In this qualitative systematic meta-synthesis study, 57 studies from the international literature published between 2010 and 2024 on the use of voice-based artificially intelligent chatbots in English language learning were analyzed. The present study aimed to explore the most recent studies on this topic by investigating the theoretical frameworks, methodological and technological properties, user reports of chatbot usage experience, and pedagogical implementations. It sought to identify research and implementation trends for voice-based chatbots via qualitative data analysis methods. Based on the reviewed studies, this paper presents data-based pedagogical implications that align with the latest voice-based AI chatbot research trends.

This systematic review maps the trends of computer-assisted pronunciation training (CAPT) research based on the pedagogy of second language (L2) pronunciation instruction and assessment. The review was limited to empirical studies investigating the effects of CAPT on healthy L2 learners’ pronunciation. Thirty peer-reviewed journal articles published between 1999 and 2022 were selected based on specific inclusion and exclusion criteria. Data were collected about the studies’ contexts, participants, experimental designs, CAPT systems, pronunciation training scopes and approaches, pronunciation assessment practices, and learning measures. Using a pedagogically informed codebook, the pronunciation training and assessment practices were classified and evaluated based on established L2 pronunciation teaching guidelines. The findings indicated that most of the studies focused on the pronunciation training of adult English learners with an emphasis on the production of segmental features (i.e. vowels and consonants) rather than suprasegmental features (i.e. stress, intonation, and rhythm). Despite the innovation promised by CAPT technology, pronunciation practice in the studies reviewed was characterized by the predominant use of drilling through listen-and-repeat and read-aloud activities. As for assessment, most CAPT studies relied on human listeners to measure the accurate production of discrete pronunciation features (i.e. segmental and suprasegmental accuracy). Meanwhile, few studies employed global pronunciation learning measures such as intelligibility and comprehensibility. Recommendations for future research are provided based on the discussion of these results.

This study explored how collaborative writing, an often-used instructional strategy in second language (L2) learning, intersects with large-group dynamics, and investigated their potential impact on the quality of writing outcomes in an online distance learning course. Using a mixed-methods approach, the research scrutinized intra-group interaction processes in two large groups undertaking a computer-assisted language learning writing assignment and evaluated the impact of these interaction processes on their writing products. Data from discussions in both a public online forum and a private social communication platform (WeChat) were collected, systematically coded, and analysed quantitatively and qualitatively based on language functions. Data collection also included an assessment of the written products and follow-up group interviews. The findings indicate distinct interaction patterns between high-performing and low-performing groups, characterised by an expert/participant pattern and a dominant/passive pattern, respectively. Additionally, insights from the interviews shed light on these interaction patterns and the potential impact on student learning outcomes. The study suggests practical implications, highlighting the importance of task design in promoting high levels of collaborative knowledge construction to enhance students’ writing skills and L2 language learning in large-group settings.

The research field of online informal English learning has revealed associations of various informal digital English activities and second language vocabulary development. However, most of these studies have regarded digital resources as uniform entities when investigating their potential for vocabulary development and have failed to consider learners’ idiosyncratic interaction with the resources driven by self-defined purposes of use. Informed by the uses and gratifications theory, this study explored how three purposes of extramural digital experience (entertainment, socialization and information) relate to vocabulary knowledge, based on the survey responses from 322 undergraduate Chinese EFL learners and their receptive vocabulary knowledge. PLS-SEM analysis uncovered differential associations of the three media use purposes with receptive vocabulary knowledge. The study also revealed that the associations between the purposes of informal digital activities and vocabulary knowledge differed depending on whether the vocabulary was high frequency or low frequency. Additionally, it was found that the strategic use of digital resources, in terms of cognitive attention to and processing of lexical information that are facilitative of vocabulary learning during and/or after the interaction, played a significant moderating role in the relationship between digital activities for information purposes and receptive knowledge of high-frequency vocabulary. The findings highlight the importance of considering media use purposes in future research and pedagogical practices.

This study investigated how multimedia glossing affects incidental vocabulary learning from a listening task on mobile devices. A total of 118 English language learners were asked to listen to a story with 25 glossed target words on their mobile phones. In order to examine the effects of different types of glossing, participants were divided into four groups with access to four glosses during their listening: L1 textual, L2 textual, L1 textual and pictorial, and L2 textual and pictorial. Two vocabulary tests (i.e. definition-supply test and meaning-recognition test) were administrated immediately after treatment and two weeks later to measure vocabulary gain for target words. The results indicated that participants who had access to L1 textual and pictorial glosses had significantly higher vocabulary gains than other conditions, especially in meaning-recall word knowledge. Finally, a detailed discussion of the findings was provided to explain the results based on the theoretical framework of the study.

The aim of this study was to contribute to the field of computer-assisted language learning (CALL) by investigating the individualization of intentional vocabulary learning. A total of 118 Japanese-speaking university students studied 20 low-frequency English words using flashcard software over two learning sessions. The participants practiced retrieval of vocabulary under different learning schedules, with short or long time intervals between encounters of the same word in each learning session: Short–Short, Short–Long, Long–Short, and Long–Long. Two individual difference measures – learning efficiency and language aptitude – were examined as predictors of long-term second language (L2) vocabulary retention. Learning efficiency was operationalized as the number of trials needed to reach a learning criterion in each session, whereas a component of aptitude (rote memory ability) was measured by a subtest of Language Aptitude Battery for the Japanese. Multiple regression and dominance analyses were conducted to evaluate the relative importance of learning efficiency and language aptitude in predicting delayed vocabulary posttest scores. The results revealed that learning efficiency in the second learning session was the strongest predictor of vocabulary retention. Language aptitude, however, did not significantly predict vocabulary retention. Moreover, the predictive power of learning efficiency increased when the data were analyzed within each learning schedule, underscoring the need to assess learners’ abilities under specific learning conditions for optimizing their computer-assisted learning performance. These findings not only inform the development of more effective, individualized CALL systems for L2 acquisition but also emphasize the importance of gauging individuals’ abilities such as learning efficiency in a more flexible, context-sensitive manner.

This study used a mixed-methods approach to evaluate the efficacy of mobile-assisted language learning (MALL) in teaching English phrasal verbs (PVs) in a 12-week study. The participants were 122 EFL college students divided equally into an experimental and a control group. The experimental group was assigned PV learning on an iOS-based application (henceforth referred to as “app”) for eight weeks; the control group learned the same PVs through paper-based material. Pre-tests, post-tests, and weekly class tests were conducted, and one-way ANOVAs were performed to evaluate the differences between the two groups using their pre-test and post-test scores, with repeated measures ANOVA used to analyse the learning gains in weekly tests. The results revealed that the experimental group significantly outperformed the control group in the post-test (F = 6.09, p = .015, Cohen’s d = 0.45) and weekly tests (F = 31.68, p = .000). A Likert-scale-based e-questionnaire consisting of 19 items was administered to the experimental group to obtain their perceptions of the app’s usefulness for learning English PVs. The overall results suggest that MALL, particularly with this specific mobile app, may enhance students’ ability to understand and use English PVs, a key aspect of vocabulary skills. The findings can be used to encourage instructors to employ MALL for teaching the English lexicon for better learning outcomes in EFL settings.

This study creates a virtual space for language learning using a user-customizable metaverse platform and explores its potential for EFL learning. To this end, a virtual learning space, grounded in constructivist learning principles – contextualized learning, active learning, and collaborative learning – was created on a 2D metaverse platform. The metaverse was designed as a simulated deserted island for enjoyable and playful learning, allowing the students to actively explore, discover, and interact as they look for clues to escape the island. For educational application, 29 Korean middle school students participated in a two-hour activity. Data included screen recordings of student activities, student surveys, and interviews with the students and teachers. The findings showed that, as an EFL learning space of playful constructivism, the metaverse had great potential to embed contextualized learning and served as a medium for active learning that positively affected student interest and motivation. The results confirmed that the team-based approach combined with a game-like metaverse fostered student collaboration. Overall, the study showcased how language instructors can make use of a customizable metaverse for L2 learning and how a virtual space may serve as an arena for learner-centered instruction.

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.