Investigating speech fluency has, for a long time, been at the core of second language (L2) studies, as fluency is believed to epitomise successful acquisition of L2, characterise effective communication, elucidate the complex process of acquisition, and predict L2 speakers' proficiency. The significance attributed to fluency in these areas explicates the research attention paid to it over the past decades. An important area of development in this regard is L2 assessment in which fluency is recognised as a key underlying construct of spoken language ability by international language tests (e.g., IELTS, TEEP, APTIS) and language benchmarks (e.g., CEFR). Many high-stakes tests of English and other languages include fluency in their rating scales, with the earliest on record tracing back to the 1930s – the College Board's English Competence Examination (1930) in America. Including fluency as a fundamental aspect of speaking ability in the rating scales, rating descriptors, and rater training materials, either as an independent criterion or combined with others (e.g., delivery), has become common practice in language testing over the past decades. What has made assessment of fluency even more appealing to researchers and test providers in recent years is the objectivity and reliability of its measurement and its compatibility with the technological developments in automated assessment of speaking. Fluency is now largely recognised as a construct that can be efficiently and reliably assessed in automated assessment of spoken language ability and used to predict proficiency (de Jong, 2018*; Ginther et al., 2010*; Kang & Johnson, 2021*; Tavakoli et al., 2023).
Decades before educators were forced to confront the disruption posed by widely accessible generative artificial intelligence (AI) tools such as ChatGPT, language learners, instructors, and researchers began dealing with its game-changing predecessor: machine translation (MT). Researchers began assessing MT systems and proposing language teaching applications for them as soon as universities and schools gained access to them in the mid-1980s (*Anderson, 1995*; Ball, 1989*; Corness, 1985; French 1991; Lewis, 1997; Richmond, 1994*). These inquiries accelerated in the early 2000s, when internet-enabled computer labs and increasingly smarter devices put free online MT services such as Babel Fish and Google Translate (GT) at students' fingertips, triggering concerns over output quality, academic dishonesty, and the short-circuiting of actual learning. In recent years, there has been a veritable explosion of research on MT's role in and impact on language teaching and learning, with many dozens of peer-reviewed articles published in the past five years alone, as documented in a handful of comprehensive literatures reviews (Gokgoz-Kurt, 2023; Jiang et al., 2024; Jolley & Maimone, 2022; Klimova et al., 2023; Lee, 2023). The present article provides a timeline of this rapidly expanding research domain.
As Kathleen Graves argues in her 2023 article, the belief that students learn best when teachers deliver a curriculum exactly as written is a common fallacy, based on an underlying assumption that ‘the institutional curriculum is the most important determinant of what happens in the classroom’ (p. 200). Graves stresses that, in reality, the institutional curriculum itself does not guarantee effective learning and that, instead, it is up to teachers to modify, adapt, or ‘enact’ the curriculum for it to make sense and work effectively in each unique context (p. 200). In our roles as academic writing instructors at a university in Japan, we are simultaneously teachers and curriculum developers. As such, we were drawn to this article and have examined how Graves’ ideas relate to our teaching beliefs and experiences. In this response article, we first discuss issues caused by an overemphasis on the institutional as well as on the enacted curricula. We then highlight the importance of building a program culture that invites open dialogue about how teachers creatively adapt a given curriculum in order to involve teachers meaningfully in course development.