Gamification, characterized by the integration of game design elements into non‐game environments, has gained popularity in classrooms due to its potential for increased engagement and enjoyment compared to traditional lecture‐based teaching methods. While students generally exhibit positive attitudes towards gamification, its impact on academic achievement remains a subject of debate. This study employed a meta‐analysis approach to examine the overall influence of gamification on students' academic performance. The sample comprised 22 experimental studies conducted between 2008 and 2023, comparing the effects of gamified and non‐gamified classes. Utilizing a random effects model, the results revealed a moderately positive effect of gamification on student academic performance (Hedges's g = 0.782, p < 0.05). The paper further discussed the outcomes of various moderator analyses, providing valuable insights into the selection and utilization of game design elements, as well as considerations specific to different educational stages. Practitioner notes: What is already known about this topic: Most research has consistently demonstrated that gamification has a positive impact on students' achievement. The current state of review research is not sufficiently comprehensive. There is a lack of meta‐analyses exploring the diverse impacts of gamification. What this paper adds: The effect of factors such as geographical regions, education levels, learning environments, subjects and game elements on gamification was examined. The study revealed a significant and positive impact of gamification on students' achievement across various factors, including geographical regions, education levels, learning environments, subjects and game elements. Implications for practice and/or policy: Gamification represents a prudent choice for teachers seeking to enhance students' achievement. Teachers are suggested to adopt and employ appropriate game elements in their instructional approaches. Future research could focus on investigating the impact of feedback as a game element in teaching and learning.

Motivated by the rapid development and application of artificial intelligence (AI) technologies in education and the needs of language learners during the COVID-19 pandemic, an AI-enabled English language learning (AIELL) system featuring authentic and ubiquitous learning for the acquisition of vocabulary and grammar in English as a second language (L2) was developed. The aim of this study was to present the developmental process and methods used to design, develop, evaluate, and validate the AIELL system and to distil key design features for English learning in authentic contexts. There were 20 participants in the tests, with three interviewees in the study. Mixed research methods were employed to analyse the data, including a demonstration test, a usability test, and an interview. The quantitative and qualitative data collected and analysed affirmed the validity and usability of the design and helped identify areas for further improvements to the desired features. This study informs the integration of AI into facilitating language teaching and learning guided by the mobile learning principle.

As artificial intelligence (AI) becomes increasingly integrated into various fields, the need to enhance learners’ AI literacy is more urgent than ever. Despite its growing importance, a comprehensive review of AI literacy education research has been lacking. This study addresses that gap by mapping the current landscape, tracing its evolution, and identifying key themes through a bibliometric analysis of research from 2014 to 2024, utilizing CiteSpace for data visualization and analysis. This study systematically selected 335 relevant articles from databases, including Web of Science Core Collection, Scopus, and Science Direct, following PRISMA guidelines. Our methodology involved keyword co-occurrence mapping to trace the development paths and thematic evolution within the field. By examining publication trends and thematic clusters, we provide insights into the progression and focal points of AI literacy education research over the past decade. The study reveals three key insights. First, AI literacy education research has shifted from an exploratory phase to rapid growth, with a marked increase in publications. Second, four distinct developmental trajectories have emerged, emphasizing the interdisciplinary nature of the field and its connections to information, digital, and algorithmic literacy. Third, nine prominent research themes have been identified, with data literacy, machine learning, AI literacy, the technology acceptance model, and computational thinking as focal points. These themes highlight AI’s evolving role, particularly in education, and shifts in research priorities. This review provides a comprehensive understanding of AI literacy education’s evolution and its implications for education, ethics, and society. As AI continues to influence modern education and industry, this analysis serves as a valuable resource for researchers, educators, and policymakers navigating the complex intersection of AI and literacy.