Castilho, Sheila ORCID: 0000-0002-8416-6555, Gaspari, Federico ORCID: 0000-0003-3808-8418, Moorkens, Joss ORCID: 0000-0003-4864-5986 and Way, Andy ORCID: 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 Institutes 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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