The use of electronic voting systems to enhance deep learning.

The present paper introduces a technology-enhanced teaching method that promotes deep learning. Four stages that correspond to four different student cohorts were used for its development and to analyse its effectiveness. The effectiveness of the method has been assessed in terms of examination results as well as results obtained from class response system software statistics. The evidence gathered indicates that the method developed is very effective and its implementation is straightforward. Furthermore, its success in achieving results seems to be independent of the skills and/or experience of the lecturer.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in clouds: A04BPEL3.0 proposal.

Model Driven based approach for Service Evolution in Clouds will mainly focus on the reusable evolution patterns' advantage to solve evolution problems. During the process, evolution pattern will be driven by MDA models to pattern aspects. Weaving the aspects into service based process by using Aspect-Oriented extended BPEL engine at runtime will be the dynamic feature of the evolution.