43,339 research outputs found
Enhancing students’ confidence, competence and knowledge with Integrated Skills Challenge
Introduction/background:
In today's complex healthcare environment, new nursing graduates are expected to master nursing skills in a timely manner and become critical thinkers with the capacity of solving complex healthcare problems efficiently. The increased complexity of the clinical setting requires competence-building begin in introductory courses, establishing foundational skills for critical thinking and prioritisation. In the healthcare professions, teaching and learning methods are focused on integration of clinical knowledge and skills. However, traditional teaching and learning methodologies do not always facilitate the development of a requisite level of these clinical skills. For the Master of Nursing Studies (MNSt) students whose program is shortened this means the acquisition of these skills must be achieved more rapidly.
Aim/objectives:
The purpose of this study is to investigate the feasibility of developing simulation scenarios (Integrated Skill Challenge [ISC]) as a supplemental teaching-learning strategy to enhance the transfer of student self-confidence and competence to the clinical nursing environment.
Methods
To examine potential effects of ISC on the MNSt students, a pilot study was conducted including 52 participants. Data were collected weekly over 11 week period by using pre and post-test design.
Results:
Analysis showed a significant increase in the confidence, competence and knowledge. Confidence, competence and knowledge scores increased when students were pre-loaded with knowledge prior to performing in the ISC. Results generally indicated that the ISC had the anticipated effects.
Conclusions:
This study reveals a high feasibility of developing simulation scenarios as an active learning methodology and that it should be developed further and piloted on a larger sample
Investigation of the utilisation of social networks in e-learning at universities
Over the years universities have considered to use social networks for learning purposes as most of their students now engage on them. However, questions on the impact social networks would have on learning and how they can be utilised further for more effective teaching and learning are still unclear. To solve these questions, an in-depth investigation has been conducted to understand the benefits and drawback of social network features available for students. The investigation results show that students strongly believe that social network features will help enhance learning and the key ways of utilising such features have been suggested
Iterative Detection of Diagonal Block Space Time Trellis Codes, TCM and Reversible Variable Length Codes for Transmission over Rayleigh Fading Channels
Iterative detection of Diagonal Block Space Time Trellis Codes (DBSTTCs), Trellis Coded Modulation (TCM) and Reversible Variable Length Codes (RVLCs) is proposed. With the aid of efficient iterative decoding, the proposed scheme is capable of providing full transmit diversity and a near channel capacity performance. The performance of the proposed scheme was evaluated when communicating over uncorrelated Rayleigh fading channels. Explicitly, significant iteration gains were achieved by the proposed scheme, which was capable of performing within 2~dB from the channel capacity
Gravitational Theory with a Dynamical Time
A gravitational theory involving a vector field , whose zero
component has the properties of a dynamical time, is studied. The variation of
the action with respect to gives the covariant conservation of an
energy momentum tensor . Studying the theory in a
background which has killing vectors and killing tensors we find appropriate
shift symmetries of the field which lead to conservation laws. The
energy momentum that is the source of gravity is different
but related to and the covariant conservation of determines in general the vector field . When is chosen to be proportional to the metric, the theory
coincides with the Two Measures Theory, which has been studied before in
relation to the Cosmological Constant Problem. When the matter model consists
of point particles, or strings, the form of , solutions for
are found. For the case of a string gas cosmology, we find that
the Milne Universe can be a solution, where the gas of strings does not curve
the spacetime since although , , as a model for the early universe, this solution is also free
of the horizon problem. There may be also an application to the "time problem"
of quantum cosmology.Comment: 21 pages, discussions extended, some more explicit proofs included,
more references include
Steady state and dynamic properties of journal bearings in laminar and superlaminar flow regimes. II - Full floating ring bearings
Steady state and dynamic properties of journal bearings in laminar and superlaminar flow regime
Time-Varying Volatility and the Dynamic Behavior of the Term Structure
In this paper, we consider a framework with which the cross sectional and time series behavior of the yield curve can be studied simultaneously. We examine the relationship between the yield curve and the time-varying conditional volatility of the Treasury bill market. We demonstrate that differently shaped yield curves can result given different combinations of volatility and expectations about future spot rates. Moreover, adjusting the forward rate for the volatility related liquidity premium can improve its performance as a predictor of future spot rates at least for the period from August 1964 to August 1979.
Measuring and Testing the Impact of News on Volatility
This paper introduces the News Impact Curve to measure how new information is incorporated into volatility estimates. A variety of new and existing ARCH models are compared and estimated with daily Japanese stock return data to determine the shape of the News Impact Curve. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. A partially non-parametric ARCH model is introduced to allow the data to estimate this shape. A comparison of this model with the existing models suggests that the best models are one by Glosten Jaganathan and Runkle (GJR) and Nelson's EGARCE. Similar results hold on a pre-crash sample period but are less strong.
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