Stockholm University is one of the world’s top 100 higher education institutes. 70,000 students, 1,800 doctoral students and 5,000 staff are active within the areas of science and human science. eGovlab is a major centre at the Department of Computer & System Sciences. eGovlab is a place where we are developing the future of inclusive governance – not just in theory but also in practice. We apply unconventional research frameworks and methods to visualise the impact of ICT on government transformation towards inclusion, transparency, efficiency and change management. Our free thinking team of engineers, anthropologists, designers, academics and programmers, develops and designs new possibilities for inclusive future communities and participatory governance.
Department of Computer and Systems Sciences (DSV)
At DSV, research on Technology Enhanced Learning (TEL) has been conducted since the beginning of the 1970s. While scope and focus of interest have varied over the years the research conducted has formed a critical mass of competence at DSV in this research area. We have a unique combination of psychological, sociological, pedagogical, and technical expertise, which together with our research focus on TEL has led to a number of very interesting projects.
The research conducted is internationally recognized and stretches from psychological/pedagogical studies, over mobile learning, to simulation solutions with virtual factors and computer games for / in learning. Systems developed by DSV researchers have won international prices and are used at leading universities all over the world (i.e. Harvard). We focus on both developing innovative learning systems as well as performing research on those and other TEL environments.
Our approach is interdisciplinary and our team focuses not only on technology but takes into account and deals with behavioral, cultural, and social contexts as equally important aspects. In order to emphasize the importance of flexible education, DSV is since 2010 heavily involved in open education and other flexible learning models.