Ralph Gabbard

33 papers receiving 1.0k citations

Peers

Ralph Gabbard
Comparison fields: 5 of 163
  • Developmental and Educational Psychology 239
  • Computer Science Applications 79
  • Library and Information Sciences 19
  • Education 258
  • Pharmaceutical Science 50
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Peter Holtz Germany
J. R. Cooper United States
John N. Gardner United States
Amanda Collins United Kingdom
Robert M. Bell United States
James R. Cox United States
Frederick E. Williams United States
Satoru Yokoyama Japan
Cynthia J. Brame United States
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Countries citing papers authored by Ralph Gabbard

Since Specialization
Citations

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

Fields of papers citing papers by Ralph Gabbard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ralph Gabbard. 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 Ralph Gabbard. The network helps show where Ralph Gabbard may publish in the future.

Co-authors

The 13 scholars most cited alongside Ralph Gabbard, 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 Ralph Gabbard Line = papers co-authored together Ralph Gabbard links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998378
2 1977198
3 1969120
4 197856
5 197847
6 197246
7 199837
8 200837
9 196735
10 196429
11 198321
12 197319
13 195818
14 196217
15 198216
16
Hypermedia as an educational technology: a review of the empirical literature on learner comprehension, control and style
200013
17 198113
18 198013
19 196210
20 198410

About Ralph Gabbard

Ralph Gabbard is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Genetics, Pharmacology and Education, having authored 33 papers that have together received 1.2k indexed citations. Recurring topics across this work include Steroid Chemistry and Biochemistry (10 papers), Estrogen and related hormone effects (8 papers), Hormonal and reproductive studies (7 papers), Online and Blended Learning (5 papers), Analytical Chemistry and Chromatography (4 papers), Pharmacogenetics and Drug Metabolism (4 papers), Innovative Teaching and Learning Methods (3 papers) and Knowledge Management and Sharing (2 papers). The work is most often cited by research in Developmental and Educational Psychology (239 citations), Computer Science Applications (79 citations), Library and Information Sciences (19 citations), Education (258 citations) and Pharmaceutical Science (50 citations). Ralph Gabbard has collaborated with scholars based in United States. Frequent co-authors include Andrew Dillon, Albert Segaloff, A Segaloff, Edward E. Smissman, John K. Baker, David Kaunelis, William L. Duax, Ronald F. Borne, P. Strong and Douglas C. Rohrer. Their work appears in journals such as Steroids, Endocrinology, Review of Educational Research, The Journal of Organic Chemistry and Journal of Pharmaceutical Sciences.

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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