignement centré sur l'apprentissage et développé selon un mode de collaboration. Les fondements théoriques retenus s'inspirent des conceptions andragogiques de Knowles, de celles de Brookfield qui ont trait aux rôles des formateurs et formatrices d'adultes et de Conti qui présente une conception de l'enseignement qui se développe selon un mode de collaboration. Les données sont été retenues à la suite d'interviews et de questionnaires. Ce dernier instrument a été administré à 70 professeurs de formation aux adultes. Les résultats obtenus sont décrits et analysés. Les principaux éléments indiquent que la pratique actuelle de formation des adultes à ce centre de Tianjin ne tient pas compte des principes de l'éducation des adultes présenté selon un mode de collaboration. La formation est centrée sur l'enseignement. Il est à souhaiter que cette recherche contribuera à développer une meilleure compréhension de l'enseignement et de l'apprentissage en Chine tel que perçus par les formateurs et formatrices. Quelques suggestions de recherche complémentaires sont proposées à la fin.||Abstract: The present study grew out of one Chinese adult institute. Relatively few works are available that present a view of what actually happens in Chinese adult teaching and learning practice. Accordingly, it is believed that a case study on Tianjin Institute of Training Economic Management Personnel (TITEMP) which has been working for years in varions forms of adult programs, will be very useful addition to the knowledge of Chinese adult teaching and learning. The primary purpose of the present study is to serve as an introduction to one Chinese adult institute (TITEMP) in terms of characteristics of teaching, including selecting teaching content and teaching pattern, and to expand the understanding of Chinese adult teaching and learning. Based on the experiences of teachers at TITEMP, the study seeks to investigate the issues of teacher's perceptions and attitudes of teaching and learning to obtain implications toward learning-centred and collaborative mode. The theoretical foundations include andragogical conceptions (Knowles), roles of adult teachers (Brookfield), and conceptions of collaborative teaching and learning mode (Conti). The main sources of data are: the interviews and results of the questionnaire. Questionnaire responses from 70 teachers with knowledge of adult teaching and learning are described and interpreted. The general findings of the study are that the existing adult teaching practice at TITEMP does not adequately account for the principles of adult learning in a collaborative mode with adult students. Adult learning is teaching-centred. Some suggestions for further research are offered. It is hoped and believed that this research will contribute to a better understanding of Chinese adult teaching and learning in general, more particularly to the empirical study of the teachers from teaching and learning perspective in a Chinese adult higher learning setting. The research findings will be used as basis for the exploration of Chinese adult teaching.

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.

Collaborative technologies, higher order thinking and self-sufficient learning: A case study of adult learners

The inclusion of online elements in learning environments is becoming commonplace in Post Compulsory Education. A variety of research into the value of such elements is available, and this study aims to add further evidence by looking specifically at the use of collaborative technologies such as online discussion forums and wikis to encourage higher order thinking and self-sufficient learning. In particular, the research examines existing pedagogical models including Salmon’s five-stage model, along with other relevant literature. A case study of adult learners in community-based learning centres forms the basis of the research, and as a result of the findings, an arrow model is suggested as a framework for online collaboration that emphasises the learner, mentions pre-course preparation and then includes three main phases of activity: post, interact and critique. This builds on Salmon’s five-stage model and has the benefit of being flexible and responsive, as well as allowing for further development beyond the model, particularly in a blended learning environment.

The Process of Simulation Authoring/Creation by Chemistry Teachers: A Service Learning Experience

Two case studies are presented to describe the process of public school teachers authoring and creating chemistry simulations. They are part of the Virtual Didactic Laboratory for Chemistry, a project developed by the School of the Future of the University of Sao Paulo. the documental analysis of the material produced by two groups of teachers reflects different selection process for both themes and problem-situations when creating simulations. The study demonstrates the potential for chemistry learning with an approach that takes students' everyday lives into account and is based on collaborative work among teachers and researches. Also, from the teachers' perspectives, the possibilities of interaction that a simulation offers for classroom activities are considered.

Students' collective knowledge construction in the virtual learning environment ""ToLigado - your school interactive newspaper""

Introduction. The ToLigado Project - Your School Interactive Newspaper is an interactive virtual learning environment conceived, developed, implemented and supported by researchers at the School of the Future Research Laboratory of the University of Sao Paulo, Brazil. Method. This virtual learning environment aims to motivate trans-disciplinary research among public school students and teachers in 2,931 schools equipped with Internet-access computer rooms. Within this virtual community, students produce collective multimedia research documents that are immediately published in the portal. The project also aims to increase students' autonomy for research, collaborative work and Web authorship. Main sections of the portal are presented and described. Results. Partial results of the first two years' implementation are presented and indicate a strong motivation among students to produce knowledge despite the fragile hardware and software infrastructure at the time. Discussion. In this new environment, students should be seen as 'knowledge architects' and teachers as facilitators, or 'curiosity managers'. The ToLigado portal may constitute a repository for future studies regarding student attitudes in virtual learning environments, students' behaviour as 'authors', Web authorship involving collective knowledge production, teachers' behaviour as facilitators, and virtual learning environments as digital repositories of students' knowledge construction and social capital in virtual learning communities.

CONTRASTING PHYLOGEOGRAPHIC PATTERNS IN MITOCHONDRIAL DNA AND MICROSATELLITES: EVIDENCE OF FEMALE PHILOPATRY AND MALE-BIASED GENE FLOW AMONG REGIONAL POPULATIONS OF THE BLUE-AND-YELLOW MACAW (PSITTACIFORMES: ARA ARARAUNA) IN BRAZIL

Comparing the patterns of population differentiation among genetic markers with different modes of inheritance call provide insights into patterns of sex-biased dispersal and gene flow. The blue-and-yellow Macaw (Ara ararauna) is a Neotropical parrot with a broad geographic distribution ill South America. However, little is known about the natural history and current status Of remaining wild populations, including levels of genetic variability. The progressive decline and possible fragmentation of populations may endanger this species in the near future. We analyzed mitochondrial DNA (mtDNA) control-region sequences and six microsatellite 106 Of Blue-and-yellow Macaws sampled throughout their geographic range ill Brazil to describe population genetic Structure, to make inferences about historical demography and dispersal behavior, and to provide insight for conservation efforts. Analyses of population genetic structure based on mtDNA showed evidence of two major populations ill western and eastern Brazil that share a few low-frequency haplotypes. This phylogeographic pattern seems to have originated by the historical isolation of Blue-and-yellow Macaw populations similar to 374,000 years ago and has been maintained by restricted gene flow and female philopatry. By contrast, variation ill biparentally inherited microsatellites was not structured geographically, Male-biased dispersal and female philopatry best explain the different patterns observed in these two markers. Because females disperse less than males, the two regional populations with well-differentiated mtDNA haplogroups should be considered two different management units for conservation purposes. Received 4 November 2007 accepted 10 December 2008.

Two-dimensional supersonic nonlinear Schrodinger flow past an extended obstacle

Supersonic flow of a superfluid past a slender impenetrable macroscopic obstacle is studied in the framework of the two-dimensional (2D) defocusing nonlinear Schroumldinger (NLS) equation. This problem is of fundamental importance as a dispersive analog of the corresponding classical gas-dynamics problem. Assuming the oncoming flow speed is sufficiently high, we asymptotically reduce the original boundary-value problem for a steady flow past a slender body to the one-dimensional dispersive piston problem described by the nonstationary NLS equation, in which the role of time is played by the stretched x coordinate and the piston motion curve is defined by the spatial body profile. Two steady oblique spatial dispersive shock waves (DSWs) spreading from the pointed ends of the body are generated in both half planes. These are described analytically by constructing appropriate exact solutions of the Whitham modulation equations for the front DSW and by using a generalized Bohr-Sommerfeld quantization rule for the oblique dark soliton fan in the rear DSW. We propose an extension of the traditional modulation description of DSWs to include the linear ""ship-wave"" pattern forming outside the nonlinear modulation region of the front DSW. Our analytic results are supported by direct 2D unsteady numerical simulations and are relevant to recent experiments on Bose-Einstein condensates freely expanding past obstacles.

Constant-random practice and the adaptive process in motor learning with varying amounts of constant practice

The adaptive process in motor learning was examined in terms of effects of varying amounts of constant practice performed before random practice. Participants pressed five response keys sequentially, the last one coincident with the lighting of a final visual stimulus provided by a complex coincident timing apparatus. Different visual stimulus speeds were used during the random practice. 33 children (M age=11.6 yr.) were randomly assigned to one of three experimental groups: constant-random, constant-random 33%, and constant-random 66%. The constant-random group practiced constantly until they reached a criterion of performance stabilization three consecutive trials within 50 msec. of error. The other two groups had additional constant practice of 33 and 66%, respectively, of the number of trials needed to achieve the stabilization criterion. All three groups performed 36 trials under random practice; in the adaptation phase, they practiced at a different visual stimulus speed adopted in the stabilization phase. Global performance measures were absolute, constant, and variable errors, and movement pattern was analyzed by relative timing and overall movement time. There was no group difference in relation to global performance measures and overall movement time. However, differences between the groups were observed on movement pattern, since constant-random 66% group changed its relative timing performance in the adaptation phase.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Resource use pattern analysis for predicting resource availability in opportunistic grids

This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

Learning for fun: The unique contribution of educational leisure experiences

What do visitors want or expect from an educational leisure activity such as a visit to a museum, zoo, aquarium or other such experience? Is it to learn something or to experience learning? This paper uses the term 'learning for fun' to refer to the phenomenon in which visitors engage in a learning experience because they value and enjoy the process of learning itself. Five propositions regarding the nature of learning for fun are discussed, drawing on quantitative and qualitative data from visitors to a range of educational leisure activities. The commonalities between learning for fun and other theoretical constructs such as 'experience,' 'flow', 'intrinsic motivation', and 'curiosity' are explored. It is concluded that learning for fun is a unique and distinctive offering of educational leisure experiences, with implications for future research and experience design.