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Integrating machine translation into MOOCS

Castilho, Sheila orcid logoORCID: 0000-0002-8416-6555, Gaspari, Federico orcid logoORCID: 0000-0003-3808-8418, Moorkens, Joss orcid logoORCID: 0000-0003-4864-5986 and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2017) Integrating machine translation into MOOCS. In: EDULEARN17, 3-5 July 2017, Barcelona, Spain. ISBN 978-84-697-3777-4

Abstract
This paper presents TraMOOC (Translation for Massive Open Online Courses), a European research project developed with the intention of empowering international learners in the digital multilingual world by providing reliable machine translation (MT) specifically tailored to MOOCs from English into 11 languages (Bulgarian, Chinese, Croatian, Czech, Dutch, German, Greek, Italian, Polish, Portuguese, and Russian). The paper describes how the project is addressing the challenges involved in developing an innovative, high-quality MT service for producing accurate translations of heterogeneous multi-genre MOOC materials, encompassing subtitles of video lectures, assignments, tutorials, and social web text posted on student blogs and fora. Based on the results of a large-scale and multi-method evaluation conducted as part of the TraMOOC project, we offer a reflection on how to best integrate state-of-the-art MT into MOOC platforms. The conclusion summarizes the key lessons learned, that can be applied by the wider community of international professionals with an interest in the multilingual aspects of innovative education and new learning technologies.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:MOOCs; translation; e-learning; distance learning
Subjects:Computer Science > Machine learning
Social Sciences > Distance education
Social Sciences > Educational technology
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Proceedings of EDULEARN17 Conference. . International Academy of Technology, Education and Development (IATED). ISBN 978-84-697-3777-4
Publisher:International Academy of Technology, Education and Development (IATED)
Official URL:http://dx.doi.org/10.21125/edulearn.2017.0765
Copyright Information:© 2017 IATED
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:European Union’s Horizon 2020 research and innovation programme under grant agreement № 644333, ADAPT Centre for Digital Content Technology at Dublin City University is funded under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.
ID Code:23351
Deposited On:23 May 2019 15:15 by Thomas Murtagh . Last Modified 20 Jan 2021 16:50
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