Learning mathematics has been considered as a great challenge for many students. The advancement of computer technologies, in particular, artificial intelligence (AI), provides an opportunity to cope with this problem by diagnosing individual students’ learning problems and providing personalized supports to maximize their learning performances in mathematics courses. However, there is a lack of reviews from diverse perspectives to help researchers, especially novices, gain a whole picture of the research of AI in mathematics education. To this end, this research aims to conduct a bibliometric mapping analysis and systematic review to explore the role and research trends of AI in mathematics education by searching for the relevant articles published in the quality journals indexed by the Social Sciences Citation Index (SSCI) from the Web of Science (WOS) database. Moreover, by referring to the technology-based learning model, several dimensions of AI in mathematics education research, such as the application domains, participants, research methods, adopted technologies, research issues and the roles of AI as well as the citation and co-citation relationships, are taken into account. Accordingly, the advancements of AI in mathematics education research are reported, and potential research topics for future research are recommended.

Automated writing feedback supported by artificial intelligence (AI) techniques has attracted the attention of English as Foreign Language (EFL) researchers. However, there is insufficient evidence and inconsistent conclusions on the actual impacts of AI on students’ writing skills. In addition, in the field of EFL writing, there are few studies which have integrated appropriate teaching strategies to promote the effectiveness of EFL writing teaching and learning. Furthermore, it remains unclear how learners can effectively benefit from AI technology-based English writing. To solve this problem, this study proposed a reflective thinking promotion mechanism-based AI-supported English writing (RTP-AIEW) approach to deepen learners’ thinking and improve their EFL writing quality. To investigate the effectiveness of this learning approach, a quasi-experiment was conducted in two EFL writing classes in a university. One class (50 students) was the experimental group learning with the proposed RTP-AIEW approach, while the other class (53 students) was the control group learning with conventional AI-supported EFL writing. The results indicated that the proposed approach not only significantly improved the experimental group students’ English writing performance, but also improved their self-efficacy and self-regulated learning, and significantly reduced their cognitive load. In addition, students’ learning experience and perceptions are also discussed.

This study provides research-based evidence to profile: (1) the roles of artificial intelligence in nursing, (2) its research applications, and (3) the research trends for future study. On the basis of the PRISMA statement, a series of AI and nursing education related keywords from the literature were used to retrieve high-quality journal articles from the Web of Science. A total of 112 AI-supported nursing education research articles were analyzed based on a three-dimensional framework, including interaction (e.g. the roles of AI, types of AI systems), research (e.g. methods and fields), and performance (e.g. research groups and measurement foci). The results revealed that AI played a primary role in profiling and prediction in nursing research (63%), and the most used AI system in nursing was intelligent agents (53%). The quantitative approach (87%) was the dominant research method, and the most relevant studies concerned health and medicine (92%). Regarding sample and measurement matters, patients and medical staff (75%) were the two primary research samples, and the performance evaluation of AI-related tools and systems (90%) was the core measurement focus. Additional content analysis across the three research interests was performed and discussed. Directions for future studies are provided.