Cutting edge: Science hackathons for developing interdisciplinary research and collaborations

Science hackathons can help academics, particularly those in the early stage of their careers, to build collaborations and write research proposals.This work was funded by the UK Engineering and Physical Sciences Research Council under grant numbers EP/I017909/1 (www.2020science.net), and by the Department of Mathematics at Imperial College London under the EPSRC Mathematics Platform grant EP/I019111/1

Estimating Bayes factors via thermodynamic integration and population MCMC

A Bayesian approach to model comparison based on the integrated or marginal likelihood is considered, and applications to linear regression models and nonlinear ordinary differential equation (ODE) models are used as the setting in which to elucidate and further develop existing statistical methodology. The focus is on two methods of marginal likelihood estimation. First, a statistical failure of the widely employed Posterior Harmonic Mean estimator is highlighted. It is demonstrated that there is a systematic bias capable of significantly skewing Bayes factor estimates, which has not previously been highlighted in the literature. Second, a detailed study of the recently proposed Thermodynamic Integral estimator is presented, which characterises the error associated with its discrete form. An experimental study using analytically tractable linear regression models highlights substantial differences with recently published results regarding optimal discretisation. Finally, with the insights gained, it is demonstrated how Population MCMC and thermodynamic integration methods may be elegantly combined to estimate Bayes factors accurately enough to discriminate between nonlinear models based on systems of ODEs, which has important application in describing the behaviour of complex processes arising in a wide variety of research areas, such as Systems Biology, Computational Ecology and Chemical Engineering. (C) 2009 Elsevier B.V. All rights reserve

Computational inference in systems biology

Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem. The computational costs associated with repeatedly solving the ODEs are often high. Aimed at reducing this cost, new concepts using gradient matching have been proposed. This paper combines current adaptive gradient matching approaches, using Gaussian processes, with a parallel tempering scheme, and conducts a comparative evaluation with current methods used for parameter inference in ODEs

Reflective Journaling: A Theoretical Model and Digital Prototype for Developing Resilience and Creativity

Reflection is commonly discussed as a tool for personal and professional development that is becoming increasingly important in today’s global and digital world. In this paper, we propose a model that suggests ways in which reflection, in the form of Reflective Journaling, can support the development of creativity and resilience, which are needed to enable individuals to function effectively in a fast-changing environment. In addition, the model proposes ways in which external support and progress monitoring can be used in conjunction with skills in adaptive resilience and structured creativity, to support the maintenance of reflective journaling as a habit, in the longer term, thus creating virtuous cycles of skills and behaviours that can reinforce each other. Based on our model, and additional user research, we describe the design of a first digital prototype that aims to support the use of Reflective Journaling and to develop creativity and resilience through suggested mechanisms. Initial evaluations of our prototype are positive. It has been well-received by early test users, and has the potential to address all the connections defined. We therefore suggest that the theoretical model can be used to develop digital tools, such as the one included, to help those who wish to develop the habit of reflective journaling, and through that a range of other skills associated with resilience and creative thinking. We see this as a starting point for investigating this potential in more depth

Statistical analysis of modal gating in ion channels

Ion channels regulate the concentrations of ions within cells. By stochastically opening and closing its pore, they enable or prevent ions from crossing the cell membrane. However, rather than opening with a constant probability, many ion channels switch between several different levels of activity even if the experimental conditions are unchanged. This phenomenon is known as modal gating: instead of directly adapting its activity, the channel seems to mix sojourns in active and inactive modes in order to exhibit intermediate open probabilities. Evidence is accumulating that modal gating rather than modulation of opening and closing at a faster time scale is the primary regulatory mechanism of ion channels. However, currently, no method is available for reliably calculating sojourns in different modes. In order to address this challenge, we develop a statistical framework for segmenting single-channel datasets into segments that are characteristic for particular modes. The algorithm finds the number of mode changes, detects their locations and infers the open probabilities of the modes. We apply our approach to data from the inositol-trisphosphate receptor. Based upon these results, we propose that mode changes originate from alternative conformational states of the channel protein that determine a certain level of channel activity

The initial education of high school teachers : a critical review of major issues and trends

This paper draws on major research findings in international literature in order to provide a critical review of a number of key issues and trends in the initial education of high school teachers. Firstly, this paper contextualizes the prevalent discourse surrounding the field of initial teacher education (ITE) and explores the effect that this discourse has on the conceptualization of teachers’ work. Secondly, this paper focuses on the debates regarding the most propitious site for the teacher education enterprise, the programme structure for ITE, the field placement or practicum, the relationship between subject study and pedagogy, and the overall effectiveness of teacher education. The paper concludes by considering the new challenges that the field of initial teacher education must confront and the implications of such challenges for the ITE curriculum.peer-reviewe

Investigation of chemistry graduate teaching assistants’ teacher knowledge and teacher identity

Graduate students play an integral role in undergraduate chemistry education at doctoral granting institutions where they routinely serve as instructors of laboratories and supplementary discussion sessions. Simultaneously, graduate teaching assistants (GTAs) balance major research and academic responsibilities. Although GTAs have substantial instructional facetime with large numbers of undergraduate students, little is known about their conceptions of teaching or their identities as teachers. To investigate the knowledge that GTAs have regarding teaching in this unique context, their teaching identities, and how these developed, we conducted 22 interviews with graduate students from several universities at various levels in their graduate school career using a modified Teacher Beliefs Interview. Interviews were analyzed for two overarching teacher learning constructs: teacher knowledge and teacher identity. We characterized chemistry GTAs’ teacher knowledge and identity and determined major influencing factors. We found that chemistry GTAs often identified as a tutor or lab manager, which hindered their self‐investment in developing as teachers. The results presented herein contribute to an understanding of GTAs’ teacher knowledge, teacher identity, and their teaching context, from which training can be designed to best support GTA development.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155950/1/tea21618_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155950/2/tea21618.pd