Load-managed problem formats: Scaffolding and modeling the translation task to improve transfer

Kelly Washbourne
Kent State University
Abstract

Does the “expert blind spot”, our “unconscious competence”, lead us to undermine the effectiveness of our translation assignments? This study characterizes the translation task as schema-based, and thus prone to cognitive overload for the learner. Accordingly, schema acquisition tasks featuring reduced-goal specificity and goal-free problems for training the novice are reviewed. The argument is put forward that we need 1) to use more scaffolding to reduce cognitive load, 2) to vary task architecture for learning (including the use of planning pre-tasks), and 3) to provide diagnostic help for the student translator to attain context-independence for ‘high road transfer’. Formats for expertise modeling are considered—reverse tasks, completion examples, and other whole-task models—as instructional designs for load-managed translation tasks that improve problemsolving, schema acquisition, process-orientation, and metacognitive monitoring.

Keywords:
Table of contents

Translation has been called a prime example of an ill-structured domain (Kiraly 2005). In Morrison et al’s (2011, 4) definition of an ill-structured task (or domain), there may be more than one solution, more than one path, and unknown task constraints, including unavailable information. Simple examples in the translation classroom would include improving work processes, carrying out a ‘transcreation’ of a promotional text, or even justifying decisions with a translation log or thinkaloud protocol. This sort of task stands in contrast to the reiterable, algorhythmic solutions applied to problems calling for predictable procedures or routines. [ p. 339 ]Perhaps the most important aspect of ill-structuredness for translation is that it is a process calling for creative solutions rather than dualistic ‘right/wrong’ ones, and a higher-level cognitive task rather than procedural or single-component skill tasks. Translation, moreover, calls for many schema-based or non-recurrent skills (i.e., executed in different ways across problem situations (Van Merriënboer 1997)), for example a transfer task involving a unique combination of problems such as, say, a source text with a substandard level of writing, a brief prescribing that the translator leverage certain terminology, and perhaps any number of other constraints, be they extrinsic, cognitive, situational, rhetorical, or attitudinal (to borrow Darwish’s (1999, 20) terms).

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