Jui-Long Hung

58 papers receiving 1.6k citations

Peers

Jui-Long Hung
Comparison fields: 5 of 102
  • Computer Science Applications 735
  • Management Information Systems 268
  • Developmental and Educational Psychology 270
  • Information Systems 465
  • Education 536
Replace Uwe Matzat with:
Uwe Matzat Netherlands
Anuradha Mathrani New Zealand
Jarkko T Suhonen Finland
Mohamed Amine Chatti Germany
Ángel Hernández-García Spain
Thomas Andreas Herrmann Germany
Suraya Binti Hamid Malaysia
Pedro Teixeira Isaias Portugal
Wen‐Hsiung Wu Taiwan
Shaíley Minocha United Kingdom
Jui-Long Hung relative to Uwe Matzat Netherlands Uwe Matzat's profile →
Citations per field
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Uwe Matzat · 1×
Citations per year

Countries citing papers authored by Jui-Long Hung

Since Specialization
Citations

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

Fields of papers citing papers by Jui-Long Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jui-Long Hung. 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 Jui-Long Hung. The network helps show where Jui-Long Hung may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011175
2 2010164
3
Revealing Online Learning Behaviors and Activity Patterns and Making Predictions with Data Mining Techniques in Online Teaching
2008113
4 2016110
5 201991
6 201985
7 201584
8 201779
9 201370
10 201667
11
Integrating Data Mining in Program Evaluation of K-12 Online Education
201263
12 202055
13 201950
14 200948
15 201546
16 202039
17 201934
18 200932
19 202229
20 202323

About Jui-Long Hung

Jui-Long Hung is a scholar working on Computer Science Applications, Developmental and Educational Psychology, Education, Artificial Intelligence and Information Systems, having authored 64 papers that have together received 1.8k indexed citations. Recurring topics across this work include Online Learning and Analytics (32 papers), Innovative Teaching and Learning Methods (19 papers), Online and Blended Learning (18 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers), Imbalanced Data Classification Techniques (4 papers), Educational Technology and Assessment (4 papers), Knowledge Management and Sharing (3 papers) and Data Stream Mining Techniques (3 papers). The work is most often cited by research in Computer Science Applications (735 citations), Management Information Systems (268 citations), Developmental and Educational Psychology (270 citations), Information Systems (465 citations) and Education (536 citations). Jui-Long Hung has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Ke Zhang, Brett E. Shelton, Xu Du, Juan Yang, Wu He, Yu‐Chang Hsu, Kerry Rice, Jiancheng Shen, Haichao Zheng and Patrick R. Lowenthal. Their work appears in journals such as Data Technologies and Applications, IEEE Transactions on Learning Technologies, Distance Education, Journal of Computing in Higher Education and Interactive Learning Environments.

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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