'Democracy begins in conversation’: the phenomenology of problem-based learning and legal education

Learning is complex for any number of reasons. One of these is that it doesn’t take place in a laboratory: it happens in real places, within and between real people, and as a consequence it takes place in multi-factorial environments. At every stage of learning in Higher Education (HE), from student choice of institution and programme, to the transfer of learning from theory to practice, to a single institution’s or a teacher’s evaluation of teaching and learning, there are many causal factors that affect educational process and outcome. The complexities and variables created by the interaction of such multiple factors, well known in the field of education, make learning a highly complex phenomenon to analyse and understand

A Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to Knowledge Acquisition

Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to knowledge acquisition is proposed in this paper as a viable solution to the challenges of rule-based unwieldiness and sharp boundary problem in building a fuzzy rule-based expert system. The fuzzy models were based on domain experts’ opinion about the data description. The proposed approach is committed to modelling of a compact Fuzzy Rule-Based Expert Systems. It is also aimed at providing a platform for instant update of the knowledge-base in case new knowledge is discovered. The insight to the new approach strategies and underlining assumptions, the structure of FARME-D and its practical application in medical domain was discussed. Also, the modalities for the validation of the FARME-D approach were discussed

A survey of UK medical schools' arrangements for early patient contact

Background: Many U.K. medical schools have patient contact in the first two years of the undergraduate course. Aim: To compare the purposes and organization of early patient contact in UK medical schools and to relate these arrangements to the schools' curricular objectives. Methods: A telephone survey of lead educators in UK medicals schools. Categories of contact were plotted against phases of the course to discern patterns of organisation. Results: The quantity of contact varies considerably (four to 65 days). There is a pattern, with learning objectives around the social context of health and illness preceding skills based work and integrated clinical knowledge for practice coming later. Schools fall into three categories: close adherence to the preclinical/clinical split, with limited early contact acting as an introduction to social aspects of health; provision of substantial patient contact to maximize the integration of knowledge and skills; and transitional, with limited clinical goals. General practice provides between one third and one half of early patient contact. Conclusions: Arrangements meet the objectives set by each school and reflect differing educational philosophies. Change is toward more early contact. There appears to be no national guidance which supports a minimum quantity of patient contact or specific educational purpose in the early years of U.K. basic medical training

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

In this paper we present a novel method for the correction of motion artifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of the whole uterus. Contrary to current slice-to-volume registration (SVR) methods, requiring an inflexible anatomical enclosure of a single investigated organ, the proposed patch-to-volume reconstruction (PVR) approach is able to reconstruct a large field of view of non-rigidly deforming structures. It relaxes rigid motion assumptions by introducing a specific amount of redundant information that is exploited with parallelized patch-wise optimization, super-resolution, and automatic outlier rejection. We further describe and provide an efficient parallel implementation of PVR allowing its execution within reasonable time on commercially available graphics processing units (GPU), enabling its use in the clinical practice. We evaluate PVR's computational overhead compared to standard methods and observe improved reconstruction accuracy in presence of affine motion artifacts of approximately 30% compared to conventional SVR in synthetic experiments. Furthermore, we have evaluated our method qualitatively and quantitatively on real fetal MRI data subject to maternal breathing and sudden fetal movements. We evaluate peak-signal-to-noise ratio (PSNR), structural similarity index (SSIM), and cross correlation (CC) with respect to the originally acquired data and provide a method for visual inspection of reconstruction uncertainty. With these experiments we demonstrate successful application of PVR motion compensation to the whole uterus, the human fetus, and the human placenta.Comment: 10 pages, 13 figures, submitted to IEEE Transactions on Medical Imaging. v2: wadded funders acknowledgements to preprin