Speaking is often challenging for language learners to develop due to factors such as anxiety and limited practice opportunities. Dialogue-based computer-assisted language learning (CALL) systems have the potential to address these challenges. While there is evidence of their usefulness in second language (L2) learning, the effectiveness of these systems on speaking development remains unclear. The present meta-analysis attempts to provide a comprehensive overview of the effect of dialogue-based CALL in facilitating L2 speaking development. After an extensive literature search, we identified 16 studies encompassing 89 effect sizes. Through a three-level meta-analysis, we calculated the overall effect size and investigated the potential moderating effect of 13 variables spanning study context, study design and treatment, and measures. Results indicated a moderate overall effect size (g = .61) of dialogue systems on L2 learners’ speaking development. Notably, three moderators were found to have significant effects: type of system, system meaning constraint, and system modality. No significant moderating effect was identified for education stage, L2 proficiency, learning location, corrective feedback, length of intervention, type of interaction, measure, and key assessment component. These findings suggest directions for future research, including the role of corrective feedback in dialogue-based CALL, the effectiveness of such systems across proficiency levels, and their potential in diverse learning contexts with the integration of generative artificial intelligence.

Limited research has examined the quality of language MOOCs and no existing instrument has been developed to gauge learners’ evaluation of LMOOC quality. This study develops an LMOOC Quality Evaluation Scale (LQES) and validates it in the Chinese context, which has the largest number of LMOOC learners in the world. The data were collected from 2,315 LMOOC learners in China using a mixed-method approach. Development and validation of the scale involved (1) generation of an initial item pool based on a semi-structured interview and literature review, (2) refinement of scale items through consultation of LMOOC experts and a focus group interview, (3) exploration of the factor structure of the scale using exploratory factor analysis, and (4) validation and confirmation of the final scale using confirmatory factor analysis. A four-factor model, comprising Instructional Design, L2 Teachers’ Competence, Teaching Implementation, and Technical Support, emerged and was validated. The 26-item LQES provides an original and comprehensive framework for understanding the complexities of LMOOC quality. This study highlights the critical factors underpinning the evaluation of LMOOC quality and paves the way for further refining of the instrument in future research.

This article explores how online language learners encounter foreign language speaking anxiety (FLSA), what mitigating strategies they apply to manage synchronous online tutorials, and what their asynchronous speaking practices are. In a large-scale mixed methods study, we gathered survey data from 307 language learners at a UK online and distance learning university and conducted in-depth group interviews with 10 students focusing on their FLSA experience and perceptions regarding synchronous and asynchronous speaking activities. The results reveal that the triggers of FLSA and the mitigating strategies learners apply partly overlap with those in the face-to-face context but are partly specific to the online environment (e.g. breakout rooms, vicarious learning). The use of technology can be anxiety-inducing (e.g. cameras) as well as supportive (e.g. online translation tools and dictionaries). Novel findings of the study are that avoidance strategies are more nuanced in this context, ranging from complete avoidance of tutorials to full engagement via the chat, and that the use of breakout rooms magnifies learners’ emotions and is one of the main triggers of FLSA. This might be helpful for practitioners – also beyond language courses – in scaffolding and optimising their small group activities online.

English as a foreign language (EFL) students are increasingly learning English in extramural digital settings (informal digital learning of English; IDLE). Previous research has investigated the antecedents of IDLE engagement, focusing on basic psychological needs (BPNs) in classroom settings. However, little attention has been given to the role of BPNs in digital settings, where digital-native EFL students often fulfil their psychological needs. This study explores the relationship between two core BPNs – competence and relatedness – in both classroom and digital settings and IDLE engagement among 226 Kazakhstani university EFL students. Hierarchical multiple regression analyses indicate that, in the classroom, students who perceive themselves as more competent are more likely to engage in receptive and productive IDLE. Also, a higher sense of in-class relatedness strengthens the positive relationship between in-class competence and productive IDLE. In the digital settings, students who perceive themselves as more competent are more likely to engage in receptive IDLE, while competence alone does not directly lead to productive IDLE. A higher sense of relatedness positively moderates the links, amplifying the connection between competence and engagement in both receptive and productive IDLE. These findings suggest that educators can enhance EFL students’ IDLE engagement by designing and recommending activities that foster competence and a sense of community in both classroom and digital settings.

This study explored the effects of interacting with ChatGPT 4.0 on L2 learners’ motivation to write English argumentative essays. Conducted at a public university in a non-English-speaking country, the study had an experimental and mixed-methods design. It utilized both quantitative and qualitative data analyses to inform the development of effective AI-enhanced tailored interventions for teaching L2 essay writing. Overall, the results revealed that interacting with ChatGPT 4.0 had a positive lasting effect on learners’ motivation to write argumentative essays in English. However, a decline in their motivation at the delayed post-intervention stage suggested the need to maintain a balance between utilizing ChatGPT as a writing support tool and enhancing their independent writing capabilities. Learners attributed the increase in their motivation to several factors, including their perceived improvement in essay writing skills, the supportive learning environment created by ChatGPT as a tutor, positive interactions with it, and the development of meta-cognitive awareness by addressing their specific writing issues. The study highlights the potential of AI-based tools in enhancing L2 learners’ motivation in English classrooms.

The emphasis in L2 learning has mainly focused on individual writers and monomodal academic genres (e.g. narration, argumentation), neglecting the potential of collaborative composing and the use of digital genres that introduce additional semiotic sources, for fear of having to deal with “a messy transition to digital multimodal communication” (Lotherington, 2021: 220). Yet, because Web 2.0 technological upgrades have enabled interactivity, literacy has morphed from discretely reading and writing a static page to dynamically reading and writing a multimodal one, which underpins collaborative authorship and (local and global) audience awareness. Considering the inclusion of working collaboratively with multimodal tasks in the L2 classroom, the question of how to help students effectively incorporate multimodal with academic monomodal texts remains unanswered. In response to this challenge, this study examines the design and implementation of an online task to foster multiliteracies. Thirty-seven international students of diverse disciplines (e.g. economics, engineering, history), enrolled in a Spanish as a second language course, worked collaboratively to create multimodal texts based on previously created monomodal texts. Informed by a student questionnaire and a teacher focus group, we analyzed both students’ and teachers’ perceptions to ascertain the effectiveness of the intervention and the possibilities these kinds of tasks bring to the foreign language classroom. Both sets of participants reported positive results concerning linguistic advancement, motivation, and multiliteracies development. Pedagogical recommendations related to the inclusion of this pedagogical practice are provided.

While previous studies in computer-assisted language learning have extensively explored sociolinguistic factors, such as cultural competence, important psycholinguistic factors such as online L2 motivational self-system, L2 grit, and online self-regulation in relation to virtual exchange (VE) have remained widely unexplored. To address this gap, a study was conducted with 92 Spanish English as a foreign language learners who exchanged language and culture with Cypriot and Irish students and responded to questionnaires adapted for the study context, as part of the SOCIEMOVE (Socioemotional Skills Through Virtual Exchange) Project. The partial least squares structural equation modeling approach showed that language learners who set positive personal goals for the future and evaluate their current learning progress in VE can regulate their learning in it. Interestingly, the sign of authenticity gap was found in the study context, since learners’ motivation to learn in VE was higher compared to their previous language learning contexts, resulting in more effort and consistency of interest in setting their goals, evaluating their progress, and asking for help from others. Furthermore, learners’ L2 grit moderated and mediated the correlation between learners’ online motivation and online self-regulation, indicating that VE success requires long-term perseverance of effort and consistency of interest. Accordingly, a new conceptual framework for VE was developed. In addition, one of the main implications is that teachers who employ VE should focus more on learners’ current needs and the goals they wish to achieve when exchanging information rather than only focusing on their accomplishments based on the course syllabus.

The advent of generative artificial intelligence (AI) models holds potential for aiding teachers in the generation of pedagogical materials. However, numerous knowledge gaps concerning the behavior of these models obfuscate the generation of research-informed guidance for their effective usage. Here, we assess trends in prompt specificity, variability, and weaknesses in foreign language teacher lesson plans generated by zero-shot prompting in ChatGPT. Iterating a series of prompts that increased in complexity, we found that output lesson plans were generally high quality, though additional context and specificity to a prompt did not guarantee a concomitant increase in quality. Additionally, we observed extreme cases of variability in outputs generated by the same prompt. In many cases, this variability reflected a conflict between outdated (e.g. reciting scripted dialogues) and more current research-based pedagogical practices (e.g. a focus on communication). These results suggest that the training of generative AI models on classic texts concerning pedagogical practices may bias generated content toward teaching practices that have been long refuted by research. Collectively, our results offer immediate translational implications for practicing and training foreign language teachers on the use of AI tools. More broadly, these findings highlight trends in generative AI output that have implications for the development of pedagogical materials across a diversity of content areas.

Informal digital learning of English (IDLE) is a promising way of learning English that has received growing attention in recent years. It has positive effects on English as a foreign language (EFL) learners and also creates valuable opportunities for EFL teachers to improve their teaching skills. However, there has been a lack of a valid and reliable scale to measure IDLE among teachers in EFL contexts. To address this lacuna, this study aims to develop and validate a scale to measure IDLE for EFL teachers in Iran. For this purpose, a nine-step rigorous validation procedure was undertaken: administering pilot interviews; creating the first item pool; running expert judgment; running interviews and think-aloud protocol; running the pilot study; performing exploratory factor analysis, Cronbach’s alpha, and confirmatory factor analysis; creating the second item pool; conducting expert reviews; and performing translation and translation quality check. Findings yielded a 41-item scale with six subscales: IDLE-enhanced benefits (12 items), IDLE practice (five items), support from others (nine items), authentic L2 experience (three items), resources and cognition (four items), and frequency and device (eight items). The scale demonstrated satisfactory psychometric properties such that it can be used for research and educational purposes in future.

This study explores the integration of generative artificial intelligence (GenAI) in informal digital learning of English (IDLE) practices, focusing on its potential to enhance language learning outcomes and addressing the technological challenges language teachers face in utilising AI-based tools to facilitate second language acquisition. Based on the research context of IDLE and holistic learning ecology and drawing on the theoretical frameworks of technological pedagogical and content knowledge and social cognitive theory, we performed a mixed-methods investigation with an empirical experiment to assess the effectiveness of GenAI followed by semi-structured interviews. The results suggest that the GenAI-mediated IDLE practices effectively improve college students’ oral proficiency in English from both technological and humanistic perspectives. However, results also indicate that the GenAI conversational partner alone is not adequate to provoke continuous extramural GenAI-mediated IDLE practices. We discuss the theoretical and pragmatic significance of GenAI-mediated IDLE in educational equity and reformation.