The Role of Machine Learning in Distance Education - Alan, Abdullah; Karabatak, Songul; Karabatak, Murat (Institute of Electrical and Electronics Engineers Inc., 2025)
This study aims to present a bibliometric analysis to examine the role of machine learning in distance education. The analysis of 1768 articles obtained from the Web of Science database between 2005 and 2024, using the keywords 'machine learning, deep learning, distance education, e-Iearning, and online learning,' was conducted using the Biblioshiny software. The analytical approach used in this study covers a range of bibliometric indicators, including keywords, authors, documents, sources, and countries. A significant increase in the number of publications on the topic has been observed since 2017. The majority of the studies come from China and the United States, which are also the countries with the highest number of citations. Nanyang Technological University and Tsinghua University are among the institutions with the highest number of publications on the topic. IEEE Access, Education and Information Technologies, and Applied Sciences-Basel are the journals where the articles are most frequently published. 'Online learning,' 'machine learning,' and 'deep learning' are the most frequently used keywords. This study highlights the increasing importance of machine learning in distance education and provides valuable insights for future research. © 2025 IEEE.
13th International Symposium on Digital Forensics and Security, ISDFS 2025 -- 24 April 2025 through 25 April 2025 -- Boston -- 209331
Keywords: Bibliometrics; Deep Learning; Distance Education; Machine Learning