At present, emerging technologies, such as machine learning, deep learning, or various forms of artificial intelligence are penetrating different fields of education, including foreign language education (FLE). Moreover, the current young generation was born into the technological environment, and they perceive technologies as being an indispensable part of their everyday life. However, they mainly use technologies in their informal learning, but there is not much research into emerging technologies in FLE, namely in teaching and learning English as an applied language. Therefore, the purpose of this systematic review is to identify, bring together, compare and analyze all of the technologies that are currently efficiently employed in foreign language teaching and learning, and based on the findings of the detected experimental studies, we provide specific pedagogical implications on how to use these technologies in the acquisition of English as an applied language at the university level. The methodology followed the PRISMA guidelines for systematic reviews and meta-analyses. The results of the detected experimental studies revealed that there was a serious lack of the latest technologies, such as chatbots or virtual reality (VR) devices, that are being empirically employed in a foreign language (FL) education. Moreover, mobile apps are merely focused on the development of FL vocabulary. The findings also indicate that although the FL teachers might theoretically know about these latest technological devices, such as neural machine translation, they do not know how to practically implement them in their teaching process. Therefore, this research suggests that teachers must be trained and pedagogically guided on how to purposefully implement them in their FL classes to support traditional instruction in order to identify what skills or language structures could be developed through their use. In addition, it is also claimed that more experimental studies are needed to clearly the evidence and its usefulness in teaching a foreign language as an applied language.

With the advent of new emerging technologies, machine translation, especially natural machine translation (NMT) and its tools, is being increasingly applied in second language (L2) acquisition. The aim of this study is to investigate the usefulness of machine translation, specifically DeepL Translator, in the second language acquisition process, since it has a great potential to transform foreign language education. The present empirical pilot study describes an experiment dealing with the use of neural machine translation in the process of formal writing (i.e., writing a summary) in a foreign language. Altogether 16 university students learning English as an applied foreign language with C1 level of English proficiency participated in the experiment. The results show differences between pre-test and post-test, and a significant improvement in students' language skills due to the use of DeepL Translator. The questionnaire survey, among other things, reveals positive perceptions of this tool and awareness of improved language skills by the research participants. The findings indicate that purposefully guided working with a NMT tool can contribute to the perceived usefulness of its use in learning English as an applied foreign language.

Mobile devices and applications, which have become an integral part of our lives, are gradually used for different purposes, including learning languages in EFL classrooms. Since vocabulary plays an important role in the process of foreign language learning, the aim of this study was to explore the use of the vocabulary mobile learning application and its usefulness in blended English learning. Quantitative and qualitative approach to research was used, since the integration of both approaches created the possibility to solve complex research problem. The case study was based on the use of the developed mobile application called Angličtina Today the content of which corresponded to the language needs of the target group of students. The quantitative approach used a method of quasi-experiment aiming to achieve the pre-tests and post-test results of the students from the experimental and control groups. The results showed that the students facing blended learning, including mobile application in the process of language learning, achieved better results than the students exposed to the traditional, face-to-face education. In addition, the results revealed students’ overall satisfaction with the application. The main reasons for their satisfaction were improved vocabulary knowledge, ease of use, and enhanced motivation. Based on these findings from the current study, it can be argued that the vocabulary mobile learning application proved to be useful in the process of blended English language learning.

This paper explores the perceptions of Gen Z students at different levels of English proficiency regarding the use of technology, particularly Neural Machine Translation (NMT) and ChatGPT, in second language acquisition. The research aims to understand how these technologies influence language learning and identify how these tools are used across varying proficiency levels. The significance of the study lies in its potential to inform educators and highlight the role of using technologies in language learning. Based on data collected from a survey of 151 students (ranging from A2 to C2 proficiency levels), the findings indicate that students across all proficiency levels actively engage with NMT and ChatGPT. Across all proficiency levels, NMT and ChatGPT are used primarily for word translation. However, higher proficiency students use ChatGPT for complex tasks (such as mistake correction or summary writing). Moreover, the study emphasizes the positive attitudes of Gen Z learners toward technology as a flexible and valuable educational resource. The motivation to use technology stems from the desire to learn new vocabulary, comprehend English content, and enjoy flexible learning. Therefore, the study recommends that educators adapt teaching strategies to include these technologies, considering the different proficiency levels of students. Future research should focus on the long-term impacts of technology use on language acquisition.