1,212 research outputs found

    Researching APEL routes to becoming professionally recognised as a teacher in Higher Education

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    This study examines the experience of 19 academics who received postgraduate credits through an Assessment of Prior Experiential Learning (APEL) process with portfolios as the method of assessment. The purpose of the study was to inform the design of routes to professional recognition based on experience. Actor-Network-Theory (ANT) was used to analyse the data from the study which was in the form of interviews and portfolios. Key to ANT is the process of symmetry. That is, the principle that human and non-human elements of a network should be analysed in the same way. ANT provided an overarching framework for analysing different approaches to APEL whilst remaining true to the individual realities of the process for participants. ANT concepts such as mediators and intermediaries explained the different roles actors (human and material) had in shaping meaning and action in different networks. ANT facilitated an explanation of the role of evidence as both an enabler and barrier to the process of portfolio-building and made visible the resources used by participants in the process. Thus, ANT concepts were fundamental in explaining how the final portfolios came to be. The outcomes of the analysis provided an alternative to experiential learning models (cf Kolb) for facilitating APEL and hereafter the process is referred to as the Recognition of Prior Learning. Three approaches were identified to the translation and transfer of prior learning from practice contexts to academic contexts. These were Articulating, Demonstrating and Authenticating. These approaches represented as a model for Recognising Prior Learning (RPL) had different implications for individual subjectivities and behaviours. Developed into a typology of pedagogic approaches to RPL they provide ways of thinking about RPL design. The argument made throughout the study is that understanding the learner experience of RPL is key to increasing engagement with the process. Examples are provided from the author’s own practice which used the outcomes of this study to inform RPL design in the context of professional recognition and the award of academic credit

    Commuting, transitions and belonging: the experiences of students living at home in their first year at university

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    In this study, our cross-case analysis of students’ lives challenges the conventional home–university model of transition and highlights the importance of acknowledging the influence of this complex symbiotic relationship for students who attend university and live at home. We argue that as with stay-at-home holidays, or “staycations”, which are of such crucial importance to the tourism industry, so stay-at-home students or commuter students are vital to higher education and the term utilised here is “stayeducation”. Through the narratives of “stayeducation” students, we see how family and community aspects of students’ lives are far more significant than previously realised, and our study suggests that these heavily influence the development of a student sense of belonging. Drawing upon biographical narrative method, this paper introduces three first-year Business and Economics students enrolled at different universities in London and explores their journeys through their transition through home, school and early university life. Ways in which key themes play out in the transition stories of our students and the challenges and obstacles for the individual are drawn out through the cross-case analysis. Findings support the existing literature around gender, class and identity; however, new insights into the importance, for these students, of family, friendships and community are presented. Our work has implications for academic staff, those writing institutional policies, and argues for the creation of different spaces within which students can integrate into their new environment

    Recognition of Prior Learning (RPL) as pedagogical pragmatism

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    This case study is located within a joint venture between a University and a College of Further Education, with an explicit mission to bring into Higher Education under-represented groups, including mature learners and to promote part-time education. Our case study provides a review and evaluation of the successful development of an undergraduate programme in leadership and professional development for experienced learners, two-thirds of which is awarded through the Recognition of Prior Learning (RPL). The case study demonstrates how the research-informed RPL design has enabled the recognition of prior learning in a way that is both true to the students’ experience and works within the parameters of quality assurance frameworks. The term used is pedagogical pragmatism i.e. a process that rests on particular combinations of both technical rationality (e.g adherence to a Learning Outcome focused output which is static and a "given") and professional artistry (differential judgements made about the efficacy of approaches to RPL). The practices are contextual, however we would argue that sharing the conditions that underpin RPL as a specialised pedagogic practice is an important part of moving this agenda forward in the sector

    Coagulation of combustion generated nanoparticles and their measurement behind vehicle engines: can they play a role as atmospheric pollutants?

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    International audienceBased on photoionisation mass spectrometry two types of experiments were carried out. (i) In a fast flow reactor coupled to a low pressure flame as a particle source, rate coefficients for the coagulation of primary nanoparticles were measured through variation of the reactor residence time. The results are kc (350K) = 3.5x10-10cm3/s and kc (573K) = 1.1x10-9cm3/s, i.e. very high rate coefficients. It was also shown that coagulated nanoparticles can have masses beyond 50ku, corresponding to equivalent diameters between 4 to 5nm. These particles are easily fragmented during photoionisation. (ii) Using a second and mobile photoionisation mass spectrometer equipped with a fast flow inlet system, measurements were carried out behind three different vehicle engines, a two-stroke scooter engine, a four-stroke motorbike engine and a DI (direct injection) gasoline research engine. In all cases ion signals around 1000u were found that are clearly dependent on engine conditions. In the case of the DI engine, they correlate with the smoke number. These signals cannot be explained by PAHs due to their low volatility at the respective masses. Major contributions of soot or droplet fragmentation were ruled out through additional experiments using a heated inlet line and a filter. Consequently, these signals are interpreted as fragments of coagulated nanoparticles

    New, nearby bright southern ultracool dwarfs

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    We report the discovery of twenty-one hitherto unknown bright southern ultracool dwarfs with spectral types in the range M7 to L5.5, together with new observations of a further three late M dwarfs previously confirmed. Three more objects are already identified in the literature as high proper motion stars;we derive their spectral types for the first time. All objects were selected from the 2MASS All Sky and SuperCOSMOS point source databases on the basis of their optical/near-infrared colours, JJ-band magnitudes and proper motions. Low resolution (R \sim 1000) JHJH spectroscopy with the ESO/NTT SOFI spectrograph has confirmed the ultracool nature of 24 targets, out of a total of 25 candidates observed. Spectral types are derived by direct comparison with template objects and compared to results from H2_2O and FeH indices. We also report the discovery of one binary, as revealed by SOFI acquisition imaging; spectra were taken for both components. The spectral types of the two components are L2 and L4 and the distance \sim 19 pc. Spectroscopic distances and transverse velocities are derived for the sample. Two \sim L5 objects lie only \sim 10 pc distant. Such nearby objects are excellent targets for further study to derive their parallaxes and to search for fainter, later companions with AO and/or methane imaging.Comment: 11 pages, 10 figures, accepted to MNRA

    Time-to-birth prediction models and the influence of expert opinions

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    Preterm birth is the leading cause of death among children under five years old. The pathophysiology and etiology of preterm labor are not yet fully understood. This causes a large number of unnecessary hospitalizations due to high--sensitivity clinical policies, which has a significant psychological and economic impact. In this study, we present a predictive model, based on a new dataset containing information of 1,243 admissions, that predicts whether a patient will give birth within a given time after admission. Such a model could provide support in the clinical decision-making process. Predictions for birth within 48 h or 7 days after admission yield an Area Under the Curve of the Receiver Operating Characteristic (AUC) of 0.72 for both tasks. Furthermore, we show that by incorporating predictions made by experts at admission, which introduces a potential bias, the prediction effectiveness increases to an AUC score of 0.83 and 0.81 for these respective tasks

    The Parallel Complexity of Growth Models

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    This paper investigates the parallel complexity of several non-equilibrium growth models. Invasion percolation, Eden growth, ballistic deposition and solid-on-solid growth are all seemingly highly sequential processes that yield self-similar or self-affine random clusters. Nonetheless, we present fast parallel randomized algorithms for generating these clusters. The running times of the algorithms scale as O(log2N)O(\log^2 N), where NN is the system size, and the number of processors required scale as a polynomial in NN. The algorithms are based on fast parallel procedures for finding minimum weight paths; they illuminate the close connection between growth models and self-avoiding paths in random environments. In addition to their potential practical value, our algorithms serve to classify these growth models as less complex than other growth models, such as diffusion-limited aggregation, for which fast parallel algorithms probably do not exist.Comment: 20 pages, latex, submitted to J. Stat. Phys., UNH-TR94-0
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