scholarly journals Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 584 ◽  
Author(s):  
Gwo-Jen Hwang ◽  
Yun-Fang Tu
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Education Research ◽  
Mathematics Education ◽  
Research Trends ◽  
Mathematics Education Research ◽  
Future Research ◽  
Research Issues ◽  
Bibliometric Mapping ◽  
Mapping Analysis

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.

scholarly journals When bibliometrics met mathematics education research: the case of instrumental orchestration

ZDM ◽  
2020 ◽  
Vol 52 (7) ◽  
pp. 1455-1469 ◽  
Author(s):  
Paul Drijvers ◽  
Sebastian Grauwin ◽  
Luc Trouche
Keyword(s):  
Education Research ◽  
Mathematics Education ◽  
Adult Learners ◽  
Research Literature ◽  
Mathematics Education Research ◽  
Future Research ◽  
Teaching With Technology ◽  
Instrumental Orchestration ◽  
Identity Cards ◽  
Set Up

Abstract Thanks to digital technology, methods for finding and analysing research literature have become dramatically more powerful over the last decades. Also, new bibliometric techniques have been developed and applied to the results of such literature search queries. The application of these bibliometric tools to mathematics education research, however, is rare. In this paper, we explore the value of these techniques for mathematics education research through triangulating bibliometrics and expert findings. To do so, we address the case of instrumental orchestration, and want to know how this notion developed over time and was used in research practices. The results show that bibliometric clustering techniques provided a sense-making sketch of the ‘landscape’ of instrumental orchestration research. Triangulating the bibliometric findings with expert interpretations seemed an appropriate method to set up compact ‘identity cards’. In the case of instrumental orchestration, we identified five main clusters in research literature, characterized by the following labels: Managing teaching complexity, Designing living resources, Teaching with technology, Adult learners, and Interacting with computers. The paper ends with some reflections on the potential of bibliometrics in our field and on future research on instrumental orchestration.

Researching Race in Mathematics Education

2009 ◽  
Vol 111 (2) ◽  
pp. 295-338 ◽  
Author(s):  
Danny Bernard Martin
Keyword(s):  
Education Research ◽  
African American ◽  
Mathematics Education ◽  
Critical Theory ◽  
Research Policy ◽  
Mathematics Learning ◽  
Mathematics Education Research ◽  
Future Research ◽  
Policy And Practice ◽  
Differential Outcomes

Background Within mathematics education research, policy, and practice, race remains undertheorized in relation to mathematics learning and participation. Although race is characterized in the sociological and critical theory literatures as socially and politically constructed with structural expressions, most studies of differential outcomes in mathematics education begin and end their analyses of race with static racial categories and group labels used for the sole purpose of disaggregating data. This inadequate framing is, itself, reflective of a racialization process that continues to legitimize the social devaluing and stigmatization of many students of color. I draw from my own research with African American adults and adolescents, as well as recent research on the mathematical experiences of African American students conducted by other scholars. I also draw from the sociological and critical theory literatures to examine the ways that race and racism are conceptualized in the larger social context and in ways that are informative for mathematics education researchers, policy makers, and practitioners. Purpose To review and critically analyze how the construct of race has been conceptualized in mathematics education research, policy, and practice. Research Design Narrative synthesis. Conclusion Future research and policy efforts in mathematics education should examine racialized inequalities by considering the socially constructed nature of race.

Teachers’ perception, interpretation, and decision-making: a systematic review of empirical mathematics education research

ZDM ◽  
2016 ◽  
Vol 48 (1-2) ◽  
pp. 1-27 ◽  
Author(s):  
Rebekka Stahnke ◽  
Sven Schueler ◽  
Bettina Roesken-Winter
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Education Research ◽  
Mathematics Education ◽  
Mathematics Education Research

scholarly journals Implementation-related research in mathematics education: the search for identity

ZDM ◽  
2021 ◽  
Author(s):  
Boris Koichu ◽  
Mario Sánchez Aguilar ◽  
Morten Misfeldt
Keyword(s):  
Education Research ◽  
Mathematics Education ◽  
Implementation Research ◽  
Scaling Up ◽  
Mathematics Education Research ◽  
Future Research ◽  
Special Issue ◽  
Related Research ◽  
Survey Paper ◽  
Research In Mathematics Education

AbstractImplementation has always been a paramount concern of mathematics education, but only recently has the conceptualizing and theorizing work on implementation as a phenomenon begun in our field. In this survey paper, we conduct a hermeneutic review of mathematics education research identified as related to the implementation problematics. The first cycle of the review is based on examples of studies published in mathematics education journals during the last 40 years. It is organized according to five reasons for developing implementation research. The second cycle concerns 15 papers included in this special issue and is organized by four themes, as follows: objects of implementation, stakeholders in implementation, implementation vs. scaling up, and implementability of mathematics education research. The paper is concluded with a refined glossary of implementation-related terms and suggestions for future research.

Educational data mining: a systematic review of research and emerging trends

2020 ◽  
Vol 48 (4) ◽  
pp. 225-236
Author(s):  
Xu Du ◽  
Juan Yang ◽  
Jui-Long Hung ◽  
Brett Shelton
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Educational Data Mining ◽  
Research Trends ◽  
Future Research ◽  
Major Research ◽  
Research Topics ◽  
Content Type ◽  
State Of Art ◽  
Open Issues

Purpose Educational data mining (EDM) and learning analytics, which are highly related subjects but have different definitions and focuses, have enabled instructors to obtain a holistic view of student progress and trigger corresponding decision-making. Furthermore, the automation part of EDM is closer to the concept of artificial intelligence. Due to the wide applications of artificial intelligence in assorted fields, the authors are curious about the state-of-art of related applications in Education. Design/methodology/approach This study focused on systematically reviewing 1,219 EDM studies that were searched from five digital databases based on a strict search procedure. Although 33 reviews were attempted to synthesize research literature, several research gaps were identified. A comprehensive and systematic review report is needed to show us: what research trends can be revealed and what major research topics and open issues are existed in EDM research. Findings Results show that the EDM research has moved toward the early majority stage; EDM publications are mainly contributed by “actual analysis” category; machine learning or even deep learning algorithms have been widely adopted, but collecting actual larger data sets for EDM research is rare, especially in K-12. Four major research topics, including prediction of performance, decision support for teachers and learners, detection of behaviors and learner modeling and comparison or optimization of algorithms, have been identified. Some open issues and future research directions in EDM field are also put forward. Research limitations/implications Limitations for this search method include the likelihood of missing EDM research that was not captured through these portals. Originality/value This systematic review has not only reported the research trends of EDM but also discussed open issues to direct future research. Finally, it is concluded that the state-of-art of EDM research is far from the ideal of artificial intelligence and the automatic support part for teaching and learning in EDM may need improvement in the future work.

Mathematics educators are speaking about PISA, aren’t they?

2020 ◽  
Vol 39 (4) ◽  
pp. 266-280
Author(s):  
Chiara Giberti ◽  
Andrea Maffia
Keyword(s):  
Education Research ◽  
Mathematics Education ◽  
International Student ◽  
Student Assessment ◽  
Development Program ◽  
Mathematics Education Research ◽  
Future Research ◽  
International Student Assessment ◽  
Oecd Pisa ◽  
Using Data

Abstract This paper sets out to explore the different uses made of Organisation for Economic Co-operation and Development Program for International Student Assessment (OECD-PISA) tests and data in mathematics education research. Through a comprehensive literature review of journals and conference papers, we show that although a large variety of topics is addressed, they do not cover all the topics considered in mathematics education research. Analysing the temporal and geographical distribution of papers, we find that there is increasing interest in the use of PISA in our field of research and that different countries are involved in different ways in mathematics education research about PISA. As a conclusion, we suggest that critical research into the effect of PISA can be developed further, especially in those countries that have joined the OECD survey in recent years. Other future research paths using data from PISA are detected.

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