Peer-Reviewed Journal Details
Mandatory Fields
Doherty, Stephen and Dorothy Kenny
The Interpreter and Translator Trainer
The design and evaluation of a Statistical Machine Translation syllabus for translation students
15 ()
Optional Fields
Cloud-based SMT Machine Translation evaluation Self-efficacy Statistical machine translation Syllabus design
© 2014 Taylor & Francis. Despite the acknowledged importance of translation technology in translation studies programmes and the current ascendancy of Statistical Machine Translation (SMT), there has been little reflection to date on how SMT can or should be integrated into the translation studies curriculum. In a companion paper we set out a rationale for including a holistic SMT syllabus in the translation curriculum. In this paper, we show how the priorities and aspirations articulated in that source can be operationalised in the translation technology classroom and lab. We draw on our experience of designing and evaluating an SMT syllabus for a cohort of postgraduate student translators at Dublin City University in 2012. In particular, we report on data derived from a mixed-methods approach that aims to capture the students' view of the syllabus and their self-assessment of their own learning. Using the construct of self-efficacy, we show significant increases in students' knowledge of and confidence in using machine translation in general and SMT in particular, after completion of teaching units in SMT. We report on additional insights gleaned from student assignments, and conclude with ideas for future refinements of the syllabus.
Grant Details