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Titel
Maschinelle Übersetzung in der Didaktik : Am Beispiel der Universität Innsbruck
VerfasserNeuhold, Nina
Betreuer / BetreuerinnenSandrini, Peter
Erschienen2019
HochschulschriftInnsbruck, Univ., Masterarb., 2019
Datum der AbgabeJanuar 2019
SpracheDeutsch
DokumenttypMasterarbeit
Schlagwörter (DE)Maschinelle Übersetzung / MÜ-Systeme / Maschinelle Übersetzungssysteme / TranslatorInnenausbildung / universitäre Ausbildung / Universität Innsbruck / Lehrinhalte / Lehrziele
Schlagwörter (EN)machine translation / MT systems / translator training / teaching content / University of Innsbruck / teaching content / teaching objectives
URNurn:nbn:at:at-ubi:1-36262 Persistent Identifier (URN)
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Maschinelle Übersetzung in der Didaktik [2.07 mb]
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Zusammenfassung (Englisch)

This thesis examines the applicability of machine translation as a tool for professional and prospective translators, with the aim of improving curriula and teaching objectives of training institutes and adapting them to the technological development of MT. It is argued that these significant developments should be embraced in order to offer a broader range of translation services and to enable a profitable operation through knowledge and skills related to MT. For the research, a survey was deducted by means of three different questionnaires, asking professional translators and students as well as lecturers from the University of Innsbruck about their use of and points of view on MT in order to identify their perception and use of MT. The results have shown that machine translation is used on a voluntary basis by about half of the respondents, that common MT systems are evaluated in a variety of ways and that there is a fundamental will to regard MT as an integral part of translator training. The translation competence models of the EMT and PACTE Group are also in favour of working with MT in translator training institutes. For the implementation of MT, different approaches are discussed. These provide starting points for the formal and content-related framework of MT-related classes. In addition, existing models for MT integration can be optimised using a negative approach where the graduates lack of skills is identified and teaching content is adapted.

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