About

Machine translation (MT) tools, like Google Translate, are getting better. The latest iterations are faster, more efficient, and provide more accurate translations in languages with sufficient databases (Kelleher, 2019; Lewis-Kraus, 2016; Poibeau, 2017; Wu et al., 2016).

Language learners have reported wide-spread use of MT tools (Bourdais & Guichon, 2020; Clifford, Merschel, & Munné, 2013; Jolley & Maimone, 2015; O’Neill, 2019; White & Heidrich, 2013). But instructors are often reluctant to integrate MT into their classrooms, opting to ban or limit student use of MT (Briggs, 2018; Hellmich & Vinall, 2021). 

For instructors who express interest in integrating MT into their classroom practices, some pedagogical suggestions are available (e.g., Correa, 2014; Ducar & Schocket, 2018; Jiménez-Crespo, 2017; Niño, 2008).   

However, most of these pedagogical guidelines are based on reported student use—that is, how students think they use tools. Few studies have looked at how language learners actually use MT tools (e.g., Garcia & Pena, 2011; Tight, 2017). 

Our study was based on the following idea: in order to develop effective strategies for addressing MT in the language learning classroom, we need to know how learners are actually using MT tools.