Artificial intelligence (AI) in chemistry education: A bibliometric and content analysis of papers published.

Chemistry education is an important field that aims to provide students with practical skills as well as theoretical knowledge. In recent years, the use of AI technologies

in education has started to reshape teaching and learning, so there is an increase in

the number of papers dealing with use of AI applications in chemistry education research. This study aims analyze papers published on the integration of AI in chemistry

education to identify the trends and developments. These trends will be useful in

terms of determining the new studies on AI applications in chemistry courses and

making chemistry teaching effective, efficient and interesting. We particularly, aimed

to determine the research area, subject and research designs, data collection tools

and analyses of the publications in Web of Science (WoS) related to AI in chemistry

teaching.

We employed document analysis as a research design. The documents used in the

study consist of research articles related to chemistry education AI in the journals indexed in the ‘Web of science’. The data were obtained from the analysis of 91 research

articles between 2015-2024. The articles were analyzed with VosViewer and ARRefMan softwares. The data were analyzed by creating word groups obtained from the

categories under the themes determined in the data obtained. The findings obtained

from the analysis, trends were tried to be determined according to years, journal

name, chemistry field, chemistry topics, teaching method used, universities where the

first or responsible authors are located. In addition, the research approach, design,

data collection tools, target group, sample size, data analysis types used in the method

section of the research articles were also determined.