961 resultados para nursing student


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An experiment was conducted to evaluate the effects of control of carbon/nitrogen ratio (C/N ratio) by addition of low cost carbohydrate to the water column on water quality and pond ecology in freshwater prawn Macrobrachium rosenbergii post-larvae nursing system. In this experiment, two level of dietary protein 20% and 35% without carbohydrate addition (‘P20' and ‘P35') and with carbohydrate addition (‘P20+CH' and ‘P35+CH') were compared in small ponds of 40 m² area stocked with 20 post-larvae (0.021 ± 0.001g) per m² . Maize flour was used as low cost carbohydrate and applied to the water column followed by the first feeding during the day. The addition of carbohydrate significantly reduced (p< 0.05) ammonia-nitrogen (NH sub(3)-N) and nitrite-nitrogen (NO sub(2) - N) of water in P20 + CH and P35 + CH treatments. It significantly increased (p< 0.05) the total heterotrophic bacteria (THB) population both in water and sediment. Fifty nine genera of plankton were identified belonging to the Bacillariophyceae (11), Chlorophyceae (21), Cyanophyceae (7), Dinophyceae (1), Rotifera (7) and Crustacea (9) without any significant difference (p>0.05) of total phytoplankton and zooplankton among the treatments. Survival rate of prawn was significantly lowest (p<0.05) in P20 and no significant difference (p>0.05) was observed between P20+CH and P35 treatments. Control of C/N ratio by the addition of low-cost carbohydrate to the pond water column benefited the freshwater prawn nursing practices in three ways (1) increased heterotrophic bacterial growth supplying bacterial protein augment the prawn post-larvae growth performances, (2) reduced demand for supplemental feed protein and subsequent reduction in feed cost and (3) reduced toxic NH sub(3)-N and NO sub(2)-N levels in pond nursing system.

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This paper discusses innovations in curriculum development in the Department of Engineering at the University of Cambridge as a participant in the Teaching for Learning Network (TFLN), a teaching and learning development initiative funded by the Cambridge-MIT Institute a pedagogic collaboration and brokerage network. A year-long research and development project investigated the practical experiences through which students traditionally explore engineering disciplines, apply and extend the knowledge gained in lectures and other settings, and begin to develop their professional expertise. The research project evaluated current practice in these sessions and developed an evidence-base to identify requirements for new activities, student support and staff development. The evidence collected included a novel student 'practice-value' survey highlighting effective practice and areas of concern, classroom observation of practicals, semi-structured interviews with staff, a student focus group and informal discussions with staff. Analysis of the data identified three potentially 'high-leverage' strategies for improvement: development of a more integrated teaching framework, within which practical work could be contextualised in relation to other learning; a more transparent and integrated conceptual framework where theory and practice were more closely linked; development of practical work more reflective of the complex problems facing professional engineers. This paper sets out key elements of the evidence collected and the changes that have been informed by this evidence and analysis, leading to the creation of a suite of integrated practical sessions carefully linked to other course elements and reinforcing central concepts in engineering, accompanied by a training and support programme for teaching staff.

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We investigate the Student-t process as an alternative to the Gaussian process as a non-parametric prior over functions. We derive closed form expressions for the marginal likelihood and predictive distribution of a Student-t process, by integrating away an inverse Wishart process prior over the co-variance kernel of a Gaussian process model. We show surprising equivalences between different hierarchical Gaussian process models leading to Student-t processes, and derive a new sampling scheme for the inverse Wishart process, which helps elucidate these equivalences. Overall, we show that a Student-t process can retain the attractive properties of a Gaussian process - a nonparamet-ric representation, analytic marginal and predictive distributions, and easy model selection through covariance kernels - but has enhanced flexibility, and predictive covariances that, unlike a Gaussian process, explicitly depend on the values of training observations. We verify empirically that a Student-t process is especially useful in situations where there are changes in covariance structure, or in applications such as Bayesian optimization, where accurate predictive covariances are critical for good performance. These advantages come at no additional computational cost over Gaussian processes.

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The setting, marking and providing feedback on assessments forms an important part of a tutor’s role. Studies into the use of feedback and how it is interpreted by students indicate a mismatch between what students are looking for and what tutors think they are giving. Tutors comment that students are more interested in the mark than the feedback, and yet students indicate that they do not get enough feedback, or that it is not useful. This study investigates student and staff perceptions of the linking of marking and feedback in face-to-face sessions. A cohort of year one university students were given the option of receiving either written feedback or a 15 minute meeting with one of their tutors to have their essay marked with them. Forty nine students chose face-to-face marking, the remaining 35 students received written feedback. Focus groups were used to investigate the student experience. Staff members were also asked to reflect on the process. Students and staff found the experience of face-to-face marking beneficial and positive. Both felt that the time spent together allowed for a feedback dialogue about the piece of work, and that staff could explain and justify why marks were given.

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Urquhart,C., Thomas, R., Spink, S., Fenton, R., Yeoman, A., Lonsdale, R., Armstrong, C., Banwell, L., Ray, K., Coulson, G. & Rowley, J. (2005). Student use of electronic information services in further education. International Journal of Information Management, 25(4), 347-362. Sponsorship: JISC

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Urquhart, C. & Currell, R. (2005). Reviewing the evidence on nursing record systems. Health Informatics Journal, 11(1), 33-44. First appeared as a paper in iSHIMR2004, Proceedings of the Ninth International Symposium on Health Information Management Research, 15-17 June 2004, Sheffield, UK.

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Eckerdal, A. McCartney, R. Mostr?m, J.E. Ratcliffe, M. Zander, C. Comparing Student Software Designs Using Semantic Categorization. Proceedings of the Fifth Finnish/Baltic Sea Conference on Computer Science Education, 2005

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Rowley, J.& Urquhart, C. (2007). Understanding student information behavior in relation to electronic information services: lessons from longitudinal monitoring and evaluation Part 1. Journal of the American Society for Information Science and Technology, 58(8), 1162-1174. Sponsorship: JISC

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Urquhart, C. & Rowley, J. (2007). Understanding student information behavior in relation to electronic information services: lessons from longitudinal monitoring and evaluation Part 2. Journal of the American Society for Information Science and Technology, 58(8), 1188-1197. Sponsorship: JISC

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K. Rasmani and Q. Shen. Data-driven fuzzy rule generation and its application for student academic performance evaluation. Applied Intelligence, 25(3):305-319, 2006.

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K. Rasmani and Q. Shen. Subsethood-based Fuzzy Rule Models and their Application to Student Performance Classification. Proceedings of the 14th International Conference on Fuzzy Systems, pages 755-760, 2005.

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Kinnunen, P., McCartney, R., Murphy, L., and Thomas, L. 2007. Through the eyes of instructors: a phenomenographic investigation of student success. In Proceedings of the Third international Workshop on Computing Education Research (Atlanta, Georgia, USA, September 15 - 16, 2007). ICER '07. ACM, New York, NY, 61-72.