DCCSEDU 2017 Abstracts

Short Papers
Paper Nr: 1

Self-assessment of Higher Online Education Programmes


Renata Marciniak

Abstract: This paper presents a PhD project which purpose is to design a model to be applied in the self-assessment of online education programmes. The starting point of the design is a bibliographical-documental analysis of the elements of online education programmes as well as a specific bibliographical study of the standards, models and tools created in order to evaluate the quality of online education. Based on the results of the said analysis, a model for the self-assessment of higher online education programmes is created, composed of two variables, fourteen dimensions and one hundred eleven indicators. Before creating the definitive model, two drafts were created and subject to the validation by international online education experts and discussed in two discussion groups: one composed of experts in online education and the other one composed of online students. Nevertheless, in order to verify the total utility of the designed model it should be applied in the self-assessment of various online programmes in different countries.

Paper Nr: 2

Implementation of a Framework for e-Assessment on Students’ Devices


Bastian Küppers and Ulrik Schroeder

Abstract: Following the trend of digitalization in university education, lectures and accompanying exercises and tutorials incorporate more and more digital components. These digital components spread from the usage of computers and tablets in tutorials to incorporating online learning management systems into the lectures. Despite e-Assessment being a valuable component in form of self-tests and formative assessment, the trend of digitalization has not yet been transferred on examinations. That is among other things caused by financial reasons, because maintaining a suitable IT-infrastructure for e-Assessment is expensive in terms of money as well as administrative effort. This paper presents a Bring Your Own Device approach to e-Assessment as potential solution to this issue.

Paper Nr: 3

Uncertainty and Integration of Emotional States in e-Learning - Doctoral Consortium Paper


Grzegorz Brodny

Abstract: One of the main applications of affective computing remains supporting e-learning process. Therefore, apart from human mentoring, automatic emotion recognition is also applied in monitoring learning activities. Specific context of e-learning, that happens at home desk or anywhere (mobile e-learning), adds additional challenge to emotion recognition, e.g. temporal unavailability and noise in input channels. Nowadays, affective computing has provided many solutions for emotion recognition. There are numerous emotion recognition algorithms which differ on input information channels, representation emotion model on output and classification method. The most common approach is to combine the emotion information channels. Using multiple input channels proved to be the most accurate and reliable, however there is no standard architecture proposed for this kind of solutions. This paper presents outline of the author's PhD thesis, which concentrates on integration of emotional states in educational applications with consideration of uncertainty. The paper presents state of art, the architecture of integration, performer experiments and planned simulations.