Supporting the first year student experience through the use of learning technologies

This guide is based on discussion and contributions by the E-learning and the First Year Student Experience (ELFYSE) special interest group (SIG). ELFYSE SIG was supported by Middlesex University and the Higher Education Academy in 2009-10. It has provided a focus for practitioners involved in further and higher education as well as those who are interested in how learning technologies can support the first-year experience and the challenges which face institutions and students. Specifically, these are: transition, retention and progression. This guide will be of interest to both academic and support staff who contribute to the first year experience for students: e-learning managers, learning technologists, widening participation managers, induction leaders, student achievement advisors and those implementing enhancement initiatives for the student experience. Bringing together the areas of e-learning and student transition, retention and progression, this guide draws on both theory and practice to provide recommendations for and guidance to both academic and support staff on using learning technologies to support the first-year student experience. It is designed to help you think about ways of approaching and incorporating the use of learning technologies to support and enhance your students' first-year experience

Final report to the Higher Education Academy. managing connections: using e-learning tracking information to improve retention rates in higher education

The Final Report provides an outline of the research design, the findings and the recommendations which arose from the ‘Managing Connections: using e-learning tracking information to improve retention rates in higher education’ project, which was funded by the Higher Education Academy and Middlesex University between 2007 and 2008

An exploration of perceptions of learning and e-learning held by students who withdraw and those who persist with UK higher education

This paper discusses the relationships that first-year students have with learning and with technology. Due to the lack of previous work linking e-learning with student retention, differences between ‘withdrawers’ and ‘persisters’ were explored. Data were collected using interviews and questionnaires and analysed using thematic analysis. Evidence of a deficit approach to e-learning appears to manifest itself in both groups and technologies that promote social interaction were primarily reserved for personal use rather than within an institutional context. Recommendations from this research include the need to learn how technologies promoting social interaction are used and incorporate lessons learnt into the design of e-learning experiences

Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular\ud electrophysiology

Cellular and ionic causes of variability in the electrophysiological activity of hearts from individuals of the same species are unknown. However, improved understanding of this variability is key to enable prediction of the response of specific hearts to disease and therapies. Limitations of current mathematical modeling and experimental techniques hamper our ability to provide insight into variability. Here we describe a methodology to unravel the ionic determinants of inter-subject variability exhibited in experimental recordings, based on the construction and calibration of populations of models. We illustrate the methodology through its application to rabbit Purkinje preparations, due to their importance in arrhythmias and safety pharmacology assessment. We consider a set of equations describing the biophysical processes underlying rabbit Purkinje electrophysiology and we construct a population of over 10,000 models by randomly assigning specific parameter values corresponding to ionic current conductances and kinetics. We calibrate the model population by closely comparing simulation output and experimental recordings at three pacing frequencies. We show that 213 of the 10,000 candidate models are fully consistent with the experimental dataset. Ionic properties in the 213 models cover a wide range of values, including differences up to ±100% in several conductances. Partial correlation analysis shows that particular combinations of ionic properties determine the precise shape, amplitude and rate dependence of specific action potentials. Finally, we demonstrate that the population of models calibrated using data obtained under physiological conditions quantitatively predicts the action potential duration prolongation caused by exposure to four concentrations of the potassium channel blocker dofetilide

Low loss Ge-on-Si waveguides operating in the 8–14 µm atmospheric transmission window

Germanium-on-silicon waveguides were modeled, fabricated and characterized at wavelengths ranging from 7.5 to 11 µm. Measured waveguide losses are below 5 dB/cm for both TE and TM polarization and reach values of ∼ 1 dB/cm for ≥ 10 µm wavelengths for the TE polarization. This work demonstrates experimentally for the first time that Ge-on-Si is a viable waveguide platform for sensing in the molecular fingerprint spectral region. Detailed modeling and analysis is presented to identify the various loss contributions, showing that with practical techniques losses below 1 dB/cm could be achieved across the full measurement range

Ohmic contacts to n-type germanium with low specific contact resistivity

A low temperature nickel process has been developed that produces Ohmic contacts to n-type germanium with specific contact resistivities down to (2.3 ± 1.8) x10<sup>-7</sup> Ω-cm<sup>2</sup> for anneal temperatures of 340 degC. The low contact resistivity is attributed to the low resistivity NiGe phase which was identified using electron diffraction in a transmission electron microscope. Electrical results indicate that the linear Ohmic behaviour of the contact is attributed to quantum mechanical tunnelling through the Schottky barrier formed between the NiGe alloy and the heavily doped n-Ge.<p></p&gt

Mid-infrared intersubband absorption from p-Ge quantum wells grown on Si substrates

Mid-infrared intersubband absorption from p-Ge quantum wells with Si0.5Ge0.5 barriers grown on a Si substrate is demonstrated from 6 to 9 μm wavelength at room temperature and can be tuned by adjusting the quantum well thickness. Fourier transform infra-red transmission and photoluminescence measurements demonstrate clear absorption peaks corresponding to intersubband transitions among confined hole states. The work indicates an approach that will allow quantum well intersubband photodetectors to be realized on Si substrates in the important atmospheric transmission window of 8–13 μm

Extrapolating parametric survival models in health technology assessment : a simulation study

Extrapolations of parametric survival models fitted to censored data are routinely used in the assessment of health technologies to estimate mean survival, particularly in diseases that potentially reduce the life expectancy of patients. Akaike’s information criterion (AIC) and Bayesian information criterion (BIC) are commonly used in health technology assessment alongside an assessment of plausibility to determine which statistical model best fits the data and should be used for prediction of long-term treatment effects. We compare fit and estimates of restricted mean survival time (RMST) from 8 parametric models and contrast models preferred in terms of AIC, BIC, and log-likelihood, without considering model plausibility. We assess the methods’ suitability for selecting a parametric model through simulation of data replicating the follow-up of intervention arms for various time-to-event outcomes from 4 clinical trials. Follow-up was replicated through the consideration of recruitment duration and minimum and maximum follow-up times. Ten thousand simulations of each scenario were performed. We demonstrate that the different methods can result in disagreement over the best model and that it is inappropriate to base model selection solely on goodness-of-fit statistics without consideration of hazard behavior and plausibility of extrapolations. We show that typical trial follow-up can be unsuitable for extrapolation, resulting in unreliable estimation of multiple parameter models, and infer that selecting survival models based only on goodness-of-fit statistics is unsuitable due to the high level of uncertainty in a cost-effectiveness analysis. This article demonstrates the potential problems of overreliance on goodness-of-fit statistics when selecting a model for extrapolation. When follow-up is more mature, BIC appears superior to the other selection methods, selecting models with the most accurate and least biased estimates of RMST

Mid-Infrared Intersubband Absorption from P-Ge Quantum Wells on Si

Mid-infrared intersubband absorption from p-Ge quantum wells with Si0.5Ge0.5 barriers grown on a Si substrate is demonstrated from 6 to 9 μm wavelength at room temperature and can be tuned by adjusting the quantum well thickness. Fourier transform infra-red spectroscopy measurements demonstrate clear absorption peaks corresponding to intersubband transitions among confined hole states. The work indicates an approach that will allow quantum well intersubband photodetectors to be realized on Si substrates in the important atmospheric transmission window of 8–13 μm

FE and skills across the four countries of the UK: new opportunities for policy learning

This report showcases research across England, Scotland, Wales and Northern Ireland concerning national specificities and shared problems and challenges. It concludes that in the area of further education and skills there is greater opportunities for policy learning involving these countries than in general education in which there are deep divisions between the three smaller countries and England