Abstract
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.
Highlights
Several previous studies have reported that students generally feel that it is difficult to complete mathematics tasks, in particular, those which need to be resolved with multiple steps [3,4]
The greatest amount of AI in mathematics education (AIME) research was published in Computers & Education, followed by the Journal of Educational Psychology and the Journal of Computer Assisted
More education and educational technology researchers have engaged in AIME research than mathematics education researchers
Summary
Mathematics education has been identified as a complex and challenging task aiming to foster learners’. Several previous studies have reported that students generally feel that it is difficult to complete mathematics tasks, in particular, those which need to be resolved with multiple steps [3,4]. Researchers have made attempts to develop various learning strategies and tools to enhance students’ mathematics learning outcomes [1]. They have pointed out the importance of identifying the factors affecting students’ mathematics learning performance, such as insufficient prior knowledge and lack of personalized supports for individual students [5,6]
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