Mary Pearson

487 citations
35 papers · 310 · h-index 9

Impact in

Papers in

Mary Pearson

29 papers receiving 286 citations

Peers

Mary Pearson
Comparison fields: 5 of 88
  • Computer Science Applications 42
  • Safety Research 60
  • Media Technology 38
  • Education 106
  • Radiological and Ultrasound Technology 16
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Citations per field
00.5×4.6×
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Citations per year

Countries citing papers authored by Mary Pearson

Since Specialization
Citations

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

Fields of papers citing papers by Mary Pearson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Mary Pearson, 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 Mary Pearson Line = papers co-authored together Mary Pearson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201061
2 199553
3 199546
4 201918
5 201915
6
Modeling Universal Design for Learning Techniques to Support Multicultural Education for Pre-Service Secondary Educators.
201513
7 201912
8 201911
9 201911
10
An Examination of Skill Learning Using Direct Instruction.
20058
11 20207
12 20206
13 20206
14 20205
15 19965
16 20205
17 20205
18
Predicting and Understanding Success in an Innovation-Based Learning Course.
20204
19 20254
20 19953

About Mary Pearson

Mary Pearson is a scholar working on Education, Computer Science Applications, Media Technology, Biomedical Engineering and Sociology and Political Science, having authored 35 papers that have together received 310 indexed citations. Recurring topics across this work include Biomedical and Engineering Education (7 papers), Online Learning and Analytics (6 papers), Experimental Learning in Engineering (6 papers), E-Learning and Knowledge Management (6 papers), Problem and Project Based Learning (4 papers), Engineering Education and Curriculum Development (4 papers), Innovative Teaching Methods (3 papers) and Disability Education and Employment (2 papers). The work is most often cited by research in Computer Science Applications (42 citations), Safety Research (60 citations), Media Technology (38 citations), Education (106 citations) and Radiological and Ultrasound Technology (16 citations). Mary Pearson has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Bruce B. Frey, Jennifer Ng, Ryan O. Kellems, Mary E. Morningstar, Patricia M. Noonan, Kendra Williams-Diehm, Ellen Swartz, James M. Shumway, Dan Ewert and Ha Young Kim. Their work appears in journals such as Career Development for Exceptional Individuals, Journal of Professional Nursing, Multicultural education, International Journal of Special Education (IJSE) and 2021 IEEE Frontiers in Education Conference (FIE).

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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