The Standing Conference on Teacher Education North-South (SCoTENS) Citizenship Website

This site been designed primarily to support students, staff and other professionals involved in Initial Teacher Education North or South. However, it should also be of interest to others within the formal and non-formal education sectors.Those involved with, or interested in, Education for Citizenship.

Religious segregation and teacher education in Northern Ireland

This paper surveys the extent of religious segregation in teacher education in Northern Ireland and notes that there are elements of separation within a general context of (increasing) common teacher education. With reference to liberal and communitarian theories the case for separate teacher education is considered. It is acknowledged that a case can be made for forms of separate teacher education in a liberal society but that certain limits or expectations should apply. A common teacher education is found to be desirable but it is suggested that in order to justify its dominant status in a plural environment it must be accommodating of religion, encourage dialogical engagement around concepts of shared fate and cultivate a sense of community. © 2010 Taylor & Francis.

Exploring diversity through ethos in initial teacher education

This paper considers whether there is value in introducing student teachers to schools of different ethos as part of their initial teacher education. A 2-year study of undergraduate post-primary student teachers at a university college in Northern Ireland reveals that encounters with schools of different ethos can help student teachers to understand differences between schools and their visions of education, as well as correcting misunderstandings and challenging stereotypes. It is argued that as a result of experiencing diverse examples of ethos, student teachers may also be helped to understand the complexity of schools as organisations and to position themselves and their professional practice within wider debates about the aims of education and schools as communities of practice. © 2008 Elsevier Ltd. All rights reserved.

Changes in quality and safety attributes throughout long term storage of tomato juice processed by high pressure.

Tomato is the second most widely grown vegetable crop across the globe and it is one of widely cultivated crops in Sri Lanka. However, tomato industry in Sri Lanka facing a problem of high postharvest loss (54%) during the glut coupled with heavy revenue loss to the country by importing processed products. The aim of this work is to develop shelf-stable tomato product with maximum quality characteristics using high pressure processing (HPP). Tomato juice with altered and unaltered pH was processed using HPP at 600 MPa for 1 min after blanching (90 oC/2 min). As a control tomato juice was subjected to thermal processing (TP) at 95 oC /20 min. Processed samples were stored under 20oC and 28oC for 9 month period and analysed for total viable count (TVC) and instrumental colour (L, a, b) value at 0,1,2 3, and 4 week and 2, 3, 6 and 9 months interval. The raw juice sample had initial 6.69 log10 CFU/ml and both TP and HPP caused a more than 4.69 log10 reduction in the TVC of juice and microbial numbers remained low throughout the storage period even at 3 months after storage irrespective of the storage temperature. Both TP and HPP treated samples had the redness ⤘a value’ of 14.44-17.15 just after processing and showed non-significant reduction with storage in all the treatments after 3 months. The storage study results and discussed in relation to the end goal and compared with the literature.

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

A Transatlantic Experience - Student and Teacher Perspective

Impact of Free Glasses and a Teacher Incentive on Children's Use of Eyeglasses: A Cluster-Randomized Controlled Trial.

Purpose: To study the effect of free glasses combined with teacher incentives on in-school glasses wear among Chinese urban migrant children. Design: Cluster-randomized controlled trial. Methods: Children with VA <= 6/12 in either eye due to refractive error in 94 randomly-chosen primary schools underwent randomization by school to receive free glasses, education on their use and a teacher incentive (Intervention), or glasses prescriptions only (Control). Intervention group teachers received a tablet computer if >= 80% of children given glasses wore them during un-announced visits 6 weeks and 6 months (main outcome) after intervention. Results: Among 4376 children, 728 (16.7%, mean age 10.9 years, 51.0% boys) met enrollment criteria and were randomly allocated, 358 (49.2%, 47 schools) to Intervention and 370 (50.8%, 47 schools) to Control. Among these, 693 children (95.2%) completed the study and underwent analysis. Spectacle wear was significantly higher at 6 months among Intervention children (Observed [main outcome]: 68.3% versus 23.9%, Adjusted Odds Ratio [OR]=11.5, 95% Confidence Interval [CI] 5.91-22.5, P<0.001; Self-reported: 90.6% versus 32.1%, OR = 43.7, 95% CI = 21.7-88.5, P < 0.001). Other predictors of observed wear at 6 months included baseline spectacle wear (P<0.001), uncorrected VA<6/18 (P=0.01) and parental spectacle wear (P=0.02). The 6-month observed wear rate was only 41% among similar-aged children provided free glasses in our previous trial without teacher incentives. Conclusions: Free spectacles and teacher incentives maintain classroom wear in the large majority of children needing glasses over a school year. Low wear among Control children demonstrates the need for interventions.

Gatekeepers to the profession: recruitment to initial teacher education in the United Kingdom

We develop a framing for research on the relationship between context, process and outcomes in recruitment to the teaching profession. We do this through a ‘home international’ comparison of policies, outcomes and recruitment processes in England, Northern Ireland, Scotland and Wales. There is plenty of movement between these countries in the graduate labour market, but the contexts for teacher supply and demand vary in terms of: (i) scale, (ii) excess supply or demand, (iii) reliance of policy on market forces or bureaucracy and (iv) beliefs of policymakers about whether teaching is a craft or a profession. Recent changes in England and Wales have highlighted the importance of recruitment to initial teacher education (ITE as a policy issue whilst also creating further points of comparison which are useful for research. We draw on trends in data on recruitment to teaching and in-depth interviews with gatekeepers to the profession in each country.

Anomaly Detection for Data with Spatial Attributes

The problem of detecting spatially-coherent groups of data that exhibit anomalous behavior has started to attract attention due to applications across areas such as epidemic analysis and weather forecasting. Earlier efforts from the data mining community have largely focused on finding outliers, individual data objects that display deviant behavior. Such point-based methods are not easy to extend to find groups of data that exhibit anomalous behavior. Scan Statistics are methods from the statistics community that have considered the problem of identifying regions where data objects exhibit a behavior that is atypical of the general dataset. The spatial scan statistic and methods that build upon it mostly adopt the framework of defining a character for regions (e.g., circular or elliptical) of objects and repeatedly sampling regions of such character followed by applying a statistical test for anomaly detection. In the past decade, there have been efforts from the statistics community to enhance efficiency of scan statstics as well as to enable discovery of arbitrarily shaped anomalous regions. On the other hand, the data mining community has started to look at determining anomalous regions that have behavior divergent from their neighborhood.In this chapter,we survey the space of techniques for detecting anomalous regions on spatial data from across the data mining and statistics communities while outlining connections to well-studied problems in clustering and image segmentation. We analyze the techniques systematically by categorizing them appropriately to provide a structured birds eye view of the work on anomalous region detection;we hope that this would encourage better cross-pollination of ideas across communities to help advance the frontier in anomaly detection.

Think, code, succeed: The Programming Studio as a games-based collaboration:Paper published in the Proceedings of the Association for Teacher Education in Europe conference: Teacher Education through Partnerships and Collaborative Learning Communities, Glasgow, UK. ATEE, 2015

This paper investigates the profile of teachers in the island of Ireland who declared themselves willing to undertake professional development activities in programming, in particular to master programming by taking on-line courses involving the design of computer games. Using the Technology Acceptance Model (TAM), it compares scores for teachers “willing” to undertake the courses with scores for those who declined, and examines other differences between the groups of respondents. Findings reflect the perceived difficulties of programming and the current low status accorded to the subject in Ireland. The paper also reviews the use of games-based learning as a “hook” to engage learners in programming and discusses the role of gamification as a tool for motivating learners in an on-line course. The on-line course focusing on games design was met with enthusiasm, and there was general consensus that gamification was appropriate for motivating learners in structured courses such as those provided.