Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
What are the learning affordances of 3‐D virtual environments?
20091.1k citationsBarney Dalgarno, Mark J.W. Leeprofile →
Design and implementation factors in blended synchronous learning environments: Outcomes from a cross-case analysis
2015321 citationsMatt Bower, Barney Dalgarno et al.profile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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Countries citing papers authored by Barney Dalgarno
Since
Specialization
Citations
This map shows the geographic impact of Barney Dalgarno's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Barney Dalgarno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barney Dalgarno more than expected).
This network shows the impact of papers produced by Barney Dalgarno. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Barney Dalgarno. The network helps show where Barney Dalgarno may publish in the future.
Co-authorship network of co-authors of Barney Dalgarno
This figure shows the co-authorship network connecting the top 25 collaborators of Barney Dalgarno.
A scholar is included among the top collaborators of Barney Dalgarno based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Barney Dalgarno. Barney Dalgarno is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lee, Mark, Barney Dalgarno, & Helen Farley. (2012). Virtual worlds in tertiary education: An Australasian perspective. Australasian Journal of Educational Technology. 28.3 indexed citations
6.
Dalgarno, Barney, Andrea Bishop, Danny R. Bedgood, & William Adlong. (2012). What factors contribute to students’ confidence in chemistry laboratory sessions and does preparation in a virtual laboratory help?. Proceedings of The Australian Conference on Science and Mathematics Education (formerly UniServe Science Conference). 10. 15–21.3 indexed citations
Dalgarno, Barney, Gregor Kennedy, & Sue Bennett. (2010). Can functional brain imaging be used to explore interactivity and cognition in multimedia learning environments. Charles Sturt University Research Output (CRO). 21(3). 317–342.2 indexed citations
Dalgarno, Barney, Andrea Bishop, & Danny R. Bedgood. (2003). The potential of virtual laboratories for distance education science teaching: reflections from the development and evaluation of a virtual chemistry laboratory. Proceedings of The Australian Conference on Science and Mathematics Education (formerly UniServe Science Conference). 9. 90–95.31 indexed citations
19.
Dalgarno, Barney. (2002). The Potential of 3D virtual learning environments: A constructivist analysis. Australasian Journal of Educational Technology. 5(2). 1–19.67 indexed citations
20.
Dalgarno, Barney. (2001). Technologies Supporting Highly Interactive Learning Resources on the Web: An Analysis. The Journal of Interactive Learning Research. 12(2). 153–171.10 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.