E‐learning: new opportunities in continuing professional development
The growth in professional learning is opening up many new opportunities for the application of e‐learning to the world of continuing professional development (CPD). CPD programmes require professionals to engage in annual programmes of professional development, and in some cases revalidation or recertification. To date, most of this activity has been off‐line. Increasingly, CPD requirements will be satisfied through the use of learning resources available on‐line or packaged into specially tailored e‐learning courses. Societies and professional associations – as the primary managers and coordinators of CPD programmes – are in a strong position to expand upon their existing Web‐based initiatives to deliver a new generation of e‐learning services to their members.
Factors mediating the routinisation of e-learning within a traditional university education environment
Technology-enhanced or Computer Aided Learning (e-learning) can be institutionally integrated and supported by learning management systems or Virtual Learning Environments (VLEs) to offer efficiency gains, effectiveness and scalability of the e-leaning paradigm. However this can only be achieved through integration of pedagogically intelligent approaches and lesson preparation tools environment and VLE that is well accepted by both the students and teachers. The aim of this study is to consider how effective and efficient e-learning is in a web platform environment. The paper concludes that blended learning approaches offer the most flexible and scalable route to e-learning.
Inversion of self-potential anomalies caused by 2D inclined sheets using neural networks
The modular neural network (MNN) inversion method has been used for inversion of self-potential (SP) data anomalies caused by 2D inclined sheets of infinite horizontal extent. The analysed parameters are the depth (h), the half-width (a), the inclination (α), the zero distance from the origin (xo) and the polarization amplitude (k). The MNN inversion has been first tested on a synthetic example and then applied to two field examples from the Surda area of Rakha mines, India, and Kalava fault zone, India. The effect of random noise has been studied, and the technique showed satisfactory results. The inversion results show good agreement with the measured field data compared with other inversion techniques in use.