The development of artificial intelligence in recent years has promoted the use of chatbot technology in sustainable education. Many studies examined the effect of chatbots on learning outcomes. However, scant studies summarized the effectiveness of chatbots in education. The aim of the study is to investigate the effect of chatbot-assisted learning on various components and how different moderator variables influenced the effectiveness. This study, through a meta-analysis, reviewed 32 empirical studies with 2201 participants published between 2010 and 2022. The results showed that chatbot technology exerted a medium-to-high effect on overall learning outcomes regardless of moderator variables, i.e., intervention duration, chatbot roles, and learning content. In terms of learning components, chatbots could significantly improve explicit reasoning, learning achievement, knowledge retention, and learning interest despite negative findings in critical thinking, learning engagement, and motivation. Future research could expand chatbot research by including different learning components.

With the rapid development of artificial intelligence, machine translation (MT) has gained popularity in recent years. This study aims to present a systematic review of literature on MT-assisted language learning in terms of main users, theoretical frameworks, users’ attitudes, and the ways in which MT tools are integrated with language teaching and learning. To this end, relevant peer-reviewed articles (n = 26) were selected through the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P) for further analysis. The findings revealed that the main MT users were undergraduate and graduate students. Both teachers and students held mixed attitudes for different reasons. It was also found that MT integration followed four steps, i.e., introduction, demonstration, task assignment, and reflection. The procedures of MT integration could be updated and perfected by introducing other features in the future.

E-learning has gained popularity since the outbreak of COVID-19. This study aims to identify gender differences in e-learners' self-efficacy, satisfaction, motivation, attitude, and performance across the world. Through a meta-analysis and systematic review, this study concludes that there are generally no significant gender differences in e-learning outcomes except in a few countries. Females significantly outperformed males in Spain and the UK. In Austria, India, and mixed countries (Chile and Spain), females hold significantly more positive attitudes toward e-learning than males. In the USA, females present significantly higher self-efficacy than males. Future research into the gender issue in e-learning across the world may adopt cross-disciplinary research methods except for a meta-analysis.

With the rapid development of information technologies, virtual reality-assisted language learning (VRALL) has caught much attention across the world, particularly during the COVID-19 pandemic. Nevertheless, few review studies aimed to understand the influence of virtual reality (VR) on learning outcomes in terms of each language element. This literature review study selected and analyzed 23 studies from the perspective of language learning aspects, main users of VR technology, and the impact of VR on each learning aspect. The results revealed that (1) vocabulary learning and tertiary education gained the most attention in academia; (2) VR promoted pronunciation learning, listening skills, and speaking skills; (3) VR was a mixed blessing for vocabulary learning, reading skills, and writing skills. Future research could explore the solutions to improve the effectiveness of VR and highlight interdisciplinary cooperation.

As technology develops by leaps and bounds, automated writing evaluation (AWE) has caught increasing attention worldwide. This study aims to provide an overview of research literature focusing on AWE used in education through bibliometric analysis. The data of studies (N = 815) published from 2008 to 2022 were analyzed using the VOSviewer and CitNetExplorer software. The results showed that the most cited countries were USA, China, and Canada. The most cited organizations were Georgia State University, University of Delaware, and Educational Testing Service. The most co-cited authors were Graham, Crossley, and Attali. The most used keywords were feedback, automated essay scoring, and natural language processing. It was also indicated that the previous studies mainly revolved around three themes, i.e., the design and development of AWE technology, the application of AWE in education, and the effect of AWE on linguistic features. This study provided references for entry into the AWE field and identifying future research directions.