Everyday use of Spanish among bilingual teachers in New York City and their attitudes toward the language

The attitudes that bilingual teachers have toward the use of foreign languages seem to have an effect on the success of bilingual education programs. In this study, our purpose is to shed light on how often bilingual teachers in New York City use Spanish in their everyday lives, and to examine their attitudes toward the use of Spanish in the U.S. Overall, results indicate only moderate frequencies of use of Spanish in everyday life among bilingual teachers. In addition, the study shows that bilingual teachers have a favorable attitude toward the use of Spanish in the U.S. However, bilingual teachers whose first language is English seem to have a more favorable attitude than those whose first language is Spanish. Among the native Spanish speakers, those born abroad show a more favorable attitude than those born in the U.S. Although no group seems to favor the use of lexical borrowings and code-switching, bilingual native Spanish-speaking teachers born in the U.S. seem to have a less favorable attitude than native Spanish-speaking teachers born abroad. In addition, native Spanish-speaking teachers born abroad seem to have a less favorable attitude toward lexical borrowings and code-switching than U.S.-born teachers whose first language is English. Recommendations for the training of bilingual teachers are discussed in the conclusions of the study.

Description and training of neural network dynamics

Attractor properties of a popular discrete-time neural network model are illustrated through numerical simulations. The most complex dynamics is found to occur within particular ranges of parameters controlling the symmetry and magnitude of the weight matrix. A small network model is observed to produce fixed points, limit cycles, mode-locking, the Ruelle-Takens route to chaos, and the period-doubling route to chaos. Training algorithms for tuning this dynamical behaviour are discussed. Training can be an easy or difficult task, depending whether the problem requires the use of temporal information distributed over long time intervals. Such problems require training algorithms which can handle hidden nodes. The most prominent of these algorithms, back propagation through time, solves the temporal credit assignment problem in a way which can work only if the relevant information is distributed locally in time. The Moving Targets algorithm works for the more general case, but is computationally intensive, and prone to local minima.

Efficient training of RBF networks for classification.

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. We show how RBFs with logistic and softmax outputs can be trained efficiently using the Fisher scoring algorithm. This approach can be used with any model which consists of a generalised linear output function applied to a model which is linear in its parameters. We compare this approach with standard non-linear optimisation algorithms on a number of datasets.

Bayesian training of mixture density networks

Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

Efficient training of RBF networks for classification

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. In this paper we show how RBFs with logistic and softmax outputs can be trained efficiently using algorithms derived from Generalised Linear Models. This approach is compared with standard non-linear optimisation algorithms on a number of datasets.

Education and racism:a study of the teachers' and the pupils' relations in the schooling of black boys

This thesis examines the teachers' and the pupils' relations in the schooling of black boys. The study using the methodology of participant observation focusses on one school (Kilby) in an area of black population in an English city. The thesis’s intentions are two fold: firstly, in order to examine these relations, two major aspects of their interaction are addressed, that of the absence of teachers from conventional 'race-relations' research, and, the identification and examination of the anti-school pupils' sub-cultures. Two substantive questions are asked: what is the response of the teachers to the schooling of black pupils? and, what is the meaning of the pupils' resistance to schooling? Secondly, in attempting to answer these questions and offer a critique of the dominant 'race-relations' culturalist explanation of black youth's response to schooling, a theoretical framework has been developed which takes account of both the 'economic' and the 'sociological' perspectives. Methodology allowed and pointed to the importance of examining the teachers' ideologies and practices as well as those of the black boys. It is argued that a class analysis of the racially structured British society is more adequate than the conventional ethnic approach in explaining the black boys' location within Kilby School. Hence, it is posited that the major problem in the schooling of black youth is not that of their culture but of racism, which pervasively structures the social reality at Kilby school. Racism is mediated both through the existing institutional framework that discriminates against working-class youth and through the operation of race specific mechanisms, such as the process of racist stereotyping. It is thus further argued that the Kilby school teachers are of central causal significance to the - problems that the boys encounter. Furthermore, it is in response to these racist ideologies and practices that both West Indian and Asian pupils develop specific forms of collective resistance, which are seen to be linked to the wider black community, as legitimate strategies of survival.

An initial evaluation of gellan gum as a material for tissue engineering applications

Alpha-modified minimum essential medium (αMEM) has been found to cross-link a 1% gellan gum solution, resulting in the formation of a self-supporting hydrogel in 1:1 and 5:1 ratios of polysaccharide: αMEM. Rheological data from temperature sweeps confirm that in addition to orders of magnitude differences in G' between 1% gellan and 1% gellan with αMEM, there is also a 20°C increase in the temperature at which the onset of gelation takes place when αMEM is present. Frequency sweeps confirm the formation of a true gel; mechanical spectra for mixtures of gellan and αMEM clearly demonstrate G' to be independent of frequency. It is possible to immobilize cells within a three-dimensional (3D) gellan matrix that remain viable for up to 21 days in culture by adding a suspension of rat bone marrow cells (rBMC) in αMEM to 1% gellan solution. This extremely simple approach to cell immobilization within 3D constructs, made possible by the fact that gellan solutions cross-link in the presence of millimolar concentrations of cations, poses a very low risk to a cell population immobilized within a gellan matrix and thus indicates the potential of gellan for use as a tissue engineering scaffold. © 2007 Sage Publications.

Discriminative training of the hidden vector state model for semantic parsing

In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

The use of open learning in the training of neurotechnologists:a regional case study

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

The education and training of technicians in the construction industry

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

The effectiveness of an organisations' equal opportunities policy for the role and training of women, particularly in the fire service

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

The development of a semantic model for the interpretation of mathematics including the use of technology

The semantic model developed in this research was in response to the difficulty a group of mathematics learners had with conventional mathematical language and their interpretation of mathematical constructs. In order to develop the model ideas from linguistics, psycholinguistics, cognitive psychology, formal languages and natural language processing were investigated. This investigation led to the identification of four main processes: the parsing process, syntactic processing, semantic processing and conceptual processing. The model showed the complex interdependency between these four processes and provided a theoretical framework in which the behaviour of the mathematics learner could be analysed. The model was then extended to include the use of technological artefacts into the learning process. To facilitate this aspect of the research, the theory of instrumentation was incorporated into the semantic model. The conclusion of this research was that although the cognitive processes were interdependent, they could develop at different rates until mastery of a topic was achieved. It also found that the introduction of a technological artefact into the learning environment introduced another layer of complexity, both in terms of the learning process and the underlying relationship between the four cognitive processes.

Person-oriented and process-oriented teachers : an investigation of the links between ESOL teachers' personal belief systems and approaches to teaching

This thesis looks to two traditions in research into language teaching, teacher beliefs and classroom interaction, in order to investigate the question: Do teachers of ESOL have an identifiable and coherent system of beliefs about teaching and learning that may account for different approaches to teaching? A qualitative approach to research is taken, following a case study tradition, in order to carry out an in-depth study into the beliefs of six ESOL teachers. Five teachers participated in an initial pilot study and two subsequently became the main case studies for the research. The beliefs of a sixth teacher were then investigated to verify the findings. Semi-structured interviews and classroom observations were carried out with all the teachers. The teachers in the study were found to have personal belief systems that cohere around two orientations to teaching and learning - a person orientation and a process orientation. Moreover, the findings suggest that underlying the orientations is the perception that teachers have of their teacher identity, in terms of whether this is seen as a separate identity or as part of their personality. It is suggested that the two orientations may offer a powerful tool for teacher education as it is increasingly recognised that, in order to be effective, teacher educators must take into account the beliefs that teachers bring with them to training and development programmes. An initial investigations into the teachers’ classroom behaviour suggests that while their methodologies approach may be very similar there are fundamental differences in their interactions patterns and these differences may be a result of their own orientation. However, while teachers’ personal belief systems undoubtedly underlie their approach to teaching, further research is needed to establish the extent and the nature of the relationship between orientation and classroom interaction.

Trainer talk:structures of interaction in teacher training classrooms

The subject of this research is interaction and language use in an institutional context, the teacher training classroom. Trainer talk is an interactional accomplishment and the research question is: what structures of talk-in-interaction characterise trainer talk in this institutional setting? While there has been research into other kinds of classroom and into other kinds of institutional talk, this study is the first on trainer discourse. The study takes a Conversation Analysis approach to studying institutional interaction and aims to identify the main structures of sequential organization that characterize teacher trainer talk as well as the tasks and identities that are accomplished in it. The research identifies three main interactional contexts in which trainer talk is done: expository, exploratory and experiential. It describes the main characteristics of each and how they relate to each other. Expository sequences are the predominant interactional contexts for trainer talk. But the research findings show that these contexts are flexible and open to the embedding of the other two contexts. All three contexts contribute to the main institutional goal of teaching teachers how to teach. Trainer identity is related to the different sequential contexts. Three main forms of identity in interaction are evidenced in the interactional contexts: the trainer as trainer, the trainer as teacher and the trainer as colleague. Each of them play an important role in teacher trainer pedagogy. The main features of trainer talk as a form of institutional talk are characterised by the following interactional properties: 1. Professional discourse is both the vehicle and object of instruction - the articulation of reflection on experience. 2. There is a reflexive relationship between pedagogy and interaction. 3. The professional discourse that is produced by trainees is not evaluated by trainers but, rather, reformulated to give it relevant precision in terms of accuracy and appropriacy.