The capacity of European Higher Educational Institutions to address threats imposed by natural hazards View Full Text


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Article Info

DATE

2016-04

AUTHORS

Skevi Perdikou, Jiri Horak, Lena Halounov√°, Roshani Palliyaguru, Andrew Lees

ABSTRACT

The main aim of this work was to investigate the availability and capacity of educational programmes at different levels at European Higher Educational Institutions (HEI) that are directly related to disaster resilience. This investigation was important since education in disaster resilience for citizens, communities, public administrators and decision makers is vital for improving preparedness, mitigation, resistance, absorption and recovery as a result of natural disasters. For this purpose, a study on the capacity of HEIs across Europe to address the threats imposed by natural hazards has been carried out. The study was performed by using a web-based survey tool which ran for 1 year with participants from 28 European countries. Findings of this work showed a great lack of educational programmes in disaster resilience across Europe. However, in recent years, there has been an increase in such programmes mainly at postgraduate level. At undergraduate level, there is only a very limited number of such programmes, which might be related to the multidisciplinary nature of these programmes. The cohort size of the ongoing programmes indicates that they are in good health despite their young age, suggesting the potential and need for many more. The results of this study are valuable for HEIs, policy makers, decision makers and governments as it provides an insight into the existing situation across Europe with regard to educational programmes directly related to disaster resilience which can help them to focus, direct and promote education in disaster resilience according to the needs at national and European level. More... »

PAGES

1447-1466

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11069-015-2139-2

DOI

http://dx.doi.org/10.1007/s11069-015-2139-2

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https://app.dimensions.ai/details/publication/pub.1053711501


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