Tamara Tate

25 papers receiving 734 citations

Tamara Tate's Hit Papers

Comparing the quality of human and ChatGPT feedback of students’ writing 2024 · 202 citations
2020+1+2Years since publication50100150200

Peers

Tamara Tate
Comparison fields: 5 of 76
  • Health Informatics 177
  • Computer Science Applications 174
  • Developmental and Educational Psychology 154
  • Education 234
  • Artificial Intelligence 233
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Austin Pack United States
Marzuki Marzuki Indonesia
Kai Guo Hong Kong
Alex Barrett United States
Dongkwang Shin South Korea
Sin Wang Chong United Kingdom
Chunpeng Zhai Australia
Utami Widiati Indonesia
Weijiao Huang Hong Kong
Charles Fadel
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Countries citing papers authored by Tamara Tate

Since Specialization
Citations

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

Fields of papers citing papers by Tamara Tate

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Comparing the quality of human and ChatGPT feedback of students’ writing
Hit paper breakdown →
2024202
2
The affordances and contradictions of AI-generated text for writers of english as a second or foreign language
Hit paper breakdown →
2023125
3 2023120
4 202271
5
A meta-analysis of writing treatments for students in grades 6–12.
Hit paper breakdown →
202344
6 202440
7 202337
8 202416
9 201615
10 202114
11 201914
12 202413
13 201912
14 20188
15 20218
16 20226
17 20245
18 20195
19 20253
20 20222

About Tamara Tate

Tamara Tate is a scholar working on Education, Developmental and Educational Psychology, Literature and Literary Theory, Artificial Intelligence and Health Informatics, having authored 25 papers that have together received 767 indexed citations. Recurring topics across this work include Writing and Handwriting Education (14 papers), Innovative Teaching and Learning Methods (7 papers), Discourse Analysis in Language Studies (5 papers), Reading and Literacy Development (4 papers), Text Readability and Simplification (4 papers), Topic Modeling (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Health Informatics (177 citations), Computer Science Applications (174 citations), Developmental and Educational Psychology (154 citations), Education (234 citations) and Artificial Intelligence (233 citations). Tamara Tate has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Mark Warschauer, Waverly Tseng, Sharin Jacob, Youngsun Moon, Carol Booth Olson, Qian Du, Soobin Yim, Thomas J. Webster, Jacob Steiss and Jiali Wang. Their work appears in journals such as Reading and Writing, Computers and Education Artificial Intelligence, Technology Knowledge and Learning, Scientific Reports and Peabody Journal of Education.

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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