NotesFAQContact Us
Collection
Advanced
Search Tips
Back to results
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1454147
Record Type: Journal
Publication Date: 2024-Dec
Pages: 24
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1360-2357
EISSN: EISSN-1573-7608
Available Date: N/A
Computational Analysis of Knowledge and Complexity Trends in Educational Technology Research Titles from 1927 to 2023
Shesen Guo; Ganzhou Zhang
Education and Information Technologies, v29 n18 p25487-25510 2024
This study looked at titles of research papers on educational technology that were published between 1927 and 2023 using computational text analysis. To map research trends, metrics for technology terminology use, network complexity, and knowledge updating rates were used. The findings showed that, despite some fluctuations, titles have become more technologically diverse and interconnected over time, indicating a greater emphasis on technology and interdisciplinarity. Escalating title complexity was visualized using network analysis. Citation patterns revealed that science/engineering and educational technology both update knowledge at comparable rates. This computational analysis shows how the fields of education and technology have been evolving together over time, giving historical context to understand current trends. The study shows how to use data science techniques to map the dynamics of research within a practical domain that connects technology and practice.
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Information Analyses; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A