Evaluating Students in Translating Courses - Prospects and Pitfalls

Our chapter aims to discuss and analyse various evaluation and assessment methods used in evaluating both individual translation assignments and students’ overall course performances in higher education translator training. It would appear that evaluation methods often fall into the sphere of ‘tacit knowledge’, i.e. teachers develop and apply their own evaluation tools, but these are seldom actively or publicly shared. We start by briefly discussing the impact of assessment on student learning in general, and in particular as related to translation competences. We discuss different approaches to evaluating assignments, for example grading vs not grading; forms of teacher feedback; self-evaluation and peer evaluation. In regard to assessing course performance, we discuss methods such as continuous assessment; end-of-course exams; and various combinations thereof. Throughout the paper, we include a student perspective on evaluation by citing student feedback. We conclude that while different methods can be successfully applied at various stages of translator training, all evaluation should be designed along the lines of constructive alignment.Peer reviewe

Regulation of excitation-contraction coupling in mouse cardiac myocytes: integrative analysis with mathematical modelling

<p>Abstract</p> <p>Background</p> <p>The cardiomyocyte is a prime example of inherently complex biological system with inter- and cross-connected feedback loops in signalling, forming the basic properties of intracellular homeostasis. Functional properties of cells and tissues have been studied e.g. with powerful tools of genetic engineering, combined with extensive experimentation. While this approach provides accurate information about the physiology at the endpoint, complementary methods, such as mathematical modelling, can provide more detailed information about the processes that have lead to the endpoint phenotype.</p> <p>Results</p> <p>In order to gain novel mechanistic information of the excitation-contraction coupling in normal myocytes and to analyze sophisticated genetically engineered heart models, we have built a mathematical model of a mouse ventricular myocyte. In addition to the fundamental components of membrane excitation, calcium signalling and contraction, our integrated model includes the calcium-calmodulin-dependent enzyme cascade and the regulation it imposes on the proteins involved in excitation-contraction coupling. With the model, we investigate the effects of three genetic modifications that interfere with calcium signalling: 1) ablation of phospholamban, 2) disruption of the regulation of L-type calcium channels by calcium-calmodulin-dependent kinase II (CaMK) and 3) overexpression of CaMK. We show that the key features of the experimental phenotypes involve physiological compensatory and autoregulatory mechanisms that bring the system to a state closer to the original wild-type phenotype in all transgenic models. A drastic phenotype was found when the genetic modification disrupts the regulatory signalling system itself, i.e. the CaMK overexpression model.</p> <p>Conclusion</p> <p>The novel features of the presented cardiomyocyte model enable accurate description of excitation-contraction coupling. The model is thus an applicable tool for further studies of both normal and defective cellular physiology. We propose that integrative modelling as in the present work is a valuable complement to experiments in understanding the causality within complex biological systems such as cardiac myocytes.</p

A Novel Estimator for the Rate of Information Transfer by Continuous Signals

The information transfer rate provides an objective and rigorous way to quantify how much information is being transmitted through a communications channel whose input and output consist of time-varying signals. However, current estimators of information content in continuous signals are typically based on assumptions about the system's linearity and signal statistics, or they require prohibitive amounts of data. Here we present a novel information rate estimator without these limitations that is also optimized for computational efficiency. We validate the method with a simulated Gaussian information channel and demonstrate its performance with two example applications. Information transfer between the input and output signals of a nonlinear system is analyzed using a sensory receptor neuron as the model system. Then, a climate data set is analyzed to demonstrate that the method can be applied to a system based on two outputs generated by interrelated random processes. These analyses also demonstrate that the new method offers consistent performance in situations where classical methods fail. In addition to these examples, the method is applicable to a wide range of continuous time series commonly observed in the natural sciences, economics and engineering

Information and Discriminability as Measures of Reliability of Sensory Coding

Response variability is a fundamental issue in neural coding because it limits all information processing. The reliability of neuronal coding is quantified by various approaches in different studies. In most cases it is largely unclear to what extent the conclusions depend on the applied reliability measure, making a comparison across studies almost impossible. We demonstrate that different reliability measures can lead to very different conclusions even if applied to the same set of data: in particular, we applied information theoretical measures (Shannon information capacity and Kullback-Leibler divergence) as well as a discrimination measure derived from signal-detection theory to the responses of blowfly photoreceptors which represent a well established model system for sensory information processing. We stimulated the photoreceptors with white noise modulated light intensity fluctuations of different contrasts. Surprisingly, the signal-detection approach leads to a safe discrimination of the photoreceptor response even when the response signal-to-noise ratio (SNR) is well below unity whereas Shannon information capacity and also Kullback-Leibler divergence indicate a very low performance. Applying different measures, can, therefore, lead to very different interpretations concerning the system's coding performance. As a consequence of the lower sensitivity compared to the signal-detection approach, the information theoretical measures overestimate internal noise sources and underestimate the importance of photon shot noise. We stress that none of the used measures and, most likely no other measure alone, allows for an unbiased estimation of a neuron's coding properties. Therefore the applied measure needs to be selected with respect to the scientific question and the analyzed neuron's functional context

The role of ocelli in cockroach optomotor performance

Insect ocelli are relatively simple eyes that have been assigned various functions not related to pictorial vision. In some species they function as sensors of ambient light intensity, from which information is relayed to various parts of the nervous system, e.g., for the control of circadian rhythms. In this work we have investigated the possibility that the ocellar light stimulation changes the properties of the optomotor performance of the cockroach Periplaneta americana. We used a virtual reality environment where a panoramic moving image is presented to the cockroach while its movements are recorded with a trackball. Previously we have shown that the optomotor reaction of the cockroach persists down to the intensity of moonless night sky, equivalent to less than 0.1 photons/s being absorbed by each compound eye photoreceptor. By occluding the compound eyes, the ocelli, or both, we show that the ocellar stimulation can change the intensity dependence of the optomotor reaction, indicating involvement of the ocellar visual system in the information processing of movement. We also measured the cuticular transmission, which, although relatively large, is unlikely to contribute profoundly to ocellar function, but may be significant in determining the mean activity level of completely blinded cockroaches

Role of the Na(+)-Ca(2+) exchanger as an alternative trigger of CICR in mammalian cardiac myocytes.

Ca(2+) influx through the L-type Ca(2+) channels is the primary pathway for triggering the Ca(2+) release from the sarcoplasmic reticulum (SR). However, several observations have shown that Ca(2+) influx via the reverse mode of the Na(+)-Ca(2+) exchanger current (I(Na-Ca)) could also trigger the Ca(2+) release. The aim of the present study was to quantitate the role of this alternative pathway of Ca(2+) influx using a mathematical model. In our model 20% of the fast sodium channels and the Na(+)-Ca(2+) exchanger molecules are located in the restricted subspace between the sarcolemma and the SR where triggering of the calcium-induced calcium release (CICR) takes place. After determining the strengths of the alternative triggers with simulated voltage-clamps in varied membrane voltages and resting [Na](i) values, we studied the CICR in simulated action potentials, where fast sodium channel current contributes [Na](i) of the subspace. In low initial [Na](i) the Ca(2+) influx via the L-type Ca(2+) channels is the major trigger for Ca(2+) release from the SR, and the Ca(2+) influx via the reverse mode of the Na(+)-Ca(2+) exchanger cannot trigger the CICR. However, depending on the initial [Na](i), the contribution of the Ca(2+) entry via the exchanger may account for 25% (at [Na](i) = 10 mM) to nearly 100% ([Na](i) = 30 mM) of the trigger Ca(2+). The shift of the main trigger from L-type calcium channels to the exchanger reduced the delay between the action potential upstroke and the intracellular calcium transient. This may contribute to the function of the myocyte in physiological situations where [Na](i) is elevated. These main results remain the same when using different estimates for the most crucial parameters in the modeling or different models for the exchanger

TOWARDS NATURAL INSECT VISION RESEARCH REPORT SERIES IN PHYSICAL SCIENCES TOWARDS NATURAL INSECT VISION RESEARCH

Abstract Visual world is naturally correlated both spatially and temporally. The correlations are used in vision to enhance performance of neurons. For gaining maximal neural performance of the visual neurons, the experiments, from stimulus to the analysis, should be designed to take advantage of the correlations. In this thesis methods for generating and analyzing natural stimuli were examined by using computations and algorithms. For analyzing responses to natural stimuli in visual neurons, a method with only a few assumptions was developed for estimating information rate in long responses. The novel method gave a good agreement with Shannon information rate with linear system and Gaussian input but was able to handle also nonlinear processing and non-Gaussian data. Secondly, a computer controlled 3D virtual environment with a spherical screen was developed, with a large visual field. The image of the world was projected to the screen with a DLP projector, giving good enough temporal performance for insect vision research. A track-ball was used in closed loop experiments. Thirdly, properties of single photon (&quot;bump&quot;) information transfer at various light levels were investigated in cockroach photoreceptor with a coarse computational model. At dim light (&lt; 10 ph/s), where single bump responses were visible, shot noise was dominant. At higher light levels latency distribution of the bump decreased the information rate, but amplitude distribution of bump did not have an effect. Fourthly, the contribution of K + channels to information rate and energy consumption was investigated by creating a database of computation models with varying channel compositions. The information rate has a maximum as a function of mean conductance, which was a sum of the average K + conductance and the leak conductance. This maximum was fine-tuned by the K + channel composition, which had high so-called novel contribution and relatively low amount of other conductances