Jin Mao

673 citations
11 papers · 402 indexed · 1 hit paper · h-index 6
Topics
Innovative Teaching and Learning Methods (2 papers)Education and Learning Interventions (2 papers)Gender and Technology in Education (2 papers)

In The Last Decade

Jin Mao

8 papers receiving 374 citations

Hit Papers

Generative Artificial Intelligence in Education and Its I...20232026202420252023255075100

Peers

Jin Mao
Comparison fields: 5 of 67
  • Education 191
  • Sociology and Political Science 131
  • Information Systems 115
  • Computer Science Applications 86
  • Developmental and Educational Psychology 51
Replace Gila Kurtz with:
Gila Kurtz Israel
Ahlam Mohammed Al-Abdullatif Saudi Arabia
Kamal Ahmed Soomro Pakistan
Abdulrahman M. Al-Zahrani Saudi Arabia
Habibah Ab Jalil Malaysia
Selcan Kilis Türkiye
Tim Fütterer Germany
Sijia Xue China
Kumar Laxman New Zealand
Jin Mao relative to Gila Kurtz Israel Gila Kurtz's profile →
Citations per field
00.5×2.6×
Gila Kurtz · 1×
Citations per year

Countries citing papers authored by Jin Mao

Since Specialization
Citations

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

Fields of papers citing papers by Jin Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Mao. A scholar is included among the top collaborators of Jin Mao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jin Mao. Jin Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
#WorkIndexed citations
1 0
2 0
3 7
4
Generative Artificial Intelligence in Education and Its Implications for Assessmentbreakdown →
105
5 1
6 19
7 219
8 13
9 36
10
The effects of assessment strategies and self -regulated learning (SRL) skills on college students' skill-based and cognitive learning outcomes and perceptions of assessment for learning
0
11
ARCS Model and Instructional Design for Adult Learners in Online Learning Environment
2

About Jin Mao

Jin Mao is a scholar working on Developmental and Educational Psychology, Gender Studies and Computer Science Applications, having authored 11 papers that have together received 402 indexed citations. Recurring topics across this work include Innovative Teaching and Learning Methods (2 papers), Education and Learning Interventions (2 papers) and Gender and Technology in Education (2 papers). The work is most often cited by research in Health Informatics (31 citations), Computer Science Applications (86 citations) and Communication (48 citations). Jin Mao has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Baiyun Chen, Juhong Liu, Stephen A. Sivo, Kyle L. Peck, Gian Paolo Rossi, Dirk Ifenthaler, Enilda Romero‐Hall, Thomas C. Reeves, Tutaleni I. Asino and Bryan Roche. Their work appears in journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and Educational Technology Research and Development.

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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