Helping to keep history relevant : mulitmedia and authentic learning

The subject based curriculum attracts lively debate in many countries being accused of fragmenting teaching and learning, erecting artificial barriers and failing to teach the skills required in the twenty first century (Hazlewood 2005). Cross-curricular rich tasks are increasingly seen as the means to develop relevant knowledge, understanding and skills. Over the past fourteen years we have developed and evaluated a series of interactive multi-media resources for primary and secondary schools on themes within Scottish History. The generally positive evaluation given to these resources by pupils and teachers points to some ways in which subjects such as history can remain challenging and relevant. The relevance has largely stemmed, in the case of the multi-media resources, from combining the historian's traditional role of problemising the past, with a wide range of primary and secondary sources, new technologies and learning tasks encompassing critical skills/authentic learning. Consequently, we argue that subjects must in future embrace new technologies and authentic learning to maintain their place in the school curriculum

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

Teachers' classroom decision-making : its relationship to teachers' perceptions of pupils and to classroom interaction

The relevance of decision-making to classroom teaching and to questions concerning teacher effectivenesst teacher training and curricular innovation has been noted by several researchers. However, teachers' classroom decision-making has frequently been conceptualised as a stage-wise, problem-solving task, involving the evaluation of alternative courses of action, and this would appear to be incompatible with the severe time restrictions experienced by teachers in real classrooms. Exploratory studies, investigating classroom interaction and teachers' and pupils' perceptions of it, involving observation, structured interview, repertory grid and rating methods, simulation, stimulated recall and sociometric methods, suggested in fact, that rather than making decisions, teachers tended to respond spontaneouslyt in a seemingly rule-governed manner, to configurations of cues in which pupil attributes ranked high in importance. A model of teachers' classroom decision-making was derived from the exploratory studies and previous researcht and it was suggested that the difficulties encountered by beginning teachers in making classroom decisions could be accounted for in terms of their lack of a cognitive framework of rules for action and their appropriate pupil distinctions. A main study involving six first-year probationer teachers and six experienced teachers was carried out to examine seven hypotheses concerning the inter-relationships of teachers' assessments of their pupilsp classroom interaction, teachers' reasons for their classroom interaction and pupilso self-perceptions and the difference between experienced teachers and probationers on these variables: hypothesis 1) Experienced teachers assess their pupils more quickly than probationer teachers (i. e. attribute more qualities to more childreng early in the term); 2) Experienced teachers' assessments of their pupils are more stable over time; 3) There are associations between the ways in which teachers perceive their pupils and the ways in which they interact with them; 4) These associations are stronger amongst experienced teachers than probationers; 5) Some of the unequal distribution of teacher-pupil interactions can be accounted for by the reasons which teachers give for their behaviour; 6) The reasonsp given by experienced teachers, which account for their classroom interactions are different from thosel given by probationer teachers, which account for their classroom interactions; 7) There is a relationship between a teacher's assessments of his/her pupils and the pupils' perceptions of themselves and their friendship choices. Hypothesis 7, which was intended to illuminate the extent to which pupils may influence the learning of beginning teachers, was further subdivided into five more specific hypotheses, after the finding that the probationer teachers in the sample were more reactive in their classroom behaviour, whereas experienced teachers tended to be more proactive; hence it was anticipated that probationers' assessments of their pupils would be more influenced by the pupils' assessments of themselves, whereas the experienced teachers may be more effective in communicating their assessments to the pupils and thus influencing their pupils' self-perceptions. Teachers' verbal descriptions of pupils, teachers' ratings of pupilso classroom interaction data, and pupils' self-ratings and sociometric data were collected at the beginnings of both the first and second terms of the school year. In addition, teachers each gave a commentary stimulated by a tape recording of a lesson taken in the second term. It was found that experienced teachers made more attributions concerning their pupils than did probationer teachers, although their ratings of pupils were no more stable between terms. A cluster analysis of teachers' ratings resulted in some common clusters which tended to engage in characteristic patterns of interaction, but the differences in interaction amongst clusters were not statistically significant. Teachers who had given particular reasons for their behaviour, which differentiated amongst pupils were found to be better represented amongst groups of teachers associated with particular cluster/interaction patterns. Although the reasons given by experienced teachers differed to some extent from those of probationers, the occurrence of patterns of interaction with particular clusters was neither more common amongst experienced teachers nor more significant. Consequently, analysis of the data indicated some support for hypotheses l, 3, 5, and 6, and although support was found for the hypotheses that probationers are more influenced by pupils' self-perceptions whereas experienced teachers have a stronger influence upon pupils' self-perceptions, it was noted that pupil self-perceptions were not very stable between terms and could have a tendency to 'drift'. possibly drifting in the direction of teachers' assessments where the teacher is proactive, regularly providing cues regarding her assessments of pupils. It also appeared that clusters derived from each teacher's ratings bore little resemblance to the clusters derived from pupils' friendship choices thus bringing into question the popularly conceived notion of teachers influencing pupil friendship groups. In additiong the data analysis revealed several consistent individual differences amongst the teachers, in particular between the probationers and the older teachers in the sample, which could be interpreted within the proposed model of classroom decision-making. In generalv the nature of teachers' classroom decision making which is suggested by the results supports the proposed model, and the issues arising from the study, concerning research methodology, data analysisp possible future research studies and their relevance to practical classroom teaching, and in particular the issue of diagnostic assessments of pupils and their relationship to teaching practice were noted and discussed

Integration of BIM Management into Custom Residential Construction

The custom residential sector of construction currently lacks the usage of BIM management tools. This paper looks to research the current usage, advantages, and disadvantages of using BIM management software’s within custom residential construction. There will be a comparative case study held between two custom residential contractors, one with minor BIM usage and one who has fully integrated BIM software into their management procedure. The goal is to find out if BIM management is cost-effective and scalable to the custom residential industry. This information will be beneficial to the custom residential industry because it will provide custom residential general contractors with information and data about BIM, that can be directly applied to their busines

Differential geometric MCMC methods and applications

This thesis presents novel Markov chain Monte Carlo methodology that exploits the natural representation of a statistical model as a Riemannian manifold. The methods developed provide generalisations of the Metropolis-adjusted Langevin algorithm and the Hybrid Monte Carlo algorithm for Bayesian statistical inference, and resolve many shortcomings of existing Monte Carlo algorithms when sampling from target densities that may be high dimensional and exhibit strong correlation structure. The performance of these Riemannian manifold Markov chain Monte Carlo algorithms is rigorously assessed by performing Bayesian inference on logistic regression models, log-Gaussian Cox point process models, stochastic volatility models, and both parameter and model level inference of dynamical systems described by nonlinear differential equations

A study of Population MCMC for estimating Bayes Factors over nonlinear ODE models

Higher resolution biological data is now becoming available in ever greater quantities, allowing the complex behaviour of fundamental biological processes to be studied in much more detail. The area of Systems Biology is in desperate need of methods for inferring the most likely topology of the underlying genetic networks from this oftentimes noisy and poorly sampled data, to support the construction and testing of new model hypotheses. Towards that end, Bayesian methodology provides an ideal framework for tackling such challenges, and in particular offers a means of objectively comparing competing plausible models through the estimation of Bayes factors. There are, however, formidable obstacles which must be overcome to allow model inference using Bayes factors to be of practical use. Many important biological processes may be most accurately represented using nonlinear models based on systems of ordinary differential equations (ODEs), however parameter inference over these models often produces correspondingly nonlinear posterior distributions, which are very challenging to sample from, often resulting in biased marginal likelihood estimates with large variances. Such problems are commonly encountered when modelling circardian rhythms, which exhibit highly nonlinear oscillatory dynamics and play a central role in the overall functioning of most organisms. In this thesis I investigate tools for calculating Bayes factors to distinguish between ODE-based Goodwin oscillator models of varying complexity, which form the basic building blocks for describing this ubiquitous circadian behaviour. The main result in Chapter 3 of this thesis demonstrates how Population Markov Chain Monte Carlo may be employed in conjunction with thermodynamic integration methods to estimate Bayes factors which may accurately distinguish between two nonlinear oscillator models of varying complexity, given noisy experimental data generated from each of the models. In addition, it is shown how alternative methods may fail drastically in this setting, in particular harmonic mean based estimates. Suggestions are given regarding the optimal temperature schedule which should be employed for Population MCMC, and several ideas for future research extending this work are also discussed

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