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.

A university e-learning system to enhance higher education teaching environments: a model-base innovative service-orientated clouds intensive evolution approach.

The International Conference on Advanced Materials, Structures and Mechanical Engineering 2015 (ICAMSME 2015) was held on May 29-31, Incheon, South-Korea. The conference was attended by scientists, scholars, engineers and students from universities, research institutes and industries all around the world to present on going research activities. This proceedings volume assembles papers from various professionals engaged in the fields of materials, structures and mechanical engineering.

Sonifying the solar system.

Sound is potentially an effective way of analysing data and it is possible to simultaneously interpret layers of sounds and identify changes. Multiple attempts to use sound with scientific data have been made, with varying levels of success. On many occasions this was done without including the end user during the development. In this study a sonified model of the 8 planets of our solar system was built and tested using an end user approach. The sonification was created for the Esplora Planetarium, which is currently being constructed in Malta. The data requirements were gathered from a member of the planetarium staff, and 12 end users, as well as the planetarium representative tested the sonification. The results suggest that listeners were able to discern various planetary characteristics without requiring any additional information. Three out of eight sound design parameters did not represent characteristics successfully. These issues have been identified and further development will be conducted in order to improve the model.