During students’ scientific practice, the aim is to provide a quantitative analysis of inclusive artificial intelligence literature using the bibliometric method in the period 2019-2024. During the research, a general summary of the latest scientific research would be presented using the bibliometric method, the thematic development and new keywords that have appeared during the studied period would be presented. The performance analysis uses bibliometric indicators: h-index, productivity, and citations. The software VOSviewer would be used to display the bibliographic material, which creates a scientific map using common citations and key word matches. The most relevant research in the field would be identified and classified by journal, article, author, institution, and country using the Web of Science database. This study serves an informative role in quantifying and interpreting bibliographic characteristics of inclusive artificial intelligence sciences, where the most common quantitative methods for analysing scholarly communication activities are used. The goal of the project: to present a quantitative analysis of inclusive artificial intelligence literature using the bibliometric method in the period 2019-2024.
Project results:
This study aimed to explore the trends in AI-inclusive education research by conducting a bibliometric analysis of articles published between 2019 and 2023. The research questions focused on identifying the most influential study fields and trending topics within this domain.
The analysis revealed that educational sciences are the most influential field in AI-inclusive education research. Other significant fields include special education and rehabilitation, with contributions from social and environmental sciences. As indicated by citation frequency and keyword co-occurrence, the trending topics include autism and developmental disorders, general educational research, and psychological themes, with inclusive education emerging as the most dominant keyword. The United States leads in publication output, with Australia and England also showing substantial contributions. Additionally, the research volume in AI-inclusive education has consistently increased from 2019 to 2023.
In conclusion, the research confirms that AI-inclusive education is a growing interdisciplinary field with a strong focus on educational sciences and special education. The increasing number of publications and the diversity of research topics highlight the expanding interest and evolving trends in this area, emphasising the importance of inclusivity in the application of AI in education. However, due to the limited scope of the study, further research ought to be done encompassing a more thorough look at the keyword distribution and other additional measures.
Period of project implementation: 2024-07-01 - 2024-08-31
Project coordinator: Kaunas University of Technology
