Hai Min Dai

467 total citations · 1 hit paper
9 papers, 370 citations indexed

About

Hai Min Dai is a scholar working on Education, Computer Science Applications and Sociology and Political Science. According to data from OpenAlex, Hai Min Dai has authored 9 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Education, 5 papers in Computer Science Applications and 3 papers in Sociology and Political Science. Recurrent topics in Hai Min Dai's work include Online Learning and Analytics (5 papers), Online and Blended Learning (3 papers) and Technology Adoption and User Behaviour (2 papers). Hai Min Dai is often cited by papers focused on Online Learning and Analytics (5 papers), Online and Blended Learning (3 papers) and Technology Adoption and User Behaviour (2 papers). Hai Min Dai collaborates with scholars based in China, Macao and Australia. Hai Min Dai's co-authors include Timothy Teo, Natasha Anne Rappa, Fang Huang, Todd L. Sandel, Shuo Guo, Junqiang Zhao, Jian Liao, Ming Liu, Wei Zhang and Li Liu and has published in prestigious journals such as Computers in Human Behavior, Computers & Education and Higher Education.

In The Last Decade

Hai Min Dai

8 papers receiving 355 citations

Hit Papers

Explaining Chinese university students’ continuance learn... 2020 2026 2022 2024 2020 50 100 150 200

Peers

Hai Min Dai
Comparison fields: 5 of 54
  • Information Systems and Management 158
  • Computer Science Applications 155
  • Education 114
  • Sociology and Political Science 86
  • Information Systems 66
Replace Ahlam Mohammed Al-Abdullatif with:
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Harun Çiğdem Türkiye
Thomas Lerche Germany
Omar A. Alismaiel Saudi Arabia
Ritanjali Panigrahi India
Céline Cocquyt Belgium
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Mas Nida Md. Khambari Malaysia
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Ahlam Mohammed Al-Abdullatif Saudi Arabia View profile →
Citations per field, relative to Hai Min Dai
Hai Min Dai · 1×
Citations per year, relative to Hai Min Dai
Hai Min Dai · 1×

Countries citing papers authored by Hai Min Dai

Since Specialization
Citations

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

Fields of papers citing papers by Hai Min Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai Min Dai. 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 Hai Min Dai. The network helps show where Hai Min Dai may publish in the future.

Co-authorship network of co-authors of Hai Min Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Hai Min Dai. A scholar is included among the top collaborators of Hai Min Dai 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 Hai Min Dai. Hai Min Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
# Work Indexed citations
1 1
2 0
3 5
4 2
5 9
6 104
7 14
8
Explaining Chinese university students’ continuance learning intention in the MOOC setting: A modified expectation confirmation model perspective breakdown →
206
9 29

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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