Although use of machine translation (MT) technologies by learners may seem like a relatively new issue in foreign language (FL) education, researchers have been investigating connections between MT tools and FL teaching and learning for more than three decades, years before learners had access to free online services such as Google Translate. This literature review summarizes this rapidly expanding research domain both chronologically and thematically, identifying key concepts, insights, and findings and mapping them onto a framework inspired by questions commonly asked by both researchers and practitioners: How do learners use MT tools? What do instructors and learners think about MT? How might MT use affect language learning? How should instructors respond to MT use by learners? By summarizing and drawing connections between the assumptions, methods, and findings of key studies in these categories, this review provides a historical perspective and suggests new directions for future research.

This article reports the results of an empirical study designed to determine the degree to which college instructors of Spanish can distinguish between machine translation (MT) and non‐MT writing samples produced by second language (L2) learners of Spanish in an intermediate‐level writing course. We also investigated relationships between detection accuracy rates, instructor teaching experience, and text type (narrative or argumentative), as well as signs instructors consider indicators of both kinds of writing. Results demonstrated that instructors were able to distinguish MT from non‐MT writing with a high degree of accuracy by relying on a broad array of indicators. However, neither text type difference nor instructor experience related significantly to detection ability. These findings have practical implications for the L2 classroom with regard to instructor response to MT use and the integration of MT tools to support L2 writing development.