Visualizing Status, Hotspots, and Future Trends in Mathematical Literacy Research via Knowledge Graph

Xiaohong Chen, Jincheng Zhou (), Jinqiu Wang, Dan Wang, Jiu Liu, Dingpu Shi, Duo Yang and Qingna Pan
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Xiaohong Chen: School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, China
Jincheng Zhou: School of Computer and Information, Institute of Big Data Application and Artificial Intelligence, Qiannan Normal University for Nationalities, Duyun 558000, China
Jinqiu Wang: School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, China
Dan Wang: School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, China
Jiu Liu: School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, China
Dingpu Shi: School of Computer and Information, Institute of Big Data Application and Artificial Intelligence, Qiannan Normal University for Nationalities, Duyun 558000, China
Duo Yang: School of Computer and Information, Institute of Big Data Application and Artificial Intelligence, Qiannan Normal University for Nationalities, Duyun 558000, China
Qingna Pan: School of Computer and Information, Institute of Big Data Application and Artificial Intelligence, Qiannan Normal University for Nationalities, Duyun 558000, China

Sustainability, 2022, vol. 14, issue 21, 1-19

Abstract: The goal of education for sustainable development is to prepare future citizens to make informed decisions and take responsible action to solve problems. The purpose of mathematical literacy is to ensure that all learners develop an understanding of mathematics, and how to relate mathematics to the world and use mathematical knowledge to make valuable decisions in their lives, work, and society. It can be seen that the purpose of mathematical literacy coincides with the goal of education for sustainable development. In addition, math literacy is closely related to self-regulated learning (SRL), which is the key to meaningful learning and sustainable development. In educational research, it is an essential task to cultivate learners’ mathematical literacy and promote their sustainable development. With the rapid growth of emerging technologies, the emergence of big data has brought numerous challenges to various research fields. In the age of big data, educational research that can identify research perspectives and hotspots and summarize research evolution rules from a large body of literature can assist us in deepening subsequent analysis. As a result, in this study, we used CiteSpace and HistCite knowledge map visualization and exploration technology to examine mathematical literacy research trends, major research countries and regions, major research institutions, significant researchers, highly cited papers, research hotspots, and evolution trends on a global scale. Through this study, we found that the earliest literature on mathematical literacy appeared in 1957, and the research on mathematical literacy can be divided into three germination stages (1957–2001), a slow development stage (2001–2011), and a prosperous development stage (2011–2022). Most studies come from developed countries such as the US, the UK, Germany, and Australia. The Universities of Utrecht and Purdue University were the most published institutions, and scholars at Purpura published the most articles. The research object of highly cited literature is mainly children, and the research is primarily carried out through the measurement of students’ mathematical ability and achievement and the analysis of related influencing factors, which provides a direction for how to improve students’ mathematical literacy. The research on mathematical literacy mainly includes four research hotspots: working memory and mathematical literacy; brain science and mathematical literacy; mathematical achievement and mathematical literacy; and the generation strategy of mathematical literacy. The research field of mathematics literacy mainly includes working memory, parietal cortex, math performance, mathematics education, early childhood, parental belief, fractions, cognitive development, and student learning. There are 10 clusters. Different clusters have different evolutionary trends. With the evolution of time, working memory, mathematical education, fractions, and precinct beliefs clustered, gradually expanding from the concentrated research direction to the subdivision field. The clusters of parietal cortex, math performance, early childhood, cognitive development, and students do not show large keyword nodes during the research period. With time, it has gradually expanded from the centralized research direction to the subdivision field. The parietal cortex, math performance, early childhood, cognitive development, and students clusters did not show large keyword nodes during the whole study period.

Keywords: sustainable development; self-regulated learning; mathematical literacy; big data; CiteSpace; HistCite; knowledge graph visualization; research hotspots; evolution trend (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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