Robert L. Mayes

525 citations
40 papers · 311 · h-index 11

Impact in

Papers in

    • Science Education and Pedagogy 8
    • Mathematics Education and Teaching Techniques 5
    • Online and Blended Learning 3
    • Statistics Education and Methodologies 10

Robert L. Mayes

36 papers receiving 257 citations

Peers

Robert L. Mayes
Comparison fields: 5 of 68
  • Statistics and Probability 83
  • Computer Science Applications 40
  • Education 213
  • Developmental and Educational Psychology 62
  • Information Systems and Management 23
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Citations per field
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Citations per year

Countries citing papers authored by Robert L. Mayes

Since Specialization
Citations

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

Fields of papers citing papers by Robert L. Mayes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert L. Mayes. 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 Robert L. Mayes. The network helps show where Robert L. Mayes may publish in the future.

Co-authors

The 25 scholars most cited alongside Robert L. Mayes, 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 Robert L. Mayes Line = papers co-authored together Robert L. Mayes links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Quantitative Reasoning and Mathematical Modeling: A Driver for STEM Integrated Education and Teaching in Context
201236
2
Themes and strategies for transformative online instruction: A review of literature and practice
201135
3 201326
4 201325
5 199522
6 201420
7 199919
8 202115
9 199214
10
Exploring the Science Framework
201211
11 201810
12 200810
13 20217
14
Themes and Strategies for Transformative Online Instruction: A Review of Literature
20116
15
Exploring the Science Framework: Making Connections in Math with the Common Core State Standards
20126
16 20175
17 20205
18 20154
19 19934
20 20173

About Robert L. Mayes

Robert L. Mayes is a scholar working on Education, Statistics and Probability, Developmental and Educational Psychology, Molecular Biology and Computer Science Applications, having authored 40 papers that have together received 311 indexed citations. Recurring topics across this work include Statistics Education and Methodologies (10 papers), Science Education and Pedagogy (8 papers), Innovative Teaching and Learning Methods (6 papers), Teaching and Learning Programming (6 papers), Genetics, Bioinformatics, and Biomedical Research (6 papers), Mathematics Education and Teaching Techniques (5 papers), Online and Blended Learning (3 papers) and Biomedical and Engineering Education (3 papers). The work is most often cited by research in Statistics and Probability (83 citations), Computer Science Applications (40 citations), Education (213 citations), Developmental and Educational Psychology (62 citations) and Information Systems and Management (23 citations). Robert L. Mayes has collaborated with scholars based in United States, Vietnam and Egypt. Frequent co-authors include Marc Gaudry, Thomas R. Koballa, Heng‐Yu Ku, Rae Walker, Joseph Dauer, James D. Myers, Philip N. Chase, Tammy M. Long, Lisa Watson and D.H. Owens. Their work appears in journals such as School Science and Mathematics, International Journal of Science Education, Computers in the Schools, Journal of College Reading and Learning and Engineering Journal.

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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