How to teach from uncertainty? Translation learning outcomes in the age of automation

Abstract

Nowadays, sooner or later, every teacher finds themselves having to define or apply a set of learning outcomes, typically formulated along the lines of “By the end of the lesson/course/programme, the student will be able to…” (cf. Kelly, 2014, pp. 20–38). From that point on, these outcomes guide teaching: they determine how we teach, which materials we select, what activities we design, and how we assess. When they are well formulated, everything falls into place: we know what we aim to achieve and can verify whether it has actually been achieved. It all seems logical, doesn’t it?

So, what could have gone wrong in an economy regulated through centrally designed five-year plans? Teaching, like a country’s economy, is a complex system composed of a large number of moving parts, and no one can predict with certainty what will happen to each of them in the long term. Moreover, no complex social system can truly work without motivation—that is, without the basic premise that individuals may derive some benefit from their interactions with the system. But if the workings of these components are not properly understood, how can motivation to engage with the system be fostered? Why do learning outcomes fail? They fail when they are based on flawed assumptions and when they fail to take motivation into account. In fact, at present, many learning outcomes in the field of translation fail for both reasons.