Over the past two decades, various digital technologies have been applied to sustain higher education. As the latest emerging information technology, the metaverse has been a recurring theme to be considered as a new direction to promote blended English learning. This study aims to investigate metaverse-based blended English learning. Through a systematic review based on bibliographic and content analysis, the study attempts to integrate the evidence to generate a model that links the education-based metaverse. The metaverse platforms in which learners' academic success can be significantly enhanced due to a high degree of learner engagement in immersive virtual environments. In addition, the virtual learning experience is restricted by the degree of digital literacy at the same time. To improve instructors' and learners' digital literacy levels, necessary support is indispensable by educational institutions and designers of the metaverse platforms. Meanwhile, this study addresses potential challenges that may hinder sustaining metaverse-based blended English learning, and provides some suggestions based on the previous literature. In future research, we will keep updating and polishing the metaverse-based blended English learning research to provide more detailed guidance for researchers and educators.
Although academic self-concept plays a crucial role in promoting students' education, there is a paucity of studies simultaneously exploring the gender-moderated effects of academic self-concept. This study aimed to explore gender-moderated effects of academic self-concept on achievement, motivation, performance, and self-efficacy. With Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) and STARLITE criteria, this study screened and assessed the retrieved literature, finally including 53 studies. It was concluded that academic self-concept exerted a positive influence on improving achievement, enhancing motivation, ameliorating performance, and boosting self-efficacy. It should also be noted that interrelations between academic self-concept and other educational constructs may be much more complicated than expected since gender disparities may moderate the effects of academic self-concept. Gender discrepancies in academic self-concept could account for the gap between male students and female students in subject-specific achievement, motivation, performance, and self-efficacy, especially in STEM courses. Teaching interventions and educational policies should be taken to enhance female students' STEM courses self-concept. Future studies should promote educational equality, highlight academic self-concept of special groups, and enhance academic self-concept in online learning.Systematic review registrationhttps://osf.io/uxjnv/?view_only=b10db44d34154d96a361c159ca15a5b5.
Recently, achievement emotions have attracted much scholarly attention since these emotions could play a pivotal role in online learning outcomes. Despite the importance of achievement emotions in online education, very few studies have been committed to a systematic review of their effects on online learning outcomes. This study aimed to systematically review studies examining the effects of achievement emotions on online learning outcomes in terms of motivation, performance, satisfaction, engagement, and achievement. According to the selection process of Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) principles, a total of 23 publications were included in this review. It was concluded that positive achievement emotions, such as enjoyment, pride, and relaxation, could generally exert a positive effect on online learning motivation, performance, engagement, satisfaction, and achievement. It should be noted that excessive positive emotions might be detrimental to online learning outcomes. On the other hand, it has been difficult to determine the effects of negative achievement emotions on online learning outcomes because of disagreement on the effects of negative achievement emotions. In order to improve online learners' learning outcomes, instructors should implement interventions that help online learners control and regulate their achievement emotions. Teaching interventions, technological interventions, and treatment interventions could benefit online learners emotionally and academically. Future studies could examine the moderating roles of contextual factors and individual variables in the effects of achievement emotions on online learning outcomes.
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.
The new decade has been witnessing the wide acceptance of artificial intelligence (AI) in education, followed by serious concerns about its ethics. This study examined the essence and principles of AI ethics used in education, as well as the bibliometric analysis of AI ethics for educational purposes. The clustering techniques of VOSviewer (n = 880) led the author to reveal the top 10 authors, sources, organizations, and countries in the research of AI ethics in education. The analysis of clustering solution through CitNetExplorer (n = 841) concluded that the essence of AI ethics for educational purposes included deontology, utilitarianism, and virtue, while the principles of AI ethics in education included transparency, justice, fairness, equity, non-maleficence, responsibility, and privacy. Future research could consider the influence of AI interpretability on AI ethics in education because the ability to interpret the AI decisions could help judge whether the decision is consistent with ethical criteria.
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