Skip to main content

Advertisement

Log in

Deciphering the impact of machine learning on education: Insights from a bibliometric analysis using bibliometrix R-package

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

This study leverages bibliometric analysis through the bibliometrix R-package to dissect the expansive influence of machine learning on education, a field where machine learning’s adaptability and data-processing capabilities promise to revolutionize teaching and learning methods. Despite its potential, the integration of machine learning in education requires a nuanced understanding to navigate the associated challenges and ethical considerations effectively. Our investigation spans articles from 2000 to 2023, focusing on identifying growth patterns, key contributors, and emerging trends within this interdisciplinary domain. By analyzing 970 selected articles, this study uncovers the developmental trajectory of machine learning in education, revealing significant insights into publication trends, prolific authors, influential institutions, and the geographical distribution of research. Furthermore, it highlights the journals pivotal in disseminating machine learning education research, the most cited works that shape the field, and the dynamic evolution of research themes. This bibliometric exploration not only charts the current landscape but also anticipates future directions, suggesting areas for further inquiry and potential breakthroughs. Through a detailed examination of empirical evidence and a critical analysis of machine learning applications in educational settings, this study aims to provide a foundational understanding of the field’s complexities and potentials. The anticipated outcome is a comprehensive roadmap that guides researchers, educators, and policymakers towards a thoughtful integration of machine learning in education, balancing innovation with ethical stewardship.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data availability

We make sure that all data and materials support our published claims and comply with feld standards.

References

Download references

Acknowledgements

We thank editors and reviewers for their valuable feedback, which has greatly improved this manuscript. Their insights and suggestions have been instrumental in refining our work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zilong Zhong.

Ethics declarations

Competing interests

We have no conflicts of interest to declare that are relevant to the content of this article.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhong, Z., Guo, H. & Qian, K. Deciphering the impact of machine learning on education: Insights from a bibliometric analysis using bibliometrix R-package. Educ Inf Technol 29, 21995–22022 (2024). https://doi.org/10.1007/s10639-024-12734-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-024-12734-8

Keywords

Navigation