کتایون اسکویی

Thanks to the significant achievements in Artificial Intelligence (AI), Machine Translation (MT), in general, and Google Translate (GT), in particular, have been extensively used in all facets of life, including language learning. However, faced with a plethora of research evidence on GT’s educational contributions, erroneous translations create disparity regarding its use in language learning. To address this lacuna, the present study systematically reviewed 10 databases, namely, Web of Science, Scopus, ERIC, ScienceDirect, Taylor & Francis Online, Wiley Online Library, SAGE Journals, Springer Link, Springer Open, and DOAJ. Additionally, it hand searched the reference lists of 44 studies selected to be included in the synthesis from database search along with references cited in three previous systematic reviews on similar topics to capture a comprehensive view of the literature related to the use of GT in language learning between 2010-2021. It reviewed 50 studies witnessing a rise in the number of studies in this area. Studies reported that although significant improvements in the quality of GT led to pedagogical gains and more tendency to implement it in language learning, instructors still distrust it. Accordingly, this research provides pedagogical implications and suggests avenues for future research on the use of GT in language learning.     

This quantitative study aimed to investigate Iranian EFL student teachers’ perceptions on the use of Machine Translation (MT) for foreign language learning in academic context. To this end, 107 EFL student teachers from a women-only state university in Tehran, Iran, completed a recently developed and validated questionnaire in the field. The findings revealed that most participants were familiar with digital technology including MT and its different types such as Google Translate (GT). Satisfied with MT output, the majority of the participants in the study installed MT apps on their smartphones or used its website on their computers to complete assignments or to translate from Persian to English and vice versa. However, they were neutral about whether their instructors confirmed their MT use, or whether they preferred their teachers know they use MT or not. They were also not sure whether consulting MT was against the regulations. The results showed that authorities in the field of foreign language teaching are required to take a positive stand on this emerging technology; in addition, considering the importance of training for both instructors and learners, they should hold workshops for more responsible and effective MT implementation. 

The world of foreign language education has been immensely influenced by the glory of emergent machine translation (MT) technologies including Google Translate (GT) (Knowles, 2022). Considering that end users' perceptions reflect GT practicality, ample research has been conducted regarding language learners’ perceptions on GT use. Yet, investigating Iranian student teachers' perceptions on the use of GT as an ICALL tool for language learning in higher education has been underestimated. To bridge this gap, semi-structured interviews with twelve student teachers, who were selected through purposive convenience sampling, were conducted employing qualitative constructivist grounded theory methodology. Data were analyzed based on the grounded theory data coding principles (open, axial, and selective) using the MAXQDA 2020 software. A model of GT use in language learning, entitled ‘Google Translate-Assisted Language Learning (GTALL) was proposed. The three main categories (i.e. GT familiarity and use, Perceptions, and legitimacy) along with 35 sub-categories at two levels supported our core category ‘implementation of GT in language learning’. The results demonstrated considerable pedagogical implications for educational stakeholders. For administrators, to appreciate contemporary pedagogical transformations to fulfill new generation’s needs. For professors, to improve digital literacy, welcome emergent technologies, and bring them into their learners’ service for greater educational achievements, and for language learners, to develop technological skills that guarantee wise and efficient human-machine interactions.