Daniel C. Cliburn

604 citations
37 papers · 451 · h-index 12

Impact in

Papers in

Daniel C. Cliburn

36 papers receiving 410 citations

Peers

Daniel C. Cliburn
Comparison fields: 5 of 72
  • Computer Science Applications 185
  • Human-Computer Interaction 108
  • Geography, Planning and Development 60
  • Developmental and Educational Psychology 105
  • Computer Vision and Pattern Recognition 120
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Citations per field
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Countries citing papers authored by Daniel C. Cliburn

Since Specialization
Citations

This map shows the geographic impact of Daniel C. Cliburn'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 Daniel C. Cliburn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel C. Cliburn more than expected).

Fields of papers citing papers by Daniel C. Cliburn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel C. Cliburn. 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 Daniel C. Cliburn. The network helps show where Daniel C. Cliburn may publish in the future.

Co-authors

The 12 scholars most cited alongside Daniel C. Cliburn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel C. Cliburn Line = papers co-authored together Daniel C. Cliburn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200369
2 200350
3 200646
4 200239
5 200830
6 200623
7 200619
8 200718
9 200815
10 200813
11 200412
12 200911
13 200911
14 201810
15 20109
16 20088
17
Towards an effective low-cost virtual reality display system for education
20087
18 20086
19 20106
20 20065

About Daniel C. Cliburn

Daniel C. Cliburn is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Computer Science Applications, Developmental and Educational Psychology and Automotive Engineering, having authored 37 papers that have together received 451 indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (14 papers), Teaching and Learning Programming (14 papers), Augmented Reality Applications (13 papers), Educational Games and Gamification (11 papers), Interactive and Immersive Displays (7 papers), Spatial Cognition and Navigation (6 papers), Digital Games and Media (6 papers) and Experimental Learning in Engineering (4 papers). The work is most often cited by research in Computer Science Applications (185 citations), Human-Computer Interaction (108 citations), Geography, Planning and Development (60 citations), Developmental and Educational Psychology (105 citations) and Computer Vision and Pattern Recognition (120 citations). Daniel C. Cliburn has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include James R. Miller, Johannes J. Feddema, Terry A. Slocum, Susan M. Miller, John H. Krantz, David Parsons, Emma Bowring, Michael E. Doherty, John Mayberry and Henry Cheung. Their work appears in journals such as Cartography and Geographic Information Science, Computers & Graphics, 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), ACM SIGCSE Bulletin and Journal of computing sciences in colleges.

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.

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