Ling-Hsiu Chen
Impact in
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- Online Learning and Analytics
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- Customer Service Quality and Loyalty
- Job Satisfaction and Organizational Behavior
Papers in
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- Online and Blended Learning 5
- Innovative Teaching Methods 3
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- Online Learning and Analytics 6
- Teaching and Learning Programming 3
- Co-authors
- Ying‐Feng Kuo (2 shared papers)Chin‐Ling Chen (1 shared paper)Hung‐Ju Lin (1 shared paper)Rung-Ching Chen (1 shared paper)
In The Last Decade
Ling-Hsiu Chen
16 papers receiving 381 citations
Peers
Comparison fields: 5 of 71
- Computer Science Applications 107
- Organizational Behavior and Human Resource Management 121
- Information Systems and Management 67
- Developmental and Educational Psychology 80
- Education 132
Countries citing papers authored by Ling-Hsiu Chen
This map shows the geographic impact of Ling-Hsiu Chen'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 Ling-Hsiu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling-Hsiu Chen more than expected).
Fields of papers citing papers by Ling-Hsiu Chen
This network shows the impact of papers produced by Ling-Hsiu Chen. 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 Ling-Hsiu Chen. The network helps show where Ling-Hsiu Chen may publish in the future.
Co-authors
The 4 scholars most cited alongside Ling-Hsiu Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 107 | |
| 2 | 2010 | 96 | |
| 3 | 2009 | 60 | |
| 4 | 2009 | 56 | |
| 5 | 2019 | 45 | |
| 6 | 2011 | 37 | |
| 7 | 2009 | 8 | |
| 8 | 2008 | 6 | |
| 9 | 2017 | 4 | |
| 10 | 2021 | 2 | |
| 11 | INTELLIGENT E-LEARNING SYSTEM WITH PERSONALIZED MISCONCEPTION DIAGNOSE AND LEARNING PATH GUIDANCE | 2009 | 2 |
| 12 | 2017 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2008 | 1 | |
| 15 | 2014 | 1 | |
| 16 | THE RESEARCH OF ONLINE SERVICE RECOVERY BASED ON KANO'S MODEL | 2009 | 1 |
| 17 | 2022 | 0 |
About Ling-Hsiu Chen
Ling-Hsiu Chen is a scholar working on Education, Computer Science Applications, Developmental and Educational Psychology, Information Systems and Artificial Intelligence, having authored 17 papers that have together received 429 indexed citations. Recurring topics across this work include Innovative Teaching and Learning Methods (6 papers), Online Learning and Analytics (6 papers), Online and Blended Learning (5 papers), Innovative Teaching Methods (3 papers), Customer Service Quality and Loyalty (3 papers), Teaching and Learning Programming (3 papers), Technology Adoption and User Behaviour (3 papers) and Intelligent Tutoring Systems and Adaptive Learning (2 papers). The work is most often cited by research in Computer Science Applications (107 citations), Organizational Behavior and Human Resource Management (121 citations), Information Systems and Management (67 citations), Developmental and Educational Psychology (80 citations) and Education (132 citations). Ling-Hsiu Chen has collaborated with scholars based in Taiwan, China and Vietnam. Frequent co-authors include Ying‐Feng Kuo, Chin‐Ling Chen, Hung‐Ju Lin and Rung-Ching Chen. Their work appears in journals such as Journal of the Association for Information Systems, Computers & Education, Electronic Commerce Research and Applications, Computers in Human Behavior and Total Quality Management & Business Excellence.
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.