Drawing on existing research with a holistic stance toward multimodal meaning-making, this paper takes an analytic approach to integrating eye-tracking data to study the perception and use of multimodality by teachers and learners. To illustrate this approach, we analyse two webconference tutoring sessions from a telecollaborative project involving pre-service teachers and learners of Mandarin Chinese. The tutoring sessions were recorded and transcribed multimodally, and our analysis of two types of conversational side sequences shows that the integration of eye-tracking data into an ecological approach provides richer results. Specifically, our proposed approach provided a window on the participants’ cognitive management of graphic and visual affordances during interaction and uncovered episodes of joint attention.

Owing to the anytime-anywhere-anyhow nature of mobile learning, together with the ubiquity of affordably priced mobile phones, learning has become a mobigital practice, as termed by Şad and Göktaş (2014). Consequently, language teaching/learning is gradually shifting from computer-assisted language learning to mobile-assisted language learning (MALL). In response, the current study examined the impact of MALL training on preservice and in-service EFL teachers’ perceptions and use of mobile technology (MT). For this purpose, two groups of preservice (N = 33) and in-service (N = 31) EFL teachers were randomly selected and exposed to MALL training. The pretest-posttest experimental mixed-methods design was used as a framework for collecting and analyzing both quantitative and qualitative data (using closed- and open-ended-question surveys). Quantitative results revealed that both preservice and in-service teachers had similar perceptions of MT before and after training. The only exception is that, after training, in-service teachers were more interested in MT than preservice teachers. However, both groups demonstrated an overall (and subfactor) improvement in their perceptions after MT training, except for their perceived ease of use. In-service teachers’ use also improved after training and, due to the yielded positive correlation, their perceptions were a significant predictor of use. Qualitative findings showed that in-service teachers used MT more in listening and speaking (for synchronous communication) than in reading and writing, selecting social media and translation apps as the least useful ones. Moreover, they regarded technical and digital literacy problems as the ones most challenging to the use of MT.

Participation in online courses has become essential for training language professionals in under-resourced contexts with skills in computer-assisted language learning (CALL) (Godwin-Jones, 2014). Most online CALL courses use asynchronous computer-mediated communication (ACMC) to facilitate meaningful learning for participants. Although participants’ sustained engagement with ACMC is the target, global realities of participants interfere with their participation levels. This article investigates participants’ engagement profiles in asynchronous online discussions in an 8-week CALL-based global online course developed and implemented by a team at Iowa State University. Using a case study approach, nine focal participants’ engagement profiles have been analyzed in terms of identifying patterns of engagement in the discussion posts and their relation to the types of discussion prompts. Then, social network analysis (SNA) and thematic analysis were employed to investigate patterns of interaction among the participants in the replies. The results indicated that engagement patterns observed in discussion posts overall aligned with the primary goals of prompt types. SNA further identified two participants as social mediators to connect participants with each other. These findings are significant in that they suggest the effectiveness of using ACMC to promote co-construction of knowledge for a global audience. This article also provides implications regarding the design of discussion prompts to help maximize participant engagement with course content.

This study aims to synthesize research trends of blended language learning studies over the past two decades, from 2000 to 2019. Data were collected from the Web of Science, and a total of 60 SSCI-indexed journal articles were retrieved for bibliometric synthesis. Drawing on the revised technology-based learning model, participants, learning strategies, research methods, research foci, adopted technologies, and application effectiveness, advantages, and challenges were addressed. The findings demonstrated that publications were increasing rapidly, and that most articles were published in computer-assisted language learning, educational technology, and applied linguistic journals. The most common target language was English as a foreign language, and the most common learners were college students. In most studies, technologies were mainly used for the purposes of practice or exercises. Mixed, quantitative, and qualitative methods were frequently adopted, with a particular eye on the experiment design, questionnaires, and other specific methods in the second decade. Productive language skills, along with autonomy, satisfaction, and motivation, were major research foci. Language management systems and computer and web-based applications were frequently adopted technologies. Findings of application effectiveness, advantages, and challenges were summarized.

With the growth of chatbots, concerns about implementing artificial intelligence (AI) chatbots in educational settings have consistently arisen, especially for the purpose of language learning. This study introduced a task-based voice chatbot called “Ellie”, newly developed by the researchers, and examined the appropriateness of its task design and performance as an English conversation partner and students’ perceptions on using it in EFL class. Korean EFL learners (N = 314) aged 10–15 years performed three speaking tasks with Ellie in their school classroom. The participants took 9.63 turns per session on average using the first 1,000-word band, indicating that the chatbot highly encouraged students to engage in conversation, which rarely occurs in general EFL classes in Korea. The high task success rates (88.3%) showed the design appropriateness of both L2 tasks and operational intents in terms of users’ successful understanding and completeness of the given chatbot tasks. The participants’ responses to the survey not only supported the positive potential of the chatbot in EFL settings but also revealed limitations to be resolved. Future suggestions for advancing and implementing AI chatbots in EFL classrooms are discussed.

This article focuses on designing and evaluating conversation practice in a second language (L2) with a robot that employs human spoken and non-verbal interaction strategies. Based on an analysis of previous work and semi-structured interviews with L2 learners and teachers, recommendations for robot-led conversation practice for adult learners at intermediate level are first defined, focused on language learning, on the social context, on the conversational structure and on verbal and visual aspects of the robot moderation. Guided by these recommendations, an experiment is set up, in which 12 pairs of L2 learners of Swedish interact with a robot in short social conversations. These robot–learner interactions are evaluated through post-session interviews with the learners, teachers’ ratings of the robot’s behaviour and analyses of the video-recorded conversations, resulting in a set of guidelines for robot-led conversation practice: (1) societal and personal topics increase the practice’s meaningfulness for learners; (2) strategies and methods for providing corrective feedback during conversation practice need to be explored further; (3) learners should be encouraged to support each other if the robot has difficulties adapting to their linguistic level; (4) the robot should establish a social relationship by contributing with its own story, remembering the participants’ input, and making use of non-verbal communication signals; and (5) improvements are required regarding naturalness and intelligibility of text-to-speech synthesis, in particular its speed, if it is to be used for conversations with L2 learners.