This study conducts meta‐analytical estimations based on 70 empirical studies regarding inconsistent effect sizes of augmented reality in interactive learning environments. It finds that compared with traditional tools, augmented reality in interactive learning environments significantly enhances overall learning effectiveness (g = 0.717, 95% confidence interval [CI] = 0.606–0.827) at the 0.05 level. The moderating analysis finds that augmented reality in interactive learning environments significantly enhances (1) students' acceptance of technological systems and attitudes toward their courses, (2) comfort, engagement, and self‐efficacy, (3) learning motivations (measured by attention, perceived relevance to learning objectives, confidence, satisfaction, and interest), (4) critical thinking and practical skills, and (5) knowledge acquisition outcomes (including memorization, retention, and application). Interactive augmented reality has insignificant influences on students' flow experience, collaboration, and communication at the 0.05 level, while significantly reducing cognitive load at the 0.05 level. The findings in this study may enlighten further studies on educational technologies and extend applications of augmented reality in education.

As a popular strategy in collaborative learning, peer assessment has attracted keen interest in academic studies on online language learning contexts. The growing body of studies and findings necessitates the analysis of current publication trends and citation networks, given that studies in technology-enhanced language learning are increasingly active. Through a bibliometric analysis involving visualization and citation network analyses, this study finds that peer assessment in online language courses has received much attention since the COVID-19 outbreak. It remains a popular research topic with a preference for studies on online writing courses, and demonstrates international and interdisciplinary research trends. Recent studies have led peer assessment in online language courses to more specific research topics, such as critical factors for improving students’ engagement and feedback quality, unique advantages in providing online peer assessment, and designs to enhance peer assessment quality. This study also provides critical aspects about how to effectively integrate educational technologies into peer assessment in online language courses. The findings in this study will encourage future studies on peer assessment in online learning, language teaching methods, and the application of educational technologies.

Purpose The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots. Design/methodology/approach This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering. Findings Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education. Research limitations/implications The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective. Originality/value This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

Digital academic reading tools on computers bring multiple benefits to higher-education students. Through structural equation modeling methods, this study contributes to the following findings: (1) Perceived ease of use, perceived usefulness, and lecturers’ positive responses significantly predict students’ positive attitudes toward digital academic reading tools on computers; (2) perceived ease of use, lectures’ positive responses, and expectations of academic achievement are significantly positive predictors of students’ perceived usefulness of these tools; (3) attitudes and expectations of academic achievement significantly predict students’ positive intentions to use these tools; (4) academic experience significantly predicts students’ negative attitudes toward these tools; (5) perceived ease for collaborative learning and self-efficacy are significantly positive predictors of students’ perceived ease of using these tools. Findings in this study may contribute to understanding the external factors influencing students’ acceptance and use of digital academic reading tools on computers with a substantial explanatory power of the proposed model (R2 = 64.70–84.20%), which may benefit researchers, instructors, students, and technology designers.