Cognitive load in processing ELF: Translators, interpreters, and other multilinguals

Abstract

Many factors can affect the translation and interpreting process, but the quality of source texts has been explicitly identified as an issue in surveys of professional translators and interpreters as well as in recent workplace studies. If translators and interpreters encounter resistance in carrying out their tasks, for example by difficulties in extracting meaning from non-native English input, then flow can be interrupted and performance affected. In this paper, we explore how English as a lingua franca (ELF) input could potentially increase the cognitive load not only for translators and interpreters but also for other multilinguals. We describe the range of methods that can be used to measure the cognitive effort and stress associated with processing ELF input and explain the challenges that can be encountered when researchers are committed to using authentic ELF material to make comparisons under relatively controlled but ecologically valid conditions. One of the driving motivators for this type of research is to understand how interpreters and translators deploy their expertise to deal with ELF input in work settings in order to draw inferences about strategies for other segments of the population.

A Synthetic Review of Cognitive Load in Distance Interpreting: Toward an Explanatory Model

“…Analytical methods in interpreting can be mainly used to evaluate input dimensions of cognitive load, meaning that researchers can apply judgment and/or mathematical methods to measure the cognitive load induced by the task and environment factors ( Chen, 2017 ; Ehrensberger-Dow et al, 2020 ). Although a fine-grained analytical model of the overall cognitive load in DI is still to be developed, we believe the current study would be a step toward specifying the key causal factors of cognitive load in DI and their measurement methods.…”

“…Since technology has played an increasingly important role in the interpreting service industry, the factors specified for DI in this study would provide important implications for research and practice. For example, the identification of technology awareness factors would help curriculum designers and trainers in translation and interpreting programs to embed these factors into course contents (Ehrensberger-Dow et al, 2020). Third, the framework presented in this paper serves not only as a descriptor of factors affecting cognitive load, but also as a predictive tool in which the pros and cons of the measurement methods were analyzed and presented (Chittleborough and Treagust, 2009).…”

“…Since technology has played an increasingly important role in the interpreting service industry, the factors specified for DI in this study would provide important implications for research and practice. For example, the identification of technology awareness factors would help curriculum designers and trainers in translation and interpreting programs to embed these factors into course contents ( Ehrensberger-Dow et al, 2020 ).…”

The impact of task complexity and translating self-efficacy belief on students’ translation performance: Evidence from process and product data

“…This is consistent with the constructs of cognitive load and cognitive effort developed in educational psychology ( Sweller et al, 1998 ). While the cognitive load of a task can theoretically be identical for different students ( Liu et al, 2019 ; Ehrensberger-Dow et al, 2020 ), the cognitive effort expended in a task is individual since students have certain freedom regarding how much effort to expend and how to expend it ( Feng, 2017 ; Sun et al, 2020 ).…”

“…By far, task complexity has been an issue central to curriculum and test development in translator education ( Sun and Shreve, 2014 ). Myriad factors contribute to the complexity of translation tasks, such as source text complexity ( Sun and Shreve, 2014 ), source text quality ( Ehrensberger-Dow et al, 2020 ), the number of simultaneous tasks ( Sun et al, 2020 ), task familiarity ( Pokorn et al, 2019 ), and directionality ( Whyatt, 2019 ). Among them, source text complexity has been a constant focus.…”