Screen recording has gradually emerged as an efficacious tool in the context of process-oriented translator training. From an assessment standpoint, process protocols derived from screen recordings would seem to hold great potential as an empirical means through which translators and translation trainers can re-trace errors found in translation products back to underlying problem triggers that emerge during their creation. This chapter will begin by outlining how screen recordings can be utilized to reverse engineer translation products for purposes of process-oriented assessment. A series of directly observable indicators will be linked with various error classification parameters, including locus (comprehension, transfer, or production), phase (drafting or revision), and information retrieval type (internal or external) in providing assessors with a diagnostic gauge for pinpointing potential triggers. The chapter will conclude with some preliminary data on evidence of inter-rater consistency when screen recording is used in such a diagnostic capacity by various student populations.
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In the context of translation pedagogy, from the mid-1990s onwards, learner self-assessment has gained momentum as trainers have come to embrace the constructivist tenets of guiding students to “assume responsibility for their own work” and “assess the quality of their own performance” (Kiraly, 2003, p. 31). This trend is driven by a number of interrelated factors. From the perspective of language industry realities, where formal external feedback tends to be scant and no news is usually good news, trainers realize that providing students with frameworks and a skillset to assess their own performance prior to entering the industry becomes crucial. If professional translators have aspirations of advancing along an expertise trajectory, deliberate practice is an absolute necessity, and one of the primary conditions that needs to be met in order for practice to be deliberate involves working with feedback (Ericsson, 1996, p. 21). While ISO 17100 (ISO, 2015) establishes an ideal best practice of translations passing through stages of editing, proofreading, and other revisions for purposes of quality assurance, conditions are not in place for the translators to necessarily receive concrete, informative feedback on their performance. ISO 17100 also calls for the translator to check his/her own work after finalizing the initial translation. In many situations, particularly in those involving translation work that that does not meet ISO 17100 specifications, the onus for quality assurance is predominantly on the translator. Oftentimes, professional translators need to be in a position to assess their own performance, and their being able to successfully do so hinges upon their receiving formal training in this area. The importance of this is reflected in translation competence models foregrounding self-evaluation as an assessment instrument (Hurtado Albir, 2015, p. 269).
A second factor contributing to the current trend towards learner self-assessment involves technological advancement. Elearning management systems have opened new doors insofar as opportunities for learner collaboration and peer-based assessment are concerned, particularly in combination with tutor moderation (Robinson, López Rodríguez, & Tercedor Sanchez, 2006). Blogs, wiki projects, and rubric templates have expanded the horizons regarding not only from whom students of translation receive feedback, but also in which capacities and through which channels. In this day and age, feedback has the potential to be a real-time, interactive, multimedia experience. Furthermore, the virtual environment inherent to elearning can ideally be set up in a fashion that simulates interaction and quality control practices that arise within the lifespan of a given professional translation project. Robinson et al. (2006) call attention to the importance of providing learners with established rubrics and modeling their utilization for optimizing self- and peer-assessment (p. 124). Technological advancement has also resulted in new avenues for assessing performance, many of which have been borrowed from the translation process research community, particularly derived from research on translation competence (Hurtado Albir, 2017). Retrospective process-oriented performance assessment can now be carried out using such technology as audio recordings of verbalized thought processes (Jääskeläinen, 2002), keystroke logging (Hansen, 2006), and screen recordings (Angelone, 2012). The latter two technologies are gaining ever-firmer footing in the self-assessment of processes thanks to their preservation of ecological validity. In gaining insightful data for purposes of retrospective reflection, the translator does not have to do anything he or she would otherwise not do while translating, such as having to articulate all thought processes or break away from the task at hand to enter content in a translation log. Eye-tracking technology holds potential in this regard as well as it continues to become less intrusive and more mobile.