Reproducing successful rituals in bad times : exploring interactions of a new science teacher

Teaching is emotional work. This is especially the case in the first years of teaching when new teachers are particularly vulnerable. By understanding changes in teacher emotions in the early years of teaching we hope to identify strategies that might ultimately reduce teacher attrition. As part of a larger study of the transition of new teachers to the profession, this ethnographic case study explores how a new science teacher produced and reproduced positive emotional interaction rituals with her students in her first year of teaching. We show how dialogical interactions were positive and satisfying experiences for the teacher, and how they were reproduced successfully in different contexts. We also illustrate how both teacher and students used humor to create a structure for dialogical interactions. During these successful interactions the students used shared resources to satisfy their teacher that they were engaging in the relevant science content. The implications of what we have learned for the professional development of new teachers are discussed in relation to an expanded understanding of teacher emotions.

Learning the kernel matrix with semidefinite programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

A unifying view of multiple kernel learning

Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion’s dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments.

A unifying view of multiple kernel learning

Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying general optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion's dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

The undirected feedback vertex set problem has a Poly(k) Kernel

Resolving a noted open problem, we show that the Undirected Feedback Vertex Set problem, parameterized by the size of the solution set of vertices, is in the parameterized complexity class Poly(k), that is, polynomial-time pre-processing is sufficient to reduce an initial problem instance (G, k) to a decision-equivalent simplified instance (G', k') where k' � k, and the number of vertices of G' is bounded by a polynomial function of k. Our main result shows an O(k11) kernelization bound.

A sequence analytic model of entrepreneurial discovery and exploitation process

This study examined the effect that temporal order within the entrepreneurial discovery exploitation process has on the outcomes of venture creation. Consistent with sequential theories of discovery-exploitation, the general flow of venture creation was found to be directed from discovery toward exploitation in a random sample of nascent ventures. However, venture creation attempts which specifically follow this sequence derive poor outcomes. Moreover, simultaneous discovery-exploitation was the most prevalent temporal order observed, and venture attempts that proceed in this manner more likely become operational. These findings suggest that venture creation is a multi-scale phenomenon that is at once directional in time, and simultaneously driven by symbiotically coupled discovery and exploitation.

Sensitivity of the NMR density matrix to pulse sequence parameters : a simplified analytic approach

We present a formalism for the analysis of sensitivity of nuclear magnetic resonance pulse sequences to variations of pulse sequence parameters, such as radiofrequency pulses, gradient pulses or evolution delays. The formalism enables the calculation of compact, analytic expressions for the derivatives of the density matrix and the observed signal with respect to the parameters varied. The analysis is based on two constructs computed in the course of modified density-matrix simulations: the error interrogation operators and error commutators. The approach presented is consequently named the Error Commutator Formalism (ECF). It is used to evaluate the sensitivity of the density matrix to parameter variation based on the simulations carried out for the ideal parameters, obviating the need for finite-difference calculations of signal errors. The ECF analysis therefore carries a computational cost comparable to a single density-matrix or product-operator simulation. Its application is illustrated using a number of examples from basic NMR spectroscopy. We show that the strength of the ECF is its ability to provide analytic insights into the propagation of errors through pulse sequences and the behaviour of signal errors under phase cycling. Furthermore, the approach is algorithmic and easily amenable to implementation in the form of a programming code. It is envisaged that it could be incorporated into standard NMR product-operator simulation packages.

A new analytic approach for power system fault diagnosis employing the temporal information of alarm messages

Traditional analytic models for power system fault diagnosis are usually formulated as an unconstrained 0–1 integer programming problem. The key issue of the models is to seek the fault hypothesis that minimizes the discrepancy between the actual and the expected states of the concerned protective relays and circuit breakers. The temporal information of alarm messages has not been well utilized in these methods, and as a result, the diagnosis results may be not unique and hence indefinite, especially when complicated and multiple faults occur. In order to solve this problem, this paper presents a novel analytic model employing the temporal information of alarm messages along with the concept of related path. The temporal relationship among the actions of protective relays and circuit breakers, and the different protection configurations in a modern power system can be reasonably represented by the developed model, and therefore, the diagnosed results will be more definite under different circumstances of faults. Finally, an actual power system fault was served to verify the proposed method.

Finding your research voice : the application of bibliometrics as an analytic literature tool on the pedagogic field of higher education

This paper documents the use of bibliometrics as a methodology to bring forth a structured, systematic and rigorous way to analyse and evaluate a range of literature. When starting out and reading broadly for my doctoral studies, one article by Trigwell and Prosser (1996b) led me to reflect about my level of comprehension as the content, concepts and methodology did not resonate with my epistemology. A disconnection between our paradigms emerged. Further reading unveiled the work by Doyle (1987) who categorised research in teaching and teacher education by three main areas: teacher characteristics, methods research and teacher behaviour. My growing concerns that there were gaps in the knowledge also exposed the difficulties in documenting said gaps. As an early researcher who required support to locate myself in the field and to find my research voice, I identified bibliometrics (Budd, 1988; Yeoh & Kaur, 2007) as an appropriate methodology to add value and rigour in three ways. Firstly, the application of bibliometrics to analyse articles is systematic, builds a picture from the characteristics of the literature, and offers a way to elicit themes within the categories. Secondly, by systematic analysis there is occasion to identify gaps within the body of work, limitations in methodology or areas in need of further research. Finally, extension and adaptation of the bibliometrics methodology, beyond citation or content analysis, to investigate the merit of methodology, participants and instruments as a determinant for research worth allowed the researcher to build confidence and contribute new knowledge to the field. Therefore, this paper frames research in the pedagogic field of Higher Education through teacher characteristics, methods research and teacher behaviour, visually represents the literature analysis and locates my research self within methods research. Through my research voice I will present the bibliometrics methodology, the outcomes and document the landscape of pedagogy in the field of Higher Education.

Talking it through : the case for the use of conversation analytic approaches in the analysis of news journalism

This study makes out the case for the use of the Conversational Analytic method as a research approach that might both extricate and chronicle the features of the journalism interview. It seeks to encourage such research to help inform understanding of this form and to provide further lessons as to the nature of journalism practice. Such studies might follow many paths but this paper focuses more particularly on the outcomes for the debate as to the continued relevance of "objectivity" in informing journalism professional practice. To make out the case for the veracity of CA as a means through which the conduct of journalism practice might be explored the paper examines: the theories of the interaction order that gave rise to the CA method; outlines the key features of the journalism interview as explicated through the CA approach; outlines the implications of such research for the establishment of the standing of "objectivity". It concludes as to the wider relevance of such studies of journalism practice for a fracturing journalism field, which suffers from a lack of benchmarks to measure the public benefit of the range of forms that now proliferate on the internet.

Depression among Holocaust survivors : a meta-analytic review

The publication of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) introduced the notion that a life-threatening illness can be a stressor and catalyst for Posttraumatic Stress Disorder (PTSD). Since then a solid body of research has been established investigating the post-diagnosis experience of cancer. These studies have identified a number of short and long-term life changes resulting from a diagnosis of cancer and associated treatments. In this chapter, we discuss the psychosocial response to the cancer experience and the potential for cancer-related distress. Cancer can represent a life-threatening diagnosis that may be associated with aggressive treatments and result in physical and psychological changes. The potential for future trauma through the lasting effects of the disease and treatment, and the possibility of recurrence, can be a source of continued psychological distress. In addition to the documented adverse repercussions of cancer, we also outline the recent shift that has occurred in the psycho-oncology literature regarding positive life change or posttraumatic growth that is commonly reported after a diagnosis of cancer. Adopting a salutogenic framework acknowledges that the cancer experience is a dynamic psychosocial process with both negative and positive repercussions. Next, we describe the situational and individual factors that are associated with posttraumatic growth and the types of positive life change that are prevalent in this context. Finally, we discuss the implications of this research in a therapeutic context and the directions of future posttraumatic growth research with cancer survivors. This chapter will present both quantitative and qualitative research that indicates the potential for personal growth from adversity rather than just mere survival and return to pre-diagnosis functioning. It is important to emphasise however, that the presence of growth and prevalence of resilience does not negate the extremely distressing nature of a cancer diagnosis for the patient and their families and the suffering that can accompany treatment regimes. Indeed, it will be explained that for growth to occur, the experience must be one that quite literally shatters previously held schemas in order to act as a catalyst for change.

Lay theories of anorexia nervosa : a discourse analytic study

Previous studies on lay theories of anorexia nervosa have examined the 'accuracy' of lay knowledge, and the identification of factors by family and friends that would encourage early interventions. In contrast to these approaches, we examine lay theories of anorexia nervosa using a critical psychology perspective. We argue that the use of a discourse analysis methodology enables the examination of the construction of lay theories through dominant concepts and ideas. Ten semi-structured interviews with five women and five men aged between 15 and 25 years were carried out. Participants were asked questions about three main aspects of anorexia nervosa: aetiology, treatment and relationship to gender. Each interview was analysed in terms of the structure, function and variability of discourse. Three discourses: sociocultural, individual and femininity, are discussed in relation to the interview questions. We conclude that, in this study, lay theories of anorexia nervosa were structured through key discourses that maintained a separation between sociocultural aspects of anorexia nervosa and individual psychology. This separation exists in dominant psychomedical conceptualizations of anorexia nervosa, reinforcing the concept that it is a form of psychopathology.

Understanding body image disturbance in the promotion of mental health : a discourse analytic study

Health care interventions in the area of body image disturbance and eating disorders largely involve individual treatment approaches, while prevention and health promotion are relatively underexplored. A review of health promotion activities in the area of body image in Australia revealed three programmes, the most extensive and longest standing having been established in 1992. The aims of this programme are to reduce body image dissatisfaction and inappropriate eating behaviour, especially among women. Because health promotion is concerned with the social aspects of health, it was hypothesized by the authors that a social understanding of body image and eating disorders might be advanced in a health promotion setting and reflected in the approach to practice. In order to examine approaches to body image in health promotion, 10 health professionals responsible for the design and management of this programme participated in a series of semi-structured interviews between 1997 and 2000. Three discursive themes were evident in health workers' explanations of body image problems: (1) cognitive-behavioural themes; (2) gender themes; and (3) socio-cultural themes. While body image problems were constructed as psychological problems that are particularly experienced by women, their origins were largely conceived to be socio-cultural. The implications of these constructions are critically discussed in terms of the approach to health promotion used in this programme.