The present study aims to explore how pre- and in-service language teachers incorporate the cutting-edge technology of immersive virtual reality (iVR) into their teaching practice. Specifically, the study examined how their different knowledge levels and teaching experiences influenced their integration of technology by analyzing their performance-based tasks in microteaching in an iVR environment. This particular technology was selected for the study because it was expected to bring multiple pedagogical benefits to future foreign language learning classrooms, such as contextualized learning, increased learner motivation and interest, and enhanced interaction and communicative skill training. The study employed in-depth qualitative analysis. Data (lesson plans, screen recordings of microteaching episodes, and reflection papers) were collected from one preservice teacher training course and one in-service teacher training course at a Korean university. The study found a large gap between pre- and in-service teacher performance and identified the sources of the differences based on qualitative data analysis. The results showed that not only teachers’ technological knowledge but also their pedagogical knowledge of the use of technology and confidence in teaching affected technology integration. As technology integration has become more important in language education, the current study provided insight into how to better prepare teachers for future learners.

Virtual exchange (VE) projects in pre-service language teacher education are increasingly being recognized as an innovative practice due to their affordances for providing teacher learning opportunities in technology-rich environments. This study aims to report these opportunities based on results from a VE project consisting of diverse teacher education activities, including lectures, webinars, asynchronous tasks, and synchronous video-mediated interactions. This project provides a medium for pre-service teachers to collaboratively design a lesson to be implemented in hybrid language learning environments. We specifically deal with the video-mediated interactions of the transnational groups of pre-service language teachers using multimodal conversation analysis (CA) as the research methodology and investigate VE phases to explore how their interactions become consequential for the final pedagogical design. The findings show that the pre-service teachers retrospectively orient to shared practices in the earlier phases of the VE project, and the deployment of retrospective orientation as an interactional resource creates interactional space for collaborative decision-making related to their pedagogical designs. We argue that tracking the video-mediated pedagogical interactions of the pre-service teachers using CA is a methodological innovation that allows researchers to collect interactional evidence for the emergent teacher learning opportunities. The findings bring new insights to the role of the technology-mediated settings (e.g. VEs and telecollaboration) in language learning, teaching, and teacher education and in bridging different cultures, curricula, and physical spaces.

High-immersion virtual reality (HiVR) attracts increasing attention among language learning researchers because of its potential to enhance language learning. Prior studies focused mainly on HiVR and linguistic knowledge acquisition, and little is known about HiVR and emotions in language learning. Foreign language speaking anxiety (FLSA) is a common emotion that inhibits language learning and use, so it is important to explore approaches to alleviate it. This study investigated the potential use of HiVR for coping with FLSA in which 140 Chinese EFL learners were randomly assigned to four groups (35 students each) with a different combination of learning environments (HiVR or classroom) and learning principles (situated learning or teacher-centred learning). Students’ pre- and post-test of FLSA levels within and among four groups were compared via t-tests and ANOVA. Participants’ descriptions of FLSA change and perceptions of the effects of HiVR on FLSA were integrated with quantitative results for analysis. The integration of analysis showed that although most students perceived HiVR as a useful tool for alleviating FLSA, it is difficult for them to apply the reduced anxiety experienced in HiVR to real-life situations. The statistical results also showed that HiVR did not influence students’ real-life FLSA significantly. Most participants reported that HiVR offered them an authentic environment and enjoyable learning activities, which engaged them in learning, but the use of avatars in HiVR sometimes created an obstacle to communication. Implications for using HiVR technology to enhance foreign language learning are provided.

Data-driven learning (DDL) form-focused tasks are a relatively new concept. These tasks involve using concordance lines to teach language in a way that integrates discovery learning, authentic language use, consciousness-raising, and the communicative use of language. Given their novelty, there haven’t been many studies on how they impact learners’ engagement. Therefore, this study sought to study whether DDL form-focused tasks influence English as a foreign language (EFL) learners’ task engagement. A total of 114 Iranian EFL learners were randomly divided between comparison and intervention groups in a study that utilized an experimental (comparison group, pretest, and post-test) design within a sequential explanatory mixed-methods design. The comparison group completed 10 non-DDL form-focused tasks, whereas the intervention group completed 10 DDL form-focused tasks. The results of t-tests and repeated-measures ANOVA indicated that incorporating DDL form-focused tasks into English classes enhanced EFL learners’ task engagement in the short run. However, the impact of DDL form-focused tasks on EFL learners’ task engagement was not durable. Moreover, analyzing semi-structured interview data suggested that using DDL-enhanced tasks with a form-focused approach increases EFL learners’ task engagement by triggering their curiosity, improving their autonomy, enhancing their concentration and interest, and facilitating their discovery learning. The present study lends more credence to the application of such tasks. The paper ends with implications for English language teaching and materials development.

Language MOOC research has experienced a notable evolution from practice to conceptuality since its emergence as a subdiscipline of computer-assisted language learning. The versatility of the MOOC format for language learning has led to experimental designs that combine linguistic acquisition with other educational activities. This has been considered to be conducive to new ways of understanding how language learning occurs in LMOOCs, although there is no solid classification of LMOOCs subtypes to date based on course design. This study aimed to contribute to the conceptualisation of the field by creating a taxonomy for existing LMOOCs. Grounded theory strategies were adopted, so evidence was systematically collected to develop conceptual categories based on a thorough analysis process of the syllabus and short description of 432 courses. As a result, six LMOOC modalities emerged from the analysis: general language learning LMOOCs, LMOOCs for academic purposes, LMOOCs for professional purposes, LMOOCs focused on a specific language skill development, cultural-oriented LMOOCs, and meta-language learning LMOOCs. This study means a significant contribution to the LMOOC research field inasmuch as it is one of the first empirical-based attempts to broaden the definition of LMOOC.

Concerns over the quality of teaching in massive open online courses devoted to language learning (LMOOCs) have prompted extensive research on learning behavior in such courses. The purpose of this study is to gain a better understanding of autonomous learning check-ins – that is, individuals sharing their own learning records and/or other information about their learning-related experience – a novel behavior that has not been studied in previous LMOOC research. Using learning analytics, we found that just 6.2% (n = 699) of a sample of 11,293 learners autonomously engaged in check-in behavior, and that the content of these learners’ check-ins varied considerably according to their contexts and the language skills they were seeking to acquire. We further found (1) a positive association between check-in behavior and LMOOC completion; (2) that students who chose to check in earned relatively low grades on unit quizzes, especially in their early stage of learning, but outperformed the non-check-in group significantly in final exam scores; and (3) that those who checked in engaged with a significantly wider array of in-LMOOC learning components than those who did not, and thus accessed a wider system of language-learning experiences. Taken together, these results confirm that check-in behavior can aid the process of learning in an LMOOC and further highlight this behavior’s wider potential to aid self-directed autonomous online learning.

This study offers a comprehensive bibliometric analysis of artificial intelligence (AI) applications in the field of second language (L2) teaching and applied linguistics, spanning from the early developments in 1995 to 2022. It aims to uncover current trends, prominent themes, and influential authors, documents, and sources. A total of 185 relevant articles published in Social Sciences Citation Index (SSCI) indexed journals were analyzed using the VOSviewer bibliometric software tool. Our investigation reveals a highly multidisciplinary and interconnected field, with four main clusters identified: AI, natural language processing (NLP), robot-assisted language learning, and chatbots. Notable themes include the increasing use of intelligent tutoring systems, the importance of syntactic complexity and vocabulary in L2 learning, and the exploration of robots and gamification in language education. The study also highlights the potential of NLP and AI technologies to enhance personalized feedback and instruction for language learners. The findings emphasize the growing interest in AI applications in L2 teaching and applied linguistics, as well as the need for continued research to advance the field and improve language instruction and assessment. By providing a quantitative and rigorous overview of the literature, this study contributes valuable insights into the current state of research in AI-assisted L2 teaching and applied linguistics and identifies key areas for future exploration and development.