Enterprise AI Analysis

This study conducted a bibliometric analysis by retrieving scientific publications on DTT in biosciences education from the Web of Science Core Collection for the period 2015–2024. Initial search strategies, developed with ChatGPT-40, involved specific technologies, broader digital education terms, and bioscience descriptors, restricting the search to the Title field. After filtering by document type ('Article' and 'Review Article'), 224 records were collected. A rigorous screening process, following PRISMA guidelines, involved removing duplicates (1 record) and unrelated studies (56 records), resulting in a final dataset of 167 records. Metadata, including publication year, journals, author keywords, research areas, author affiliations, countries, and most cited articles, were analyzed using VantagePoint 11.0. Co-occurrence matrices were generated for network analysis using Gephi 0.10.1 to calculate metrics like degree centrality (DC), weighted degree centrality (WDC), eigenvector centrality (EC), betweenness centrality (BC), and closeness centrality (CC). The Fruchterman-Reingold algorithm determined the network layout, with WDC values influencing node size and color intensity. GraphPad Prism 8 was used for frequency graphs. The study acknowledges limitations, such as focusing on a single database (Web of Science) and title-only searches to prioritize precision, while emphasizing WoS's recognized coverage and quality metadata.

The analysis of 167 records from 2015–2024 reveals a significant growth trend in DTT bioscience education, peaking in 2024 with 49 records and a 54.10% CAGR. Anatomical Sciences Education (Wiley) leads with 14.37% of publications, followed by BMC Medical Education (4.19%). USA-based researchers are the most frequent authors (25.75%), followed by China (8.38%) and Spain (6.59%). Education & Educational Research is the top research area (54.49%), with Anatomy & Morphology (11.98%) and Computer Science (8.98%) also prominent. Virtual Reality is the most frequent keyword (34.13%), followed by Anatomy Education and Medical Education. Network analysis shows Virtual Reality as the most central keyword, highlighting the dominance of immersive technologies. The country network indicates USA as the most central node, with Spain and Australia also strong in collaboration. However, collaboration networks among organizations are sparse (8.10% density), with the University of Queensland and Ochsner Health System identified as central but often isolated hubs.

Key Trends in DTT Bioscience Education Research

The study's limitations include a focus on a single database (Web of Science) and restricting searches to article titles for precision, which might limit coverage. While these choices align with common bibliometric practices, they inherently present trade-offs. Future research should address critical gaps identified in the existing literature. There's a notable need for studies that focus on the development of *new* digital tools, rather than merely testing the effectiveness of existing ones or comparing them to traditional methods. A broader approach to teaching and learning is encouraged, considering contextual factors, teacher training, and policy investments in school infrastructure, beyond just tool development. Fostering greater international collaboration, especially with institutions in the Global South, is essential to overcome barriers like limited access to resources and expertise, ensuring more inclusive and impactful educational research and innovation in DTT for bioscience education.