European higher education remains too conservative to adapt to technological innovations, said a Commission High Level Group on the Modernisation of Higher Education in its report published last week (22 October).
The group, which was launched in 2012 to examine such challenges, makes 15 recommendations to EU member states about how to integrate digital teaching and learning methods in their educational curricula.
Current learning systems are reluctant to leave behind conventional classroom methods and restructure the way universities and schools operate. Teachers do not have the necessary professional training to cope with new ways of schooling. The institutions themselves are poorly equipped with new technologies in order to deliver high quality, online education.
“Although Europe is starting to make progress, it is still lagging behind the US in using new technologies in our universities and colleges,” said Mary McAleese, the former President of Ireland, and chair of the High Level Group. “We should capitalise on the strengths we have, such as the wide use of ECTS [European Credit Transfer and Accumulation System] credits to ensure that digital learning in Europe is recognised, accredited and quality assured.”
Students are also reluctant to enroll in online degree programs, as an alternative to traditional, classroom-based ones, because many online courses do not offer credits towards obtaining a diploma. In fact, one of the group's recommendations to EU countries is that they recognise e-learning as a legitimate part of the educational system, and formalise it.
Computational complexity could offer new insight into old ideas in biology and, yes, even the dismal science.
Economists are sometimes content asking whether or not a banking system could be stable or a market could continue to grow. But they and other scientists could benefit from a computational view that asks not just whether the right conditions exist but also how hard it is to find them, according to a commentary published today in Proceedings of the National Academy of Sciences.
The “how hard?” question is about computational complexity, saysChristos Papadimitriou, a University of California-Berkeley computer scientist and the commentary’s author. “Nature, [people]—they are doing some kind of computation,” he says, but some computations are easier than others.