Machine Translation: Friend or Foe in the Language Classroom?

Abstract

Machine translation (MT) provides a seemingly accelerated alternative way to communicate in the target language (L2). A convenient service to the public, MT renders a potential disservice to language learners. In this pedagogically focused article, we show concrete and detailed examples of how language instructors can turn MT and other electronic tools such as translation memories, grammar-and spellcheckers, or mapping tools into virtual assistants to empower students to use them responsibly. Two classroom interventions, one at a large public research university on the West coast and the second one at a medium-sized public university in the Midwest, aimed to develop students' awareness of the language learning process, while introducing them to various online tools that can help them communicate better in L2 without blindly using MT. The interventions were designed for intermediate level students. The first group of students were part of an advanced composition course who were shown limitations of MT and alternative editorial tools in L2, while the second group was part of an introductory literature course in which students were introduced to reasoning maps, such as mind, concept, and argument maps, to assist them with L2 communication. The main takeaways from these interventions were the need to readjust the students' attitudes as much as the instructors' mindsets if we want to make MT an ally. Shifting focus from accuracy to comprehensibility changes the stakes in L2 communication as the production of meaning becomes an exercise in student agency and leads to the satisfaction of being able to communicate spontaneously in the target language.

AI in the Foreign Language Classroom: A Pedagogical Overview of Automated Writing Assistance Tools

“…As such, this is consistent with SLA's multilingual turn research that enables learners to work with multiple languages independently and comfortably [96,97]. Exploring the different roles of lexicogrammatical structures in different languages moves students away from traditional grammatical and lexical distinctions to usage-based models of language that emphasize patterns and collocational use of language [56,98]. Thus, examining machine-translated texts may challenge the theory that languages are regulated and based on grammatical rules [99].…”

“…Ranalli [1] Nova [35]; Conijn et al [36]; O'Neill and Russell [37]; Ghufron [38]; Huang et al [39]; John and Woll [40]; O'Neill and Russell [41]; Dale and Viethen [4] Dodigovic and Tovmasyan [42]; Zomer and Frankenberg-Garcia [43]; Dizon and Gayed [44]; Ranalli and Yamashita [3] AI-enabled machine translation O'Neill [45]; Lewis-Kraus [46]; Ellis [31]; Godwin-Jones [47]; Crossley [48]; O'Neill [45]; Fredholm [49] Godwin-Jones [50]; Hussein et al [20]; Enriquez Raiído and Saínchez-Torrón [51]; Lee [52]; Vinall and Hellmich [53]; Hellmich and Vinall [7]; Dale and Viethen [4] Urlaub and Dessein [54]; Zhang and Torres-Hostench [55]; Klekovkina and Denié-Higney [56]; Jolley and Maimone [57]; Ryu et al [58]; Vinall and Hellmich [10]; Pellet and Myers [9] Automatic text generation Ruder [59]; Dale [60]; Floridi and Chiriatti [61]; Ferrone and Zanzotto [62]; Dale [63] Dale and Viethen [4]; Dizon and Gayed [44]; Eaton et al [5]; Godwin-Jones [47]; Zhang and Li...…”

“…Vinall and Hellmich [91] believed that when comparing MT systems to the other available digital tools, the former stands out as particularly polemical. Generally, language teachers tend to forbid its use in their classes [56]. Crossley [48] argued the reasons why many language teachers discourage the use of MT in their classrooms are either they consider using it as cheating, or they fear it could lead to an end to the demand for FL instructors.…”

“…Crossley [48] argued the reasons why many language teachers discourage the use of MT in their classrooms are either they consider using it as cheating, or they fear it could lead to an end to the demand for FL instructors. The widespread notion that the way students use Google Translate for completing their assignments is just by copying and pasting without engaging with the target language is not accurate and is an overly simplistic point of view [10,56,57]. Secondlanguage learners tend to use MT to look up individual words or phrases rather than translating whole texts from their first language to the target language.…”

Native, Non-Native, or Bilingual? A Concise Assessment of ChatGPT’s Suitability for Second-Language Instruction as a Native or Non-Native Pedagogue

“…Concurrently, it is imperative to contemplate potential drawbacks in tandem. For instance, Vera and Laurence (2022) comprehensively delineate the detriments associated with machine translation, which are likely to parallel the experience in second language (L2) acquisition using ChatGPT. These disadvantages encompass: students' exploitation of the system for their scholastic tasks; apprehensions regarding machine translation's potential to overshadow traditional language pedagogy and learning in terms of proficiency augmentation; disquietudes about the insufficiency of nurturing cognitive aptitudes through machine translation utilization; and trepidations of subpar outcomes resulting from dependence on machine translation.…”