Teaching data science to undergraduate translation trainees: Pilot evaluation of a task-based course

Abstract

The advancement in technology has changed the workflow and the role of human translator in recent years. The impact from the trend of technology-mediated translation prompted the ratification of technology literacy as a major competence for modern translators. Consequently, teaching of translation technology including but not limited to Computer-aided Translation (CAT) and Machine Translation (MT) became part of comprehensive curricula for translation training programs. However, in many institutions, the teaching of translation technology was haunted by issues such as: narrow scope of curriculum design, outdated technologies, and unbalance between theories and practices in teaching. The study was the pilot evaluation of a tailored course to foster translation trainees’ knowledge and abilities of data science. The course was designed to be a fundamental step toward sophisticated translation technologies. During the pilot evaluation of the 8-week course, 85 students (n = 85) were recruited as participants. The study adopted a mix-method design by employing a survey to investigate student’s level of satisfaction toward the course and focus group discussion to understand students’ attitudes and perceptions of key aspects of the course. By interpreting the results from statistical analysis of the survey (5.39/7) and thematic analysis of the focus group discussion, the course of data science for translators was well received among participants. The evaluation project manifested the feasibility and effectiveness of a translator-oriented data science course.

Online informal learning community for interpreter training amid COVID-19: A pilot evaluation

“…Additionally, it should be noted that the design and implementation of informal learning was part of a comprehensive restructuring of the interpreting program at XYAFU. Consequently, relevant adjustments in curriculum, teaching methods and recalibration of training objectives were undergoing [ 37 ]. As suggested by Temban and his colleagues, pre-determined and prescriptive learning objectives and curricular settings used in formal learning environment hindered the development and augmentation of informal learning [ 45 ].…”

“…Supportive and secondary research methods included survey, observation and document analysis. A survey adopted from previous studies measuring students’ perception towards an educational project was used to provide quantitative evidence regarding students’ level of satisfaction towards the informal learning project [ 37 , 38 ] (The survey was shown in S1 Appendix ). Observations of classroom activities and the informal learning project were used to provide a lens from which student’s involvement and engagement were examined.…”

Investigating students’ attitudes towards translation technology: The status quo and structural relations with translation mindsets and future work self

“…In the context of training of translation, technology seems to be the elephant in the room ( Cheung, 2022 ). Given its wide application across the industry, training students in technology has become an indispensable part of translation education ( Yan and Wang, 2022 ). Concerning TTT, according to Alcina Caudet (2002) , students’ attitudes towards translation technology should be one of the essential didactic foci.…”

“…Translation technology denotes a variety of technologies employed by translators in the translation process, for instance, search engines, CAT tools, corpora use, machine translation, localization tools, quality assurance tools, resource management software, and so on ( Man et al, 2020 ; He et al, 2022 ). As confirmed by numerous surveys ( Biau-Gil and Pym, 2006 ; Bowker and Marshman, 2010 ; Krüger, 2018 ), translation technology has brought drastic changes to the translators’ workflow ( Sikora, 2014 ; Yan and Wang, 2022 ) and is becoming increasingly entrenched in today’s translation profession. This “technological turn” ( Cronin, 2010 ) has prompted the ratification of instrumental competence as the significant component of translation competence ( EMT, 2017 ; PACTE, 2018 ).…”

“…(3) In response, a substantial bulk of study has been done on TTT course design with detailed accounts of what to teach and how to teach. In terms of what to teach, scholars have conducted enormous research on its teaching contents and resources in various sub-topics, such as computer-assisted translation ( Doherty and Moorkens, 2013 ; Enríquez Raído, 2013 ; Shuttleworth, 2017 ; Rodríguez-Castro, 2018 ), term management ( Martínez and Benítez, 2009 ), localization ( Jiménez-Crespo and Tercedor, 2011 ; Jiménez-Crespo, 2013 ), statistical machine translation ( Doherty and Kenny, 2014 ), machine translation and post-editing ( Moorkens, 2018 ; Guerberof Arenas and Moorkens, 2019 ), technical writing ( Tao et al, 2020 ), specialized corpora ( Rodríguez-Inés, 2013 ), python-based repository ( Krüger, 2021 ), and data science ( Yan and Wang, 2022 ). Meanwhile, topics like the technological skill-sets that student translators are required to acquire were often discussed ( Austermühl, 2013 ; Gaspari et al, 2015 ; He and Tao, 2022 ).…”