How to Bring a Graduate Program Closer to Employers’ Needs? View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Laurent Veillard , Stéphanie Tralongo , Catherine Galli , Abdelaziz Bouras , Michel Le Nir

ABSTRACT

Since the mid of the 1990s, Qatar is engaged in an economic diversification strategy to move away from an economy strongly based on gas and oil. The national authorities consider that high-quality education, especially at the tertiary level, is absolutely essential to succeed in this strategy. Despite of repeated reforms since the middle of the nineties, there are still some important difficulties in the Qatari higher education system, and especially in Qatar University (QU), the main national university. One of them is related to academic programs not really preparing students for professional integration. The Pro-Skima project aims at finding possible pedagogical modifications of the curriculum of the Master of Science in Computing of QU, to better meet the needs of highly skilled workers in the IT professional sector in Qatar. Part of this project is a sociological study of the main characteristics of the existing curriculum of this master program. Results highlight a curriculum based on an Anglo-Saxon model. In this model, several internal and external accreditation institutions have a strong influence on any evolution of the curriculum. They put different constraints that give little space to discuss more flexibly with local employers in order to change the curriculum. Further developments of the project consist in finding what could be some concrete solutions to overcome these difficulties and bring the curriculum closer to employers’ needs. On possibility is to experiment a curriculum that includes more workplace learning periods. More... »

PAGES

183-192

References to SciGraph publications

Book

TITLE

Teaching and Learning in a Digital World

ISBN

978-3-319-73209-1
978-3-319-73210-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-73210-7_22

DOI

http://dx.doi.org/10.1007/978-3-319-73210-7_22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100074963


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