BRAIN: Personality Questionnaires as a Basis for Improvement of University Courses in Applied Computer Science and Informatics
In order to ensure optimal teaching conditions for university students, attention should be brought to their personality traits and academic performance. In the paper Personality Questionnaires as a Basis for Improvement of University Courses in Applied Computer Science and Informatics, the authors Vladimir Ivančević, Marko Knežević, and Ivan Luković present the foundation for such an adaptation of the teaching process, supported by an analytical software solution (in its initial version).
The software solution presents two main components: a data warehouse for storing collected data and an analytical software tool (built using the Shiny framework). The data warehouse contains collected data about student academic performance and personality traits, while the analytical tool is a web application that retrieves data from the data warehouse or external CSV files matching the required structure and allows analysts to perform exploration and analysis of data concerning student performance and personality.
In neurology and neuroscience research, Steady-State Visually Evoked Potential (SSVEP) are brain signals which occur in response to visual stimulation. The paper Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed – written by Abdullah Talha Sözer and Can Bülent Fidan – aims to introduce novel detection features for the SSVEP based brain computer interfaces. Brain-computer interface (BCI) is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb. The interface enables direct communication between the brain and the object to be controlled.